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Search Results (564)

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Keywords = bio-fortification

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11 pages, 1317 KiB  
Article
Biofortification of Cucumbers with Iron Using Bio-Chelates Derived from Spent Coffee Grounds: A Greenhouse Trial
by Ana Cervera-Mata, Leslie Lara-Ramos, José Ángel Rufián-Henares, Jesús Fernández-Bayo, Gabriel Delgado and Alejandro Fernández-Arteaga
Agronomy 2024, 14(9), 2063; https://doi.org/10.3390/agronomy14092063 - 9 Sep 2024
Viewed by 290
Abstract
The transformation of spent coffee grounds (SCGs) into hydrochars has been extensively studied in recent years to explore their potential in biofortifying foods and mitigating the plant toxicity associated with SCGs. This study aimed to evaluate the effects of adding activated (ASCG and [...] Read more.
The transformation of spent coffee grounds (SCGs) into hydrochars has been extensively studied in recent years to explore their potential in biofortifying foods and mitigating the plant toxicity associated with SCGs. This study aimed to evaluate the effects of adding activated (ASCG and AH160) and functionalized SCGs, as well as SCG-derived hydrochars (ASCG-Fe and AH160-Fe), on cucumber production and plant iron content. To achieve this, SCGs and SCG-derived hydrochars activated and functionalized with Fe were incorporated into cucumber crops grown in a greenhouse over multiple harvests. Among the treatments, SCG-Fe proved to be the most promising for cucumber production, yielding an average of 25 kg of cumulative production per treatment across three harvests. Regarding iron content, the average results across all harvests showed that SCGs and functionalized SCG-hydrochars matched the performance of the commercial chelate (0.108 vs. 0.11 mg Fe/100 g fresh weight). However, in subsequent harvests, iron appeared to leach out, with the activated bio-products (ASCG and AH160) leaving the highest iron reserves in the soil. Additionally, the hydrochar activated at 160 °C demonstrated the highest utilization efficiency. In conclusion, the incorporation of SCG residues and second-generation residues (hydrochars) shows promise as agents for biofortifying cucumbers. Full article
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<p>Cumulative production of cucumbers during the trial per treatment. AH160: activated hydrochar at 160 °C; AH160-Fe: activated and functionalized hydrochar at 160 °C; ASCG: activated spent coffee grounds; ASCG-Fe: activated and functionalized spent coffee grounds.</p>
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<p>Average Fe content in cucumbers per treatment. AH160: activated hydrochar at 160 °C; AH160-Fe: activated and functionalized hydrochar at 160 °C; ASCG: activated spent coffee grounds; ASCG-Fe: activated and functionalized spent coffee grounds. Different letters indicated statistically significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Fe content in cucumbers per treatment, per harvest. AH160: activated hydrochar at 160 °C; AH160-Fe: activated and functionalized hydrochar at 160 °C; ASCG: activated spent coffee grounds; ASCG-Fe: activated and functionalized spent coffee grounds. Different letters indicated statistically significant differences between different harvests (<span class="html-italic">p</span> &lt; 0.05).</p>
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16 pages, 1522 KiB  
Article
Appropriate Soil Fertilization or Drone-Based Foliar Zn Spraying Can Simultaneously Improve Yield and Micronutrient (Particularly for Zn) Nutritional Quality of Wheat Grains
by Xue Gao, Qiang Zhao, Nuo Yuan, Xiaojing Li, Bin Zhang, Yinghua Zhu, Lingan Kong, Zhaohui Wang and Haiyong Xia
Agriculture 2024, 14(9), 1530; https://doi.org/10.3390/agriculture14091530 - 5 Sep 2024
Viewed by 296
Abstract
To better understand the effects of agronomic practices on yield–nutrition relationships in wheat (Triticum aestivum L.) grains for Zn biofortification while improving yields simultaneously, effects of different soil fertilization and different drone-based foliar spraying treatments were investigated in calcareous soils. For soil [...] Read more.
To better understand the effects of agronomic practices on yield–nutrition relationships in wheat (Triticum aestivum L.) grains for Zn biofortification while improving yields simultaneously, effects of different soil fertilization and different drone-based foliar spraying treatments were investigated in calcareous soils. For soil fertilization, the incorporation of Zn or increasing the N/P ratio in compound fertilizers proved to be effective in enhancing grain Zn concentrations and yields. However, the overall effects of soil fertilization are limited, with a maximal yield increase of only 7.0% and a maximal increase of the grain Zn concentration from 19.4 to 27.0 mg/kg, which is far below the target biofortification value of 40–50 mg/kg. Unfortunately, there was a negative side effect, which decreased Fe and Mn concentrations and the Fe bioavailability. Notably, drone-based foliar Zn sprayings increased grain yields from the control 7.5 t/ha to 8.6 t/ha at ZnO treatment by 12.0% and 8.8 t/ha at ZnSO4·7H2O treatment by 17.3%. Meanwhile, grain Zn concentrations were increased from the control 33.5 mg/kg to 41.9 mg/kg at ZnO treatment by 25.1% and 43.6 mg/kg at ZnSO4·7H2O treatment by 30.1%. Treatments with ZnSO4·7H2O increased grain Zn concentrations and accumulation more so than ZnO, indicating the importance of chemical Zn forms in determining the effectiveness of foliar spraying. Moreover, foliar Zn sprayings simultaneously increased grain concentrations and accumulation of Fe, Mn and Cu, demonstrating multiple benefits. There were positive correlations between Zn and Fe, Mn or Cu, indicating synergistic interactions. Compared to micronutrients, concentrations of grain macronutrients (N, P, K, Ca and Mg) were less affected. Thus, a dual-benefit in both grain yields and micronutrient (particularly for Zn) nutrition could be effectively achieved through appropriate soil fertilization and foliar Zn spraying. These findings provide a better understanding of the yield–nutrition relationship among wheat grain yields, Zn and other nutrient elements for a better integrated manipulation to achieve a win–win situation in yield and nutrition. Full article
(This article belongs to the Special Issue Research on Technologies for Achieving High-Yield Wheat)
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<p>Principle component analysis (PCA) of the effects of different soil fertilization treatments (<b>a</b>), foliar spraying treatments (<b>b</b>), and all soil and foliar treatments (<b>c</b>) on various investigated parameters of wheat plants. 15-15-15, 17-17-17, 26-10-15, and 30-10-11 are ratios of N-P<sub>2</sub>O<sub>5</sub>-K<sub>2</sub>O in compound fertilizers (<b>a</b>,<b>c</b>). In panels (<b>b</b>,<b>c</b>): CK: spraying of deionized water; ZnO: spraying of a mixed solution with deionized water and ZnO; Zn: spraying of a mixed solution with deionized water and ZnSO<sub>4</sub>·7H<sub>2</sub>O. The abbreviations of various parameters investigated are as follows: yield (Y), plant height (PH), spike length (SL), spike number (SN), kernel number per spike (KNPS), thousand kernel weight (TKW), HI (harvest index), concentrations of Zn, Fe, Mn, Cu, N, P, K, Ca, Mg and phytate-P, ratios of phytate-P/P, and molar ratios of phytic acid (PA)/Zn, PA × Ca/Zn, PA/Fe and PA × Ca/Fe in wheat grains.</p>
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<p>Correlation plot representing correlations among investigated grain yields, yield components, other agronomic traits, and grain nutritional parameters of wheat crop across different soil fertilization treatments (<b>a</b>) and across different foliar spraying treatments (<b>b</b>). Negative correlations are displayed in red and positive correlations in blue. The color legend on the right-hand side of correlation plot shows correlation coefficients and the corresponding colors. The intensity of the color is proportional to the correlation coefficient, and the ellipse size demonstrates the range of scattered experimental data points. “*”, “**” and “***” indicate significant correlations at <span class="html-italic">p</span> ≤ 0.05, 0.01 and 0.001, respectively. The abbreviations are as follows: yield (Y), plant height (PH), spike length (SL), spike number (SN), kernel number per spike (KNPS), thousand kernel weight (TKW), harvest index (HI), concentrations of Zn, Fe, Mn, Cu, N, P, K, Ca, Mg and phytate-P, ratios of phytate-P/P, and molar ratios of phytic acid (PA)/Zn, PA × Ca/Zn, PA/Fe and PA × Ca/Fe in wheat grains.</p>
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<p>A schematic diagram showing integrative strategies for simultaneously achieving yield increase and wheat grain Zn biofortification.</p>
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62 pages, 2191 KiB  
Review
The Role of Low-Molecular-Weight Organic Acids in Metal Homeostasis in Plants
by Ilya V. Seregin and Anna D. Kozhevnikova
Int. J. Mol. Sci. 2024, 25(17), 9542; https://doi.org/10.3390/ijms25179542 - 2 Sep 2024
Viewed by 417
Abstract
Low-molecular-weight organic acids (LMWOAs) are essential O-containing metal-binding ligands involved in maintaining metal homeostasis, various metabolic processes, and plant responses to biotic and abiotic stress. Malate, citrate, and oxalate play a crucial role in metal detoxification and transport throughout the plant. This review [...] Read more.
Low-molecular-weight organic acids (LMWOAs) are essential O-containing metal-binding ligands involved in maintaining metal homeostasis, various metabolic processes, and plant responses to biotic and abiotic stress. Malate, citrate, and oxalate play a crucial role in metal detoxification and transport throughout the plant. This review provides a comparative analysis of the accumulation of LMWOAs in excluders, which store metals mainly in roots, and hyperaccumulators, which accumulate metals mainly in shoots. Modern concepts of the mechanisms of LMWOA secretion by the roots of excluders and hyperaccumulators are summarized, and the formation of various metal complexes with LMWOAs in the vacuole and conducting tissues, playing an important role in the mechanisms of metal detoxification and transport, is discussed. Molecular mechanisms of transport of LMWOAs and their complexes with metals across cell membranes are reviewed. It is discussed whether different endogenous levels of LMWOAs in plants determine their metal tolerance. While playing an important role in maintaining metal homeostasis, LMWOAs apparently make a minor contribution to the mechanisms of metal hyperaccumulation, which is associated mainly with root exudates increasing metal bioavailability and enhanced xylem loading of LMWOAs. The studies of metal-binding compounds may also contribute to the development of approaches used in biofortification, phytoremediation, and phytomining. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>Participation of organic acids in metal transport and detoxification in plants. A generalized scheme is presented, without taking tissue specificity into account. The release of root exudates containing various organic acids (OAs) is the basis of the exclusion tolerance mechanism. Malate is secreted by aluminum-activated malate transporter 1 (ALMT1), whereas citrate is secreted by some members of the multidrug and toxic compound extrusion transporter (MATE) family (e.g., AtMATE, BoMATE, EcMATE1, FeMATE1, GmMATE13/47, GsMATE, HvAACT1, MtMATE66, OsFRDL2/4, PtrMATE1, SbMATE, ScFRDL2, TaMATE1B, VuMATE1/2, and ZmMATE1), which are located at the plasma membrane of the root rhizodermal cells. In the rhizosphere, OAs bind metal ions (Me<sup>n+</sup>) with the formation of complexes of various structures (Me-OA complexes), which affects metal entry into the plant. Aluminum ions (Al<sup>3+</sup>) in the cell walls of root rhizodermal cells may bind to malate, which is transported there by ALMT1, and the resulting complexes (Al-malate) are transported across the plasma membrane into the cytosol with the involvement of nodulin 26-like intrinsic protein (NIP1;2). In the cell, the major site of OA biosynthesis is the mitochondria and the glyoxisomes, where the reactions of the Krebs cycle and the glyoxylate cycle, respectively, take place. Pyruvate transport into the mitochondria is mediated by the mitochondrial pyruvate carrier (MPC). The transport of other OAs across the inner membrane of the mitochondria is carried out by the exchange mechanism with the involvement of dicarboxylate carriers (DICs), dicarboxylate/tricarboxylate carrier (DTC), and succinate/fumarate carrier (SFC). Having entered the cytosol via the plasma membrane transporters, metal ions bind to different low-molecular-weight ligands, including OAs, though the stability of Me-OA complexes at neutral pH values is lower than that of metal complexes with nicotianamine and histidine. The possibility of translocation of Me-OA complexes across the tonoplast cannot be excluded, though the mechanism of such transport is unknown yet (this pathway is designated by a dotted line and the unknown transporter by a question mark). The entry of metal ions into the vacuole is carried out by different vacuolar transporters, whereas the transport of OAs across the tonoplast is mediated by the tonoplast dicarboxylate transporter (tDT) and the vacuolar citrate/H+ symporter Cit1 (the latter is not shown in the figure). In <span class="html-italic">A. thaliana</span>, OA transport across the tonoplast is also carried out by ALMT4 and ALMT6, whose gene expression was shown in stomatal guard cells, and for ALMT4—also in leaf mesophyll. Potential substrates for the mitochondrial carriers (DICs, DTC, and SFC) and the vacuolar OA-transporting proteins (tDT and ALMT4) are shown next to the corresponding transporters/carriers/channels. Metal binding to OAs in the vacuole is an important internal metal detoxification mechanism. The transport of malate across the plasma membrane in stomatal guard cells in <span class="html-italic">A. thaliana</span> may be carried out by ALMT12 and ABCB14 (ATP-binding cassette subfamily B protein), being directly involved in the stomatal movement and indirectly involved in maintaining metal homeostasis. Metals are translocated from roots to shoots via the xylem mainly as complexes with OAs. Citrate is transported into the xylem vessels by the FRD3 transporter (ferric chelate reductase defective 3) located at the plasma membrane of root central cylinder cells, as well as other proteins of the MATE family (e.g., OsFRDL1, PtrMATE1, MtMATE66, and ScFRDL1). Plastidic transport of OAs in the cells of photosynthetic tissues is carried out via a double-transporter system at the inner chloroplast membrane involving the plastidic 2-oxoglutarate/malate transporter (OMT1) and the general dicarboxylate transporter (DCT1). The arrows show the direction of transport. Designations: Acetyl-CoA, acetyl coenzyme A; ACO, aconitase; CoA-SH, coenzyme A; CS, citrate synthase; FAD-SDH, FAD-succinic dehydrogenase; FUM, fumarase; GABA, gamma-aminobutyric acid; Glu, glutamic acid; ICL, isocitrate lyase; MS, malate synthase; NAD-IDH, NAD-isocitrate dehydrogenase; NAD-MDH, NAD-malate dehydrogenase; NAD-ME, NAD-malic enzyme; NAD-OGDH, NAD-2-oxoglutarate dehydrogenase; NADP-ME, NADP-malic enzyme; NADP-IDH, NADP-isocitrate dehydrogenase; PDC, pyruvate dehydrogenase complex; PEP, phosphoenolpyruvate; PEPC, phosphoenolpyruvate carboxylase; PEPCK, phosphoenolpyruvate carboxykinase; PPDK, pyruvate orthophosphate dikinase; STK, succinate thiokinase (succinyl-CoA synthetase).</p>
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<p>Protonation/deprotonation equilibria of citric (<b>A</b>) and malic (<b>B</b>) acids. p<span class="html-italic">K</span><sub>α</sub> values for citric and malic acids are presented according to [<a href="#B116-ijms-25-09542" class="html-bibr">116</a>,<a href="#B117-ijms-25-09542" class="html-bibr">117</a>], respectively.</p>
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25 pages, 4661 KiB  
Article
Effects of UV-B and UV-C Spectrum Supplementation on the Antioxidant Properties and Photosynthetic Activity of Lettuce Cultivars
by Ernest Skowron, Magdalena Trojak and Ilona Pacak
Int. J. Mol. Sci. 2024, 25(17), 9298; https://doi.org/10.3390/ijms25179298 - 27 Aug 2024
Viewed by 342
Abstract
Indoor farming systems enable plant production in precisely controlled environments. However, implementing stable growth conditions and the absence of stress stimulants can weaken plants’ defense responses and limit the accumulation of bioactive, health-beneficial phytochemicals. A potential solution is the controlled application of stressors, [...] Read more.
Indoor farming systems enable plant production in precisely controlled environments. However, implementing stable growth conditions and the absence of stress stimulants can weaken plants’ defense responses and limit the accumulation of bioactive, health-beneficial phytochemicals. A potential solution is the controlled application of stressors, such as supplemental ultraviolet (UV) light. To this end, we analyzed the efficiency of short-term pre-harvest supplementation of the red–green–blue (RGB, LED) spectrum with ultraviolet B (UV-B) or C (UV-C) light to boost phytochemical synthesis. Additionally, given the biological harm of UV radiation due to high-energy photons, we monitored plants’ photosynthetic activity during treatment and their morphology as well as sensory attributes after the treatment. Our analyses showed that UV-B radiation did not negatively impact photosynthetic activity while significantly increasing the overall antioxidant potential of lettuce through enhanced levels of secondary metabolites (total phenolics, flavonoids, anthocyanins), carotenoids, and ascorbic acid. On the contrary, UV-C radiation-induced anthocyanin accumulation in the green leaf cultivar significantly harmed the photosynthetic apparatus and limited plant growth. Taken together, we showed that short-term UV-B light supplementation is an efficient method for lettuce biofortification with healthy phytochemicals, while UV-C treatment is not recommended due to the negative impact on the quality (morphology, sensory properties) of the obtained leafy products. These results are crucial for understanding the potential of UV light supplementation for producing functional plants. Full article
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<p>Total phenolic content (TPC) of control (RGB), UV-B treated (RGB + UV-B), or UV-C treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with (<b>a</b>) green (cv. Lollo Bionda) and (<b>b</b>) reddish leaf (cv. Lollo Rossa) at 20 DAS (days after sowing), estimated as µg gallic acid equivalents per mg of fresh weight (FW). Each bar represents the average ± SD of six independent measurements (<span class="html-italic">n</span> = 6). Different letters (a–c) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>Total flavonoid content (TFC) of control (RGB), UV-B treated (RGB + UV-B), or UV-C treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with (<b>a</b>) green (cv. Lollo Bionda) and (<b>b</b>) reddish leaf (cv. Lollo Rossa) at 20 DAS (days after sowing), estimated as µg rutin equivalents per mg of fresh weight (FW). Each bar represents the average ± SD of six independent measurements (<span class="html-italic">n</span> = 6). Different letters (a–c) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>Anthocyanins (ANT) concentration of control (RGB), UV-B treated (RGB + UV-B), or UV-C treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with (<b>a</b>) green (cv. Lollo Bionda) and (<b>b</b>) reddish leaf (cv. Lollo Rossa) at 20 DAS (days after sowing), estimated as arbitrary unit (AU) per g of fresh weight (FW). Each bar represents the average ± SD of six independent measurements (<span class="html-italic">n</span> = 6). Different letters (a–c) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>Initial ascorbic acid (AsA) level, total AsA pool (AsA + DAsA), and total AsA to initial AsA ratio (AsA + DAsA/AsA) of control (RGB), UV-B treated (RGB + UV-B), or UV-C treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with (<b>a</b>,<b>c</b>) green (cv. Lollo Bionda) and (<b>b</b>,<b>d</b>) reddish leaf (cv. Lollo Rossa) at 20 DAS (days after sowing). Initial AsA was estimated directly in a sample by bipyridyl method, while the total AsA pool was assessed after additional reduction of dehydroascorbic acid (DAsA) with dithiothreitol (DTT). Each bar represents the average ± SD of six independent measurements (<span class="html-italic">n</span> = 6). Different letters (a–c) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>The total antioxidant capacity (<b>a</b>,<b>b</b>) and DPPH radical scavenging activity rate (<b>c</b>,<b>d</b>) of control (RGB), UV-B-treated (RGB + UV-B), or UV-C-treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with (<b>a</b>,<b>c</b>) green (cv. Lollo Bionda) and (<b>b</b>,<b>d</b>) reddish leaf (cv. Lollo Rossa) at 20 DAS (days after sowing), estimated as µg BHT equivalents per mg of fresh weight (FW). Each bar represents the average ± SD of six independent measurements (<span class="html-italic">n</span> = 6). Different letters (a–c) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>Densitometric analysis of RuBisCO large (LSU) and small (SSU) subunit of control (RGB), UV-B-treated (RGB + UV-B), or UV-C-treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with (<b>a</b>) green leaf (cv. Lollo Bionda) or (<b>b</b>) reddish leaf (cv. Lollo Rossa) after short-term (1–4 day) progressive exposition to UV light at 20 DAS (days after sowing). Beneath (<b>c</b>) the LSU (53 kDa) or SSU (14 kDa) protein bands of leaf proteins resolved in a 4–20% TGX polyacrylamide gel and visualized with Coomassie Stain. The relative amounts (%) of RuBisCO subunits were normalized to RGB control. Bars represent the average ± SD of three independent measurements (<span class="html-italic">n</span> = 3). Different letters (a–c for LSU or a’–c’ for SSU) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>Chlorophyll <span class="html-italic">a</span> fluorescence analysis of control (RGB), UV-B-treated (RGB + UV-B) or UV-C-treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with green leaf (cv. Lollo Bionda) after short-term (1–4 day) progressive exposition to UV light. (<b>a</b>) The maximum quantum yield of PSII photochemistry (Fv/Fm), (<b>b</b>) effective quantum yield of PSII photochemistry (ΦPSII), (<b>c</b>) quantum yield of regulated (ΦNPQ), (<b>d</b>) non-regulated energy dissipation (ΦNO), (<b>e</b>) non-photochemical quenching (NPQ), and (<b>f</b>) electron transport rate (ETR). The analyses were carried out with 55 μmol m<sup>−2</sup> s<sup>−1</sup> of blue (450 nm) actinic light. Each data point represents the average ± SD of six independent measurements (<span class="html-italic">n</span> = 6). Different letters (a, b) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>Chlorophyll <span class="html-italic">a</span> fluorescence analysis of control (RGB), UV-B-treated (RGB + UV-B), or UV-C-treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with reddish leaf (cv. Lollo Rossa) after short-term (1–4 day) progressive exposition to UV light. (<b>a</b>) The maximum quantum yield of PSII photochemistry (Fv/Fm), (<b>b</b>) effective quantum yield of PSII photochemistry (ΦPSII), (<b>c</b>) quantum yield of regulated (ΦNPQ), (<b>d</b>) non-regulated energy dissipation (ΦNO), (<b>e</b>) non-photochemical quenching (NPQ), and (<b>f</b>) electron transport rate (ETR). The analyses were conducted with 55 μmol m<sup>−2</sup> s<sup>−1</sup> of blue (450 nm) actinic light. Each data point represents the average ± SD of six independent measurements (<span class="html-italic">n</span> = 6). Different letters (a, b) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>The rate of lipid peroxidation assessed with thiobarbituric acid reactive substances (TBARS) level of control (RGB), UV-B-treated (RGB + UV-B), or UV-C-treated (RGB + UV-C) plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivars with (<b>a</b>) green (cv. Lollo Bionda) and (<b>b</b>) reddish leaf (cv. Lollo Rossa) at 20 DAS (days after sowing), estimated with TBARS assay. Each bar represents the average ± SD of six independent measurements (<span class="html-italic">n</span> = 6). Different letters (a, b) indicate significant differences between treatments at <span class="html-italic">p</span> = 0.05 with a Tukey’s HSD test.</p>
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<p>Morphology of 20-DAS plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with green leaf (cv. Lollo Bionda, LB) grown under (<b>a</b>) RGB (C, control), (<b>b</b>) RGB + UV-B (UV-B supplemented, 311 nm), or (<b>c</b>) RGB + UV-C (UV-C supplemented, 254 nm) spectrum.</p>
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<p>Morphology of 20-DAS plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with reddish leaf (cv. Lollo Rossa, LR) grown under (<b>a</b>) RGB (C, control), (<b>b</b>) RGB + UV-B (UV-B supplemented, 311 nm), or (<b>c</b>) RGB + UV-C (UV-C supplemented, 254 nm) spectrum.</p>
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<p>Sensory attributes of leaf samples of 20-DAS plants of <span class="html-italic">baby leaf</span> lettuce (<span class="html-italic">Lactuca sativa</span> var. <span class="html-italic">crispa</span> L.) cultivar with (<b>a</b>) green (cv. Lollo Bionda, LB) or (<b>b</b>) reddish leaf (cv. Lollo Bionda, LB) grown under RGB (C, control), RGB + UV-B (UV-B supplemented, 311 nm), or RGB + UV-C (UV-C supplemented, 254 nm) spectrum. The attributes of the blinded fresh leaf samples: appearance, sweetness, bitterness, crispness, aftertaste and overall assessment were scored at a scale of 0–5 (where 5 is maximal, 3—neutral, and 0—the least score) by 10 untrained consumers, aged 25–65 years (equal gender ratio). Each data point represents the average of ten independent tests (<span class="html-italic">n</span> = 10).</p>
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<p>The light spectra of lamps were recorded with a spectroradiometer at four locations and then averaged. All plants tested were grown at 200 µmol m<sup>−2</sup> s<sup>−1</sup> of RGB (red–green–blue) spectrum (R–G–B; 661:633:520:434 nm) solely ((<b>a</b>), control) for 20 days or under RGB spectrum supplemented 4 days prior to harvest with increasing doses of UV-B (311 nm) (<b>b</b>) or UV-C (254 nm) (<b>c</b>).</p>
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17 pages, 6263 KiB  
Article
Heterologous Expression of Sunflower HaHPT and HaTMT Genes Enhances Rice-Grain Vitamin E Content
by Shuang Song, Hang Li, Shaoyan Lin, Xiaoou Dong, Ruiping Tian, Zewan Wu, Qing Li, Mingyi Li, Keying Zhang, Xi Liu, Jianmin Wan and Linglong Liu
Plants 2024, 13(17), 2392; https://doi.org/10.3390/plants13172392 - 27 Aug 2024
Viewed by 395
Abstract
Insufficient dietary vitamin intake can lead to severe health conditions in humans. Improving the vitamin E (VE) content of food crops such as rice through breeding is an economical and effective means to alleviate this problem. In this study, Homogentisate phytyltransferase (HPT [...] Read more.
Insufficient dietary vitamin intake can lead to severe health conditions in humans. Improving the vitamin E (VE) content of food crops such as rice through breeding is an economical and effective means to alleviate this problem. In this study, Homogentisate phytyltransferase (HPT) and γ-tocopherol methyltransferase (γ-TMT), two genes derived from sunflower (Helianthus annuus L., a high VE species), were introduced into an elite rice (Oryza sativa L.) cultivar “Ningjing 7” for biofortification. We verified the successful expression of the two genes in multiple transformation events. High-performance liquid chromatography revealed that transgenic plants expressing either HaHPT alone or HaHPT and HaTMT accumulate more VE compared with the wild type. We also revealed that the level of α-tocopherol, the form of VE with the highest biological activity, had increased to 2.33 times in transgenic HaTMT plants compared with the wild type. Transcriptome analysis revealed that the expression levels of some chlorophyll synthesis pathway genes related to VE precursor synthesis significantly increased during grain filling in transgenic rice grains. No difference in agronomic traits was observed between the transgenic plants and their wild type except for a slightly reduced plant height associated with the transgenic plants. These data demonstrate that the heterologous expression of HaHPT gene is effective in increasing the total VE content, while HaTMT plays an important role in the relative abundance of α-tocopherol in rice grains. This study demonstrates a promising strategy for breeding rice with elevated VE content via metabolic engineering. Full article
(This article belongs to the Special Issue Molecular Breeding and Germplasm Improvement of Rice—2nd Edition)
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<p>The order of peaks in the HPLC assay corresponding to various vitamin E (VE) components. The peak from left to right: δ-3T, δ-tocotrienol; γ-3T (in brown), γ-tocotrienol; α-3T, α-tocotrienol; δ-T, δ-tocopherol; γ-T, γ-tocopherol; α-T, α-tocopherol. The purple line represents the standards of various VE components, while the black line indicates the chromatography curve of the measured sample isolated from dehusked rice grains.</p>
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<p>Schematic diagram of single-gene and double-gene co-transformation vectors. Structure A is the schematic diagram of <span class="html-italic">γ-tocopherol methyltransferase</span> (<span class="html-italic">γ-TMT</span>) transgenic construct. Structure B is the schematic diagram of <span class="html-italic">Homogentisate phytyltransferase</span> (<span class="html-italic">HPT</span>) transgenic construct. Structure C is the schematic diagram of <span class="html-italic">HaTMT</span> and <span class="html-italic">HaHPT</span> double-gene construct. LB: Left border. RB: Right border. <span class="html-italic">p35S</span>: <span class="html-italic">CaMV35S</span> promoter. <span class="html-italic">HyB</span>: The gene encodes hygromycin B phosphotransferase. <span class="html-italic">pOsR1G1B</span>: Constitutive strong promoter encodes early drought-inducible protein. <span class="html-italic">pZmUbi</span>: Constitutive strong promoter Ubiquitin. <span class="html-italic">HaHPT</span>: Sunflower <span class="html-italic">HPT</span> gene. <span class="html-italic">HaTMT</span>: Sunflower <span class="html-italic">γ-TMT</span> gene. <span class="html-italic">t35S</span>: 35S terminator. <span class="html-italic">tNOS</span>: <span class="html-italic">NOS</span> terminator.</p>
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<p>PCR analysis of transgenic plants. (<b>A</b>) PCR results of wild-type (WT) and <span class="html-italic">HaHPT</span> transgenic plants. (<b>B</b>) PCR results of WT and <span class="html-italic">HaTMT</span> transgenic plants. (<b>C</b>) PCR results of WT and <span class="html-italic">HaHPT</span>-<span class="html-italic">HaTMT</span> double-gene transformants. <span class="html-italic">HaHPT</span>-F/R primer was used to determine the introduction of <span class="html-italic">HaHPT</span> gene in (<b>A</b>). <span class="html-italic">HaTMT</span>-F/R primer was used to determine the introduction of <span class="html-italic">HaTMT</span> gene in (<b>B</b>,<b>C</b>). The different transgenic-positive plants (No. 1–3) from each construct in (<b>A</b>–<b>C</b>) were used in the follow-up phenotypic analysis. MW, molecular weight of markers (DL2000, Takara, Dalian, Liaoning, China).</p>
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<p>Relative expression of two genes in different tissues. (<b>A</b>) <span class="html-italic">HaTMT</span> gene expression difference between wild-type (WT) and transgenic plants. (<b>B</b>) <span class="html-italic">HaHPT</span> gene expression difference between wild-type (WT) and transgenic plants. For each transgenic construct, means ± SEMs from three different transgenic-positive lines are shown here. Statistical difference was determined by two-way (genotype and tissue) ANOVA with Tukey’s multiple comparison test. Means with no letter in common are significantly different at the 0.05 level.</p>
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<p>Comparison of phenotype between transgenic and wild-type (WT) seeds. (<b>A</b>,<b>B</b>) grain appearance quality, grain length (<b>A</b>) and grain width (<b>B</b>) of wild-type and <span class="html-italic">HaTMT</span>, <span class="html-italic">HaHPT</span>, <span class="html-italic">HaTMT-HPT</span> transgenic plants. Scale bar, 3 mm. (<b>C</b>–<b>E</b>) data of 1000-grain weight (<b>C</b>) grain length (<b>D</b>) and grain width (<b>E</b>) of wild-type and <span class="html-italic">HaTMT, HaHPT, HaTMT-HPT</span> transgenic plants. For each transgenic construct, means ± SEMs from three different transgenic-positive lines are shown here. Statistical difference was determined by one-way ANOVA with Dunnett’s multiple comparison test and WT was used as the control group. Means with the same lowercase letters indicate no significant difference from the control at the 0.05 level.</p>
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<p>Comparison of plant traits between transgenic and wild-type (WT) plants. (<b>A</b>–<b>C</b>) plant morphology of wild-type and <span class="html-italic">HaTMT</span> (<b>A</b>), <span class="html-italic">HaHPT</span> (<b>B</b>), <span class="html-italic">HaTMT-HPT</span> (<b>C</b>) transgenic plants at the mature stage. Scale bar, 10 cm. (<b>D</b>–<b>F</b>) plant height (<b>D</b>), tiller number (<b>E</b>) and panicle length (<b>F</b>) for wild-type and <span class="html-italic">HaTMT</span>, <span class="html-italic">HaHPT</span>, <span class="html-italic">HaTMT-HPT</span> transgenic plants. For each transgenic construct, means ± SEMs from three different transgenic-positive lines are shown here. Statistical difference was determined by one-way ANOVA with Dunnett’s multiple comparison test and WT was used as the control group. Means with no letter in common are significantly different at the 0.05 level.</p>
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<p>Contents of total vitamin E including tocopherol and tocotrienol in transgenic plant seeds (μg·g<sup>−1</sup>). For each transgenic construct, means ± SEMs from three different transgenic-positive lines are shown here. Statistical difference was determined by one-way ANOVA with Dunnett’s multiple comparison test and wild type (WT) was used as the control group. Means with no letter in common are significantly different at the 0.05 level.</p>
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<p>Different isomers of vitamin E (VE) in wild-type (WT) and transgenic seeds. All seeds were dehulled for the measurement of VE. (<b>A</b>–<b>C</b>) δ-T (<b>A</b>), γ-T (<b>B</b>), α-T (<b>C</b>) contents of wild-type and transgenic plants. (<b>D</b>–<b>F</b>) δ-3T (<b>D</b>), γ-3T (<b>E</b>), α-3T (<b>F</b>) contents of wild-type and transgenic plants. For each transgenic construct, means ± SEMs from three different transgenic-positive lines are shown here. Statistical difference was determined by one-way ANOVA with Dunnett’s multiple comparison test and WT was used as the control group. Means with no letter in common are significantly different at the 0.05 level.</p>
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<p>Volcano map of gene differential expression. CK indicates transgenic control, and T1 indicates representative <span class="html-italic">HaHPT-HaTMT</span> transformed plants for RNA-seq.</p>
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<p>GO enrichment classification bar chart.</p>
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<p>Gene Ontology (GO) enrichment bubble diagram. (<b>A</b>) Bioprocess GO enrichment bubble map. (<b>B</b>) GO enrichment bubble map of cell components. (<b>C</b>) GO enrichment bubble map of gene molecular function. The top 20 GO terms with the smallest Q value are used as GO enrichment bubbles. The ordinate represents the GO term, and the abscissa represents the enrichment factor (the number of differentially expressed genes in the GO term is divided by all the numbers in the GO term), and the size represents the number of genes. The redder the color, the smaller the Q value.</p>
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<p>KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment bubble diagram. The top 20 pathways with the smallest Q value are shown here. The ordinate is the pathway, and the abscissa is the enrichment factor (the number of differential genes in the pathway is divided by the number of all genes in the pathway), and the size indicated the number. The redder the color, the smaller the Q value.</p>
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<p>Relative expression of genes related to chlorophyll synthesis pathway. (<b>A</b>) <span class="html-italic">protochlorophyllide reductase A</span> (<span class="html-italic">PORA</span>) gene expression difference between wild-type and transgenic rice. (<b>B</b>) <span class="html-italic">protochlorophyllide reductase B</span> (<span class="html-italic">PORB</span>) gene expression difference between wild-type and transgenic rice. (<b>C</b>) <span class="html-italic">chlorophyll synthase gene</span> (<span class="html-italic">CHLG</span>) gene expression difference between wild-type and transgenic rice. (<b>D</b>) <span class="html-italic">chlorophyllide a oxidase</span> (<span class="html-italic">CAO</span>) gene expression difference between wild-type and transgenic rice. Analysis of difference significance is based on student’s <span class="html-italic">t</span>-test, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, ns: No significance.</p>
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15 pages, 1739 KiB  
Article
Assessing Elemental Diversity in Edible-Podded Peas: A Comparative Study of Pisum sativum L. var. macrocarpon and var. saccharatum through Principal Component Analysis, Correlation, and Cluster Analysis
by Saurabh Yadav, Rajinder Kumar Dhall, Hira Singh, Parteek Kumar, Dharminder Bhatia, Priyanka Kumari and Neha Rana
Horticulturae 2024, 10(8), 890; https://doi.org/10.3390/horticulturae10080890 - 22 Aug 2024
Viewed by 257
Abstract
This study assessed eleven elements in 24 edible-podded peas, including sugar snap pea and snow pea genotypes aiming to identify promising parents for nutraceutical breeding. Elemental concentrations of pods (dry weight basis) were estimated through inductively coupled plasma-optical emission spectroscopy (ICP-OES). The ranges [...] Read more.
This study assessed eleven elements in 24 edible-podded peas, including sugar snap pea and snow pea genotypes aiming to identify promising parents for nutraceutical breeding. Elemental concentrations of pods (dry weight basis) were estimated through inductively coupled plasma-optical emission spectroscopy (ICP-OES). The ranges for these elements varied significantly, highlighting the diverse elemental profiles within the edible-podded pea genotypes. All the elements exhibited a high genotypic and phenotypic coefficient of variation along with considerable heritability and hereditary progress. Positive and significant correlations were recorded among all elements, suggesting the potential for simultaneous selection for these traits. Principal component analysis (PCA) revealed that the first two components accounted for 80.56% of the variation. Further, cluster analysis, based on Euclidean distance, grouped the 24 cultivars into two major clusters. Cluster I exhibited higher means for all estimated concentrations compared to Cluster II. Notably, Dwarf Grey Sugar and Arka Sampoorna from the snap pea group and PED-21-5 and Sugar Snappy from the sugar snap pea in Cluster II demonstrated superior elemental concentration in whole pods. The selected edible-podded pea genotypes serve as valuable genetic resources for new cultivar development, particularly in biofortification efforts targeting whole pod nutrient composition. Full article
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<p>Correlation coefficient matrix, scatter plot, and phenotypic frequency distribution among element traits. Diagonal representations illustrate the distribution of each variable. Bivariate scatter plots, accompanied by trend lines, are presented below the diagonal. The correlation coefficient, along with its level of significance, is indicated at the top of the diagonal using stars: * for <span class="html-italic">p</span> ≤ 0.05, ** for <span class="html-italic">p</span> ≤ 0.01, and *** for <span class="html-italic">p</span> &gt; 0.001, denoting the respective significance levels.</p>
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<p>Biplot for the 24 edible-podded genotypes and 11 elements along the first two principal components. Note: 1, Airtel; 2, Oregon Sugar pod; 3, Arka Sampoorna; 4, PED-21-4; 5, Tardio; 6, Sugar Bon; 7, PED-18-5; 8, PED-21-2; 9, PED-18-7; 10, Mithiphali; 11, Tarvedo Sugar; 12, PED-21-7; 13, Dwarf grey sugar; 14, Sugar daddy; 15, PED-21-1; 16, Sugar snappy; 17, PED-21-5; 18, PED-21-3; 19, PED-18-6; 20, Namdhari-NA; 21, PED-18-8; 22, HPM-1; 23, HPM-2; 24, Honey snap.</p>
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<p>Hierarchical cluster analysis of 24 edible-podded pea genotypes using the Euclidean distance method implemented using the hclust package in R Studio. Here “d” is for distance between the data points; “(*, “ward.D”)” means that the dendogram was constructed using Ward’s method for clustering, with Euclidean distance metric was used to compute the distance between the data points.</p>
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21 pages, 3716 KiB  
Article
Validation of SNP Markers for Diversity Analysis, Quality Control, and Trait Selection in a Biofortified Cassava Population
by Edwige Gaby Nkouaya Mbanjo, Adebukola Ogungbesan, Afolabi Agbona, Patrick Akpotuzor, Seyi Toyinbo, Peter Iluebbey, Ismail Yusuf Rabbi, Prasad Peteti, Sharon A. Wages, Joanna Norton, Xiaofei Zhang, Adriana Bohórquez-Chaux, Hapson Mushoriwa, Chiedozie Egesi, Peter Kulakow and Elizabeth Parkes
Plants 2024, 13(16), 2328; https://doi.org/10.3390/plants13162328 - 21 Aug 2024
Viewed by 501
Abstract
A validated marker system is crucial to running an effective genomics-assisted breeding program. We used 36 Kompetitive Allele-Specific PCR (KASP) markers to genotype 376 clones from the biofortified cassava pipeline, and fingerprinted 93 of these clones with DArTseq markers to characterize breeding materials [...] Read more.
A validated marker system is crucial to running an effective genomics-assisted breeding program. We used 36 Kompetitive Allele-Specific PCR (KASP) markers to genotype 376 clones from the biofortified cassava pipeline, and fingerprinted 93 of these clones with DArTseq markers to characterize breeding materials and evaluate their relationships. The discriminating ability of the 36-quality control (QC) KASP and 6602 DArTseq markers was assessed using 92 clones genotyped in both assays. In addition, trait-specific markers were used to determine the presence or absence of target genomic regions. Hierarchical clustering identified two major groups, and the clusters were consistent with the breeding program origins. There was moderate genetic differentiation and a low degree of variation between the identified groups. The general structure of the population was similar using both assays. Nevertheless, KASP markers had poor resolution when it came to differentiating the genotypes by seed sources and overestimated the prevalence of duplicates. The trait-linked markers did not achieve optimal performance as all markers displayed variable levels of false positive and/or false negative. These findings represent the initial step in the application of genomics-assisted breeding for the biofortified cassava pipeline, and will guide the use of genomic selection in the future. Full article
(This article belongs to the Special Issue Genetic Improvement of Cassava)
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<p>Trait correlation and the distribution of traits across the unique genotypes. (<b>a</b>) Correlation between three key cassava traits: total carotenoid content (TCC), dry matter content (DMC), and cassava mosaic disease severity (CMDs). The color scale on the left shows correlation values from +1 to −1. Grey indicates a strong positive correlation, while pink, purple, and orange represent weak, moderate, and strong negative correlations, respectively. Insignificant correlations between CMDs and DMC are shown as blank. Distribution of (<b>b</b>) DMC, (<b>c</b>) TCC, and (<b>d</b>) CMD severity across unique genotypes. Symbols represent clone sources, while colors indicate different levels for each trait. For DMC: low (&lt;30%), high (30–33%), and very high (&gt;33%); for TCC: low (&lt;15 μg/g), high (15–19 μg/g), and very high (&gt;19 μg/g); for CMD: low (&lt;2) and high (&gt;2).</p>
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<p>Trait correlation and the distribution of traits across the unique genotypes. (<b>a</b>) Correlation between three key cassava traits: total carotenoid content (TCC), dry matter content (DMC), and cassava mosaic disease severity (CMDs). The color scale on the left shows correlation values from +1 to −1. Grey indicates a strong positive correlation, while pink, purple, and orange represent weak, moderate, and strong negative correlations, respectively. Insignificant correlations between CMDs and DMC are shown as blank. Distribution of (<b>b</b>) DMC, (<b>c</b>) TCC, and (<b>d</b>) CMD severity across unique genotypes. Symbols represent clone sources, while colors indicate different levels for each trait. For DMC: low (&lt;30%), high (30–33%), and very high (&gt;33%); for TCC: low (&lt;15 μg/g), high (15–19 μg/g), and very high (&gt;19 μg/g); for CMD: low (&lt;2) and high (&gt;2).</p>
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<p>Cluster analysis showing the relationship among the 92 cassava genotypes. The 92 genotypes are separated into two clusters, with 34 and 58 accessions in clusters 1 (red) and cluster 2 (green), respectively.</p>
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<p>Principal component analysis obtained using the 6602 DArTseq and 36 QC KASP markers assessed in the 92 genotypes shared by both assays. The additive relationship matrix was calculated using the R package rrBLUP [<a href="#B25-plants-13-02328" class="html-bibr">25</a>] (<b>a</b>) PCA classification using the 36 QC KASP markers; (<b>b</b>) PCA classification using the 6602 DArTseq markers. Samples are colored based on the breeding program from which the samples originated.</p>
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<p>Population structure within the 92 cassava genotypes assessed with 6602 DArTseq markers. (<b>a</b>) Cross-validation plot. Cross-validation error is shown on the <span class="html-italic">Y</span>–axis (vertical) and the number of hypothetical populations on the <span class="html-italic">X</span>–axis (horizontal). Cross-validation revealed K = 4 as the optimal number of clusters. (<b>b</b>) Individual ancestry inferred with admixture. Each genotype is represented by a vertical line partitioned by color. The proportion of the color making up each vertical line represents the proportion contributed by the ancestral population. The best-supported clustering (K = 4) divided the 92 cassava genotypes into four main groups.</p>
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<p>Boxplot showing allelic substitution effect for cassava mosaic disease severity. Three markers, namely S12-7926132 (<b>a</b>), S12-7926163 (<b>b</b>), and S14-4626854 (<b>c</b>), were evaluated. The genotypes/alleles of each marker are presented on the <span class="html-italic">X</span>–axis, while the phenotype trait and its value are mentioned on the <span class="html-italic">Y</span>–axis. The Kruskal–Wallis test was used to assess the statistical differences between genotype classes. The stars in the figure indicate levels of statistical significance. *, ***, **** significant at <span class="html-italic">p</span> ≤ 0.05, <span class="html-italic">p</span> ≤ 0.001, <span class="html-italic">p</span> ≤ 0.0001, respectively; ns = non-significant (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Boxplot showing allelic substitution effect for root dry matter content. Three markers, namely S1-24197219 (<b>a</b>), S6-20589894 (<b>b</b>), and S12-5524524 (<b>c</b>), were evaluated. The genotypes/alleles of each marker are presented on the <span class="html-italic">X</span>–axis, while the phenotype trait and its value are mentioned on the <span class="html-italic">Y</span>–axis. The Kruskal–Wallis test was used to assess the statistical differences between genotype classes. The stars in the figure indicate levels of statistical significance. *, **** significant at <span class="html-italic">p</span> ≤ 0.05 and <span class="html-italic">p</span> ≤ 0.0001, respectively; ns = non-significant (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Boxplot showing allelic substitution effect for total content of carotenoids, estimated using iCheck. Four markers, namely S1-24155522 (<b>a</b>), S1-30543962 (<b>b</b>), S5-3387558 (<b>c</b>), and S8-25598183 (<b>d</b>), were evaluated. The genotypes/alleles of each marker are presented on the <span class="html-italic">X</span>–axis, while the phenotype trait and its value are mentioned on the <span class="html-italic">Y</span>–axis. The Kruskal–Wallis test was used to assess the statistical differences between genotype classes. The stars in the figure indicate levels of statistical significance. *, ***, **** significant at <span class="html-italic">p</span> ≤ 0.05, <span class="html-italic">p</span> ≤ 0.001, <span class="html-italic">p</span> ≤ 0.0001, respectively; ns = non-significant (<span class="html-italic">p</span> &gt; 0.05).</p>
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23 pages, 4851 KiB  
Article
Foliar Sprays of Multi-Nutrient Fertilizer Containing Selenium Produce Functional Tomato Fruits with Higher Shelf Life
by Everton Geraldo de Morais, Maila Adriely Silva, Anyela Pierina Vega Quispe, Gilson Gustavo Lucinda Machado, Debora Teixeira Prado, Pedro Antônio Namorato Benevenute, Jucelino de Sousa Lima, Gustavo Ferreira de Sousa, Eduardo Valério de Barros Vilas Boas and Luiz Roberto Guimarães Guilherme
Plants 2024, 13(16), 2288; https://doi.org/10.3390/plants13162288 - 17 Aug 2024
Viewed by 550
Abstract
Selenium (Se) is a nutrient whose daily intake is often below the recommended levels in people. Biofortification with Se is a method to increase this intake by raising the Se concentration in tomato fruits, an effect dependent on sources and modes of application. [...] Read more.
Selenium (Se) is a nutrient whose daily intake is often below the recommended levels in people. Biofortification with Se is a method to increase this intake by raising the Se concentration in tomato fruits, an effect dependent on sources and modes of application. Additionally, Se application can promote the enhancement of other compounds in tomato fruits, altering their metabolism, which may increase the fruit’s shelf life. This study aimed to determine how different strategies of applying a multi-nutrient fertilizer containing Se (SeMNF) can increase the Se content and other bioactive compounds and enhance the shelf life of tomato (Solanum lycopersicum L.) fruits. Different foliar fertilization strategies involving the use of SeMNF were evaluated in field trials conducted on commercial tomato crops. Indeterminate-growth tomatoes were used, and different Se doses and application strategies were tested. Harvesting was conducted in three phases according to fruit ripening. Each harvested fruit was assessed for the Se content, macro and micronutrients, total phenolic compounds, vitamin C, antioxidant activity, carotenoids, pH, total titratable acidity, and total soluble solids in tomato fruits. Doses of 15 g ha−1 of Se, split into three applications, increased the Se content in the fruits at 1 and 2 harvests. The application of SeMNF at Se doses above 10 g of Se ha−1 increased firmness, days of ripening, and the nutritional quality of the tomatoes (higher contents of carotenoids (+39%), lycopene (+33%), antioxidant activity (+16%), total phenolic compounds (+38%), and vitamin C (+14%) in a dose-dependent effect of the application strategy used. These results contributed to an increase in the shelf life of tomatoes, consequently reducing food waste. Full article
(This article belongs to the Collection Plant Nutrition Biofortification)
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<p>Days to CO<sub>2</sub> peak, time of ripening, and fruit firmness according to different strategies of multi-nutrient fertilizer (MNF) application containing selenium in each harvest evaluated. T1: Control (without application of MNF); T2: Application at the beginning of flowering (2 kg ha<sup>−1</sup> of MNF providing 5 g of Se ha<sup>−1</sup>); T3: Application at the beginning of flowering +3rd bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T4: Application at the beginning of flowering +6th bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T5: Application at the beginning of flowering +3rd bunch +6th bunch (6 kg ha<sup>−1</sup> of MNF providing 15 g of Se ha<sup>−1</sup>). NS: statistically non-significant (<span class="html-italic">p</span> &gt; 0.05). Bars with standard error of each treatment followed by the same letter in each column are not differentiated by the Duncan test (<span class="html-italic">p</span> &gt; 0.05) in each harvest evaluated.</p>
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<p>pH, total titratable acidity, and total soluble solids in fruit pulp according to different strategies of multi-nutrient fertilizer (MNF) application containing selenium in each harvest evaluated. T1: Control (without application of MNF); T2: Application at the beginning of flowering (2 kg ha<sup>−1</sup> of MNF providing 5 g of Se ha<sup>−1</sup>); T3: Application at the beginning of flowering +3rd bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T4: Application at the beginning of flowering +6th bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T5: Application at the beginning of flowering +3rd bunch +6th bunch (6 kg ha<sup>−1</sup> of MNF providing 15 g of Se ha<sup>−1</sup>). NS: statistically non-significant (<span class="html-italic">p</span> &gt; 0.05). Bars with standard error of each treatment followed by the same letter in each column are not differentiated by the Duncan test (<span class="html-italic">p</span> &gt; 0.05) in each harvest evaluated.</p>
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<p>Total phenolic content and antioxidant activity by the phosphomolybdenum complex (mg of ascorbic acid -AA) and ABTS reduction methods according to different strategies of multi-nutrient fertilizer (MNF) application containing selenium in each harvest evaluated. T1: Control (without application of MNF); T2: Application at the beginning of flowering (2 kg ha<sup>−1</sup> of MNF providing 5 g of Se ha<sup>−1</sup>); T3: Application at the beginning of flowering +3rd bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T4: Application at the beginning of flowering +6th bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T5: Application at the beginning of flowering +3rd bunch +6th bunch (6 kg ha<sup>−1</sup> of MNF providing 15 g of Se ha<sup>−1</sup>). NS: statistically non-significant (<span class="html-italic">p</span> &gt; 0.05). Bars with standard error of each treatment followed by the same letter in each column are not differentiated by the Duncan test (<span class="html-italic">p</span> &gt; 0.05) in each harvest evaluated.</p>
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<p>Vitamin C (mg of ascorbic acid—AA), lycopene, and total carotenoids’ evaluation according to different strategies of multi-nutrient fertilizer (MNF) application containing selenium in each harvest. T1: Control (without application of MNF); T2: Application at the beginning of flowering (2 kg ha<sup>−1</sup> of MNF providing 5 g of Se ha<sup>−1</sup>); T3: Application at the beginning of flowering +3rd bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T4: Application at the beginning of flowering +6th bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T5: Application at the beginning of flowering +3rd bunch +6th bunch (6 kg ha<sup>−1</sup> of MNF providing 15 g of Se ha<sup>−1</sup>). NS: statistically non-significant (<span class="html-italic">p</span> &gt; 0.05). Bars with standard error of each treatment followed by the same letter in each column are not differentiated by the Duncan test (<span class="html-italic">p</span> &gt; 0.05) in each harvest evaluated.</p>
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<p>Determination of selenium (Se) content in dried tomato fruits according to different strategies of multi-nutrient fertilizer (MNF) application containing Se in each harvest evaluated. T1: Control (without application of MNF); T2: Application at the beginning of flowering (2 kg ha<sup>−1</sup> of MNF providing 5 g of Se ha<sup>−1</sup>); T3: Application at the beginning of flowering +3rd bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T4: Application at the beginning of flowering +6th bunch (4 kg ha<sup>−1</sup> of MNF providing 10 g of Se ha<sup>−1</sup>); T5: Application at the beginning of flowering +3rd bunch +6th bunch (6 kg ha<sup>−1</sup> of MNF providing 15 g of Se ha<sup>−1</sup>). NS: statistically non-significant (<span class="html-italic">p</span> &gt; 0.05). Bars with standard error of each treatment followed by the same letter in each column are not differentiated by the Duncan test (<span class="html-italic">p</span> &gt; 0.05) in each harvest evaluated.</p>
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<p>Principal component analysis of each harvest evaluated. pH: pH in fruit pulp; TTA: total titratable acidity in fruit pulp; TSS: total soluble solids in fruit pulp; CO<sub>2</sub> peak: days to CO<sub>2</sub> peak, Ripening: days for fruit ripening; Firmness: fruit firmness; Vitamin C: Vitamin C—mg of ascorbic acid in fruit pulp; Lycopene: Lycopene content in fruit pulp; Carotenoids: total carotenoids content in fruit pulp; Phenolic: total phenolic content in fruit pulp; Antioxidant (AA): antioxidant activity in fruit pulp by the phosphomolybdenum complex methods (mg of ascorbic acid); Antioxidant (ABTS): antioxidant activity in fruit pulp by ABTS reduction method; Zn in fruit, Cu in fruit, B in fruit, N in fruit, and Se in fruit: concentration of zinc, copper, boron, nitrogen, and selenium (Se) in dried tomato fruits, respectively; Se in leaf: concentration of Se in dried tomato leaves; PC: principal component.</p>
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<p>Location in UTM zones, design, and climatic data during the experiment.</p>
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<p>Weight loss of fruits according to different strategies of multi-nutrient fertilizer application containing selenium in each harvest evaluated. T1: Control (without application of multi-nutrient fertilizer); T2: Application at the beginning of flowering (2 kg ha<sup>−1</sup> of multi-nutrient fertilizer providing 5 g of Se ha<sup>−1</sup>); T3: Application at the beginning of flowering +3rd bunch (4 kg ha<sup>−1</sup> of multi-nutrient fertilizer providing 10 g of Se ha<sup>−1</sup>); T4: Application at the beginning of flowering +6th bunch (4 kg ha<sup>−1</sup> of multi-nutrient fertilizer providing 10 g of Se ha<sup>−1</sup>); T5: Application at the beginning of flowering +3rd bunch +6th bunch (6 kg ha<sup>−1</sup> of multi-nutrient fertilizer providing 15 g of Se ha<sup>−1</sup>). NS: statistically non-significant (<span class="html-italic">p</span> &gt; 0.05).</p>
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20 pages, 4186 KiB  
Article
Effects of Biological Nano-Selenium on Yield, Grain Quality, Aroma, and Selenium Content of Aromatic Rice
by Qichang Gu, Haowen Luo, Li Lin, Qianqian Zhang, Wentao Yi, Zhifan Liu, Xianghai Yu, Changjian Zuo, Jianying Qi and Xiangru Tang
Agronomy 2024, 14(8), 1778; https://doi.org/10.3390/agronomy14081778 - 13 Aug 2024
Viewed by 513
Abstract
Selenium (Se) is one of the human essential elements and the input of Se for its biofortification is common in rice production to meet the demand for Se in the population. Biological nano-selenium (nano-Se) is a new type of nanoscale microbial synthetic material. [...] Read more.
Selenium (Se) is one of the human essential elements and the input of Se for its biofortification is common in rice production to meet the demand for Se in the population. Biological nano-selenium (nano-Se) is a new type of nanoscale microbial synthetic material. However, the effects of biological nano-Se on aromatic rice performance metrics, such as yield formation, grain quality parameters, and the biosynthesis of 2-acetyl-1-pyrroline (2-AP, the key component of aromatic rice aroma), have rarely been reported. Therefore, this study conducted a field experiment with two cropping seasons and two aromatic rice genotypes to explore the effects of the foliar application of biological nano-Se on aromatic rice performance metrics. The results showed that the foliar application of biological nano-Se at 3–4 days before panicle differentiation or the heading stage increased the grain yield of aromatic rice. Dry matter accumulation and the leaf area index increased under Nano-Se application. Furthermore, the foliar application of Nano-Se at 3–4 days before panicle differentiation significantly enhanced the activity of peroxidase, superoxide dismutase, catalase and reduced malondialdehyde content. The foliar application of Nano-Se at the grain-filling stage also increased 2-AP content. In addition, nano-Se application substantially increased the grain Se content in aromatic rice. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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Figure 1

Figure 1
<p>Effects of biological nano-Se application on the net photosynthetic rate of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test. The same as below.</p>
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<p>Effects of biological nano-Se application on the LAI of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). The LAI (leaf area index) is the ratio of the total area of plant leaves per unit area to the planted area. Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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<p>Effect of biological nano-Se application on the aboveground dry matter of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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<p>Effects of biological nano-Se application on the SOD activity of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). FW, fresh weight. Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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<p>Effects of biological nano-Se application on the POD activity of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). FW, fresh weight. Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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<p>Effects of biological nano-Se application on the CAT activity of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). FW, fresh weight. Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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<p>Effects of biological nano-Se application on the MDA content of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). FW, fresh weight. Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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<p>Effects of biological nano-Se application on grain 2-AP content of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). 2-AP, 2-acetyl-1-pyrroline. Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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<p>Effects of biological nano-Se application on grain pyrroline content of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). FW, fresh weight. Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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<p>Effects of biological nano-Se application on grain Se content of aromatic rice (<b>A</b>) for 19Xiang in the early season; (<b>B</b>) for 19Xiang in the late season; (<b>C</b>) for Qingxiangyou19Xiang in the early season; (<b>D</b>) for Qingxiangyou19Xiang in the late season. No foliar application (CK), foliar application one time at 3–4 days before panicle differentiation (T1), foliar application one time at the heading stage (T2), foliar application one time at 10 days after the heading stage (T3), foliar application two times at 3–4 days before panicle differentiation and the heading stage, respectively (T4), foliar application two times at 3–4 days before panicle differentiation and 10 days after the heading stage (T5). Bars sharing a common letter do not differ significantly at (<span class="html-italic">p</span> ≤ 0.05) in each cropping season according to the LSD test.</p>
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24 pages, 8303 KiB  
Article
Asparagopsis taxiformis as a Novel Antioxidant Ingredient for Climate-Smart Aquaculture: Antioxidant, Metabolic and Digestive Modulation in Juvenile White Seabream (Diplodus sargus) Exposed to a Marine Heatwave
by Alícia Pereira, Isa Marmelo, Marta Dias, Ana Catarina Silva, Ana Catarina Grade, Marisa Barata, Pedro Pousão-Ferreira, Jorge Dias, Patrícia Anacleto, António Marques, Mário S. Diniz and Ana Luísa Maulvault
Antioxidants 2024, 13(8), 949; https://doi.org/10.3390/antiox13080949 - 5 Aug 2024
Viewed by 809
Abstract
The increasing frequency and duration of marine heatwaves (MHWs) due to climate change pose severe threats to aquaculture, causing drastic physiological and growth impairments in farmed fish, undermining their resilience against additional environmental pressures. To ensure sustainable production that meets the global seafood [...] Read more.
The increasing frequency and duration of marine heatwaves (MHWs) due to climate change pose severe threats to aquaculture, causing drastic physiological and growth impairments in farmed fish, undermining their resilience against additional environmental pressures. To ensure sustainable production that meets the global seafood demand and animal welfare standards, cost-effective and eco-friendly strategies are urgently needed. This study explored the efficacy of the red macroalga Asparagopsis taxiformis on juvenile white seabream Diplodus sargus reared under optimal conditions and upon exposure to a MHW. Fish were fed with four experimental diets (0%, 1.5%, 3% or 6% of dried powdered A. taxiformis) for a prophylactic period of 30 days (T30) and subsequently exposed to a Mediterranean category II MHW for 15 days (T53). Biometric data and samples were collected at T30, T53 and T61 (8 days post-MHW recovery), to assess performance indicators, biomarker responses and histopathological alterations. Results showed that A. taxiformis supplementation improved catalase and glutathione S-transferase activities and reduced lipid peroxidation promoted by the MHW, particularly in fish biofortified with 1.5% inclusion level. No histopathological alterations were observed after 30 days. Additionally, fish biofortified with 1.5% A. taxiformis exhibited increased citrate synthase activity and fish supplemented with 1.5% and 3% showed improved digestive enzyme activities (e.g., pepsin and trypsin activities). Overall, the present findings pointed to 1.5% inclusion as the optimal dosage for aquafeeds biofortification with A. taxiformis, and confirmed that this seaweed species is a promising cost-effective ingredient with functional properties and great potential for usage in a climate-smart context. Full article
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Graphical abstract

Graphical abstract
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<p>Experimental design and simulation of the category II Mediterranean Marine Heatwave including sampling days (T30, T53 and T61) for white seabream, <span class="html-italic">D. sargus</span>, fed with the different diets. Days 1–30, biofortification at 24 °C; day 30, first sampling (T30); days 30–38, temperature ramp to 28 °C; days 38–53, category II marine heatwave (28 °C); day 53, sampling day after exposure to peak temperature of the MHW (T53); days 53–61, temperature ramp back to 24 °C; day 61, sampling day post-MHW (T61). Abbreviations: CTR—control feed; CTR-HW—control feed and exposure to the MHW; 1.5-AT—1.5% inclusion of <span class="html-italic">A. taxiformis</span>; 3-AT—3% inclusion of <span class="html-italic">A. taxiformis</span>; 6-AT—6% inclusion of <span class="html-italic">A. taxiformis</span>.</p>
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<p>Oxidative stress biomarkers in the muscle tissue of white seabream, <span class="html-italic">D. sargus</span>, juveniles fed with the different diets at days 30 (T30, i.e., after 30 days of biofortification), 53 (T53, i.e., after 15 days of exposure to the MHW peak temperature), and 61 (T61, i.e., after 8 days of recovery from the MHW) of the trial (mean ± SD, <span class="html-italic">n</span> = 6). (<b>A</b>)—catalase (CAT) activity (nmol min<sup>−1</sup> mg<sup>−1</sup> protein); (<b>B</b>)—glutathione S-transferase (GST) activity (nmol min<sup>−1</sup> mg<sup>−1</sup> protein); (<b>C</b>)—superoxide dismutase (SOD) activity (% inhibition); and (<b>D</b>)—lipid peroxidation (LPO, expressed as MDA concentration, nmol mg<sup>−1</sup> protein). Different letters denote significant differences between treatments on the same sampling day, and different symbols (* and #) indicate significant differences between sampling days T53 and T61 for the same treatment (<span class="html-italic">p</span> &lt; 0.05). The absence of letters or symbols indicates no statistical difference. Abbreviations: CTR—control feed; CTR-HW—control feed exposed to the MHW; 1.5-AT—feed with 1.5% inclusion of <span class="html-italic">A. taxiformis</span>; 3-AT—feed with 3% inclusion of <span class="html-italic">A. taxiformis</span>; 6-AT—feed with 6% inclusion of <span class="html-italic">A. taxiformis</span>; CAT—catalase; GST—glutathione S-transferase; SOD—superoxide dismutase; MDA—malondialdehyde.</p>
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<p>Oxidative stress biomarkers in the gut tissue of white seabream, <span class="html-italic">D. sargus</span>, juveniles fed with the different diets at days 30 (T30, i.e., after 30 days of biofortification), 53 (T53, i.e., after 15 days of exposure to the MHW peak temperature), and 61 (T61, i.e., after 8 days of recovery from the MHW) of the trial (mean ± SD, <span class="html-italic">n</span> = 6). (<b>A</b>)—catalase (CAT) activity (nmol min<sup>−1</sup> mg<sup>−1</sup> protein); (<b>B</b>)—glutathione S-transferase (GST) activity (nmol min<sup>−1</sup> mg<sup>−1</sup> protein); (<b>C</b>)—superoxide dismutase (SOD) activity (% inhibition); and (<b>D</b>)—lipid peroxidation (LPO, expressed as MDA concentration, nmol mg<sup>−1</sup> protein). Different letters denote significant differences between treatments on the same sampling day, and different symbols (* and #) indicate significant differences between sampling days T53 and T61 for the same treatment (<span class="html-italic">p</span> &lt; 0.05). The absence of letters or symbols indicates no statistical difference. Abbreviations: CTR—control feed; CTR-HW—control feed exposed to the MHW; 1.5-AT—feed with 1.5% inclusion of <span class="html-italic">A. taxiformis</span>; 3-AT—feed with 3% inclusion of <span class="html-italic">A. taxiformis</span>; 6-AT—feed with 6% inclusion of <span class="html-italic">A. taxiformis</span>; CAT—catalase; GST—glutathione S-transferase; SOD—superoxide dismutase; MDA—malondialdehyde.</p>
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<p>Oxidative stress biomarkers in the liver of white seabream, <span class="html-italic">D. sargus</span>, juveniles fed with the different diets at days 30 (T30, i.e., after 30 days of biofortification), 53 (T53, i.e., after 15 days of exposure to the MHW peak temperature), and 61 (T61, i.e., after 8 days of recovery from the MHW) of the trial (mean ± SD, <span class="html-italic">n</span> = 6). (<b>A</b>)—catalase (CAT) activity (nmol min<sup>−1</sup> mg<sup>−1</sup> protein); (<b>B</b>)—glutathione S-transferase (GST) activity (nmol min<sup>−1</sup> mg<sup>−1</sup> protein); (<b>C</b>)—superoxide dismutase (SOD) activity (% inhibition); and (<b>D</b>)—lipid peroxidation (LPO, expressed as MDA concentration, nmol mg<sup>−1</sup> protein). Different letters denote significant differences between treatments on the same sampling day, and different symbols (* and #) indicate significant differences between sampling days T53 and T61 for the same treatment (<span class="html-italic">p</span> &lt; 0.05). The absence of letters or symbols indicates no statistical difference. Abbreviations: CTR—control feed; CTR-HW—control feed exposed to the MHW; 1.5-AT—feed with 1.5% inclusion of <span class="html-italic">A. taxiformis</span>; 3-AT—feed with 3% inclusion of <span class="html-italic">A. taxiformis</span>; 6-AT—feed with 6% inclusion of <span class="html-italic">A. taxiformis</span>; CAT—catalase; GST—glutathione S-transferase; SOD—superoxide dismutase; MDA—malondialdehyde.</p>
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<p>Metabolic responses in the muscle of <span class="html-italic">D. sargus</span> juveniles fed with the different diets at days 30 (T30, i.e., after 30 days of biofortification), 53 (T53, i.e., after 15 days of exposure to the MHW peak temperature), and 61 (T61, i.e., after 8 days of recovery from the MHW) of the trial (mean ± SD, <span class="html-italic">n</span> = 6). (<b>A</b>)—citrate synthase (CS) activity (U mg<sup>−1</sup> protein) and (<b>B</b>)—lactate dehydrogenase (LDH) activity (U mg<sup>−1</sup> protein). Different letters denote significant differences between treatments on the same sampling day, and different symbols (* and #) indicate significant differences between sampling days T53 and T61 for the same treatment (<span class="html-italic">p</span> &lt; 0.05). The absence of letters or symbols indicates no statistical difference. Abbreviations: CTR—control feed; CTR-HW—control feed exposed to the MHW; 1.5-AT—feed with 1.5% inclusion of <span class="html-italic">A. taxiformis</span>; 3-AT—feed with 3% inclusion of <span class="html-italic">A. taxiformis</span>; 6-AT—feed with 6% inclusion of <span class="html-italic">A. taxiformis</span>; CS—citrate synthase; LDH—lactate dehydrogenase.</p>
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<p>Digestive enzyme activities in the digestive tract of <span class="html-italic">D. sargus</span> fed the experimental diets at days 30 (T30, i.e., after 30 days of biofortification), 53 (T53, i.e., after 15 days of exposure to the MHW peak temperature), and 61 (T61, i.e., after 8 days of recovery from the MHW) of the trial (mean ± SD, <span class="html-italic">n</span> = 6). (<b>A</b>)—amylase activity (mU mg<sup>−1</sup> protein); (<b>B</b>)—pepsin activity (µU mg<sup>−1</sup> protein) and (<b>C</b>)—trypsin activity (mU mg<sup>−1</sup> protein). Different letters denote significant differences between treatments on the same sampling day, and different symbols (* and #) indicate significant differences between sampling days T53 and T61 for the same treatment (<span class="html-italic">p</span> &lt; 0.05). The absence of letters or symbols indicates no statistical difference. Abbreviations: CTR—control feed; CTR-HW—control feed exposed to the MHW; 1.5-AT—feed with 1.5% inclusion of <span class="html-italic">A. taxiformis</span>; 3-AT—feed with 3% inclusion of <span class="html-italic">A. taxiformis</span>; 6-AT—feed with 6% inclusion of <span class="html-italic">A. taxiformis</span>.</p>
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<p>Histological changes in the liver of <span class="html-italic">D. sargus</span> exposed to a marine heatwave. (<b>A</b>) Control fish liver tissues at day 30 (T30, i.e., after 30 days of biofortification): normal hepatopancreas (HP) and hepatocytes (hp); (<b>B</b>) Liver exposed to 1.5% of <span class="html-italic">A. taxiformis</span> after biofortification (T30): normal hepatopancreas (HP) and hepatocytes (hp) with some increase of hepatopancreas volume and blood congestion (B); (<b>C</b>) Liver exposed to 1.5% of <span class="html-italic">A. taxiformis</span> after exposure to peak temperature of the MHW (T53): normal hepatopancreas (HP), hepatocytes (hp) and some fatty liver changes (steatosis) (*); (<b>D</b>) Liver exposed to 6% of <span class="html-italic">A. taxiformis</span> post-MHW (T61): liver and hepatopancreas (HP) showing some dilatation and blood congestion in the sinusoids (black arrows). Bar = 200 μm. H&amp;E.</p>
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<p>Histological changes in the intestines of <span class="html-italic">D. sargus</span> exposed to a marine heatwave. (<b>A</b>) Control fish intestine at day 30 (T30, i.e., after 30 days of biofortification): normal serosa (S), muscularis externa (ME), submucosa (SM), lamina propria (LP), villus (V), and goblet cells (Gc); (<b>B</b>) Liver exposed to 1.5% of <span class="html-italic">A. taxiformis</span> at day 30 (T30, i.e., after 30 days of biofortification): serosa (S), muscularis externa (ME), submucosa (SM), lamina propria (LP), villus (V), goblet cells (Gc), fusion of villi (square); cellular infiltration (*); (<b>C</b>) Liver exposed to 6% of <span class="html-italic">A. taxiformis</span> at day 30 (T30, i.e., after 30 days of biofortification): serosa (S), muscularis externa (ME), submucosa (SM), lamina propria (LP), villus (V), goblet cells (Gc), fusion of villi (square); cellular infiltration (*) and pseudocrypt (Pc); (<b>D</b>) Intestine exposed to 6% of <span class="html-italic">A. taxiformis</span>, post-MHW (T61): normal muscularis externa (ME), submucosa (SM), lamina propria (LP), villus (V), and goblet cells (Gc). Bar = 200 μm. H&amp;E.</p>
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17 pages, 7000 KiB  
Article
Physiological and Biochemical Analysis of Selenium-Enriched Rice
by Tianyi Lu, Yanmei Ai, Meng Na, Shangqi Xu, Xiaoping Li, Xianqing Zheng and Jihai Zhou
Agronomy 2024, 14(8), 1715; https://doi.org/10.3390/agronomy14081715 - 4 Aug 2024
Viewed by 486
Abstract
Selenium is an essential trace element in the human body. However, its intake is generally low. Therefore, the production and utilisation of selenium-enriched foods is currently a research hotspot. In this study, the effects of low (0.2 mg·kg−1), medium (1.0 mg·kg [...] Read more.
Selenium is an essential trace element in the human body. However, its intake is generally low. Therefore, the production and utilisation of selenium-enriched foods is currently a research hotspot. In this study, the effects of low (0.2 mg·kg−1), medium (1.0 mg·kg−1), and high (5.0 mg·kg−1) concentrations of selenium on the physiological and biochemical characteristics of rice were investigated to develop selenium-enriched rice. High concentrations of selenium have been found to inhibit the growth, physiology, and biochemistry of rice, while low concentrations of selenium promote its growth. The height of mature rice plants exposed to high concentrations of selenium was reduced by 7.20% compared with the height of control rice. Selenium decreased the proline content of rice during the growth period except in mature rice treated with medium and high concentrations of selenium. Excluding high concentrations, selenium treatment increased the soluble sugar content of rice from the tillering to the mature stages. The peroxidase activity of rice at the heading stage treated with medium levels of selenium was significantly higher than that of the control rice, while the superoxide dismutase activity of rice exposed to selenium was significantly enhanced at the mature stage. The malondialdehyde levels of mature rice treated with medium and high levels of selenium were significantly lower than those of the control rice. The selenium content of each plant part was significantly correlated with the soil selenium level. An increase in the soil selenium level facilitated the production of selenium-enriched rice. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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<p>Effects of selenium on the height (<b>A</b>) and biomass (<b>B</b>) of rice. CK (control; no selenium added), LSe (0.2 mg·kg<sup>−1</sup> selenium added), MSe (1.0 mg·kg<sup>−1</sup> selenium added), HSe (5.0 mg·kg<sup>−1</sup> selenium added). Different lowercase letters indicate significant differences between different treatments during the same period (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Selenium content in rice roots (<b>A</b>), stems (<b>B</b>), leaves (<b>C</b>), husks (<b>D</b>), and brown rice (<b>E</b>). CK (control; no selenium added), LSe (0.2 mg·kg<sup>−1</sup> selenium added), MSe (1.0 mg·kg<sup>−1</sup> selenium added), HSe (5.0 mg·kg<sup>−1</sup> selenium added). Different lowercase letters indicate significant differences between the different treatments during the mature stage (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Proportion of selenium in different parts of rice. CK (control; no selenium added), LSe (0.2 mg·kg<sup>−1</sup> selenium added), MSe (1.0 mg·kg<sup>−1</sup> selenium added), HSe (5.0 mg·kg<sup>−1</sup> selenium added). BR<sub>Se</sub> represents the selenium content of brown rice; RH<sub>Se</sub> denotes the selenium content of rice husks; Leaf<sub>Se</sub> represents the selenium content of leaf, Stem<sub>Se</sub> denotes the selenium content of stem, Root<sub>Se</sub> denotes the selenium content of root.</p>
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<p>Bioconcentration factors (BCF) and translocation factors (TF) of selenium in rice under different selenium treatments: CK (control; no selenium added), LSe (0.2 mg·kg<sup>−1</sup>), MSe (1.0 mg·kg<sup>−1</sup>), and HSe (5.0 mg·kg<sup>−1</sup>). ‘-’ indicates no detectable selenium or invalid calculation. TF<sub>RH-BR</sub>: transport coefficient from rice husk to brown rice. TF<sub>L-RH</sub>: transport coefficient from leaf to rice husk. TF<sub>S-L</sub>: transport coefficient from stems to leaves. TF<sub>R-S</sub> transport coefficient from roots to stems. BCF<sub>BR</sub>: enrichment coefficient in brown rice. BCF<sub>RH</sub>: enrichment coefficient in rice husk. BCF<sub>L</sub>: enrichment coefficient in leaves. BCF<sub>S</sub>: enrichment coefficient in stems. BCF<sub>R</sub>: enrichment coefficient in roots.</p>
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<p>Effects of selenium on chlorophyll a (<b>A</b>), chlorophyll b (<b>B</b>), total chlorophyll (<b>C</b>) content, and chlorophyll a/b (<b>D</b>) in rice. CK (control; without selenium), LSe (0.2 mg·kg<sup>−1</sup> selenium addition), MSe (1.0 mg·kg<sup>−1</sup> selenium addition), HSe (5.0 mg·kg<sup>−1</sup> selenium addition). Different lowercase letters indicate significant differences between the different treatments during the same period (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of selenium on proline (<b>A</b>) and soluble sugar (<b>B</b>) levels in rice. CK (control; no selenium added), LSe (0.2 mg·kg<sup>−1</sup> selenium added), MSe (1.0 mg·kg<sup>−1</sup> selenium added), HSe (5.0 mg·kg<sup>−1</sup> selenium added). Different lowercase letters indicate significant differences between the different treatments during the same period (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of selenium on SOD (<b>A</b>), POD (<b>B</b>), CAT (<b>C</b>) activity, and MDA (<b>D</b>) content in rice. CK (control; no selenium added), LSe (0.2 mg·kg<sup>−1</sup> selenium added), MSe (1.0 mg·kg<sup>−1</sup> selenium added), HSe (5.0 mg·kg<sup>−1</sup> selenium added). Different lowercase letters indicate significant differences between the different treatments during the same period (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Correlations between the Se content and physiological characteristics of rice growth. SO<sub>Se</sub> denotes the soil selenium content; R<sub>Se</sub> is the selenium content of roots; ST<sub>Se</sub> represents the selenium content of stems; L<sub>Se</sub> refers to the leaf selenium content; RH<sub>Se</sub> is the selenium content of rice husks; BR<sub>Se</sub> indicates the selenium content of brown rice; S/R-DW is the above-ground and belowground biomass, respectively; Chla is chlorophyll a; Chlb is chlorophyll b; TChl is total chlorophyll. * indicates <span class="html-italic">p</span> &lt; 0.05, ** indicates <span class="html-italic">p</span> &lt; 0.01.</p>
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16 pages, 1235 KiB  
Article
Effects of Selenate Application on Growth, Nutrient Bioaccumulation, and Bioactive Compounds in Broccoli (Brassica oleracea var. italica L.)
by Maria J. Poblaciones, Carlos García-Latorre, Rocio Velazquez and Martin R. Broadley
Horticulturae 2024, 10(8), 808; https://doi.org/10.3390/horticulturae10080808 - 30 Jul 2024
Viewed by 644
Abstract
The biofortification of edible crops with selenium (Se) is a common and effective strategy to address inadequate Se intake, which is suffered by millions of people worldwide. However, there is little information regarding the effects of this practice on crops belonging to the [...] Read more.
The biofortification of edible crops with selenium (Se) is a common and effective strategy to address inadequate Se intake, which is suffered by millions of people worldwide. However, there is little information regarding the effects of this practice on crops belonging to the important Brassica family. To evaluate the efficacy of foliar Se application on broccoli, four treatments with varying Se concentrations were tested: 0%, 0.05%, 0.10%, and 0.15% (w/v), applied as sodium selenate during the early flowering stage. Although no overall effects on growth and biomass parameters were observed, the results indicate that the lowest Se dose (0.05-Se) was sufficient to notably increase Se concentration in the florets, even after boiling. Based on the increase to 14.2 mg Se kg−1 of dry matter in this broccoli fraction, it was estimated that consuming a 100-gram portion of boiled florets biofortified with 0.05% Se would provide approximately 140 µg of Se, which could be sufficient to potentially improve human selenium status, as previously documented. Moreover, the results obtained underscore how the application of this small dose was also adequate to reduce phytate concentration in the florets and to increase antioxidant and polyphenol concentrations, thereby improving the concentration and bioavailability of other essential nutrients, including Ca, Mg, Fe, and Zn, along with improving its quality as an antioxidant food. Full article
(This article belongs to the Section Vegetable Production Systems)
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<p>Effect of the interaction between the plant fraction (Stem+Leaves, raw florets, and boiled florets) and the biofortification treatment (Control, 0.05-Se, 0.10-Se, and 0.15-Se) on the total Se concentrations of the broccoli samples. The results are shown as the mean ± standard error (error bars). Different letters indicate significant differences according to Fisher’s protected LSD (least significant difference) test at <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Effect of the interaction between plant fraction (Stem+Leaves and raw florets) and biofortification treatment (Control, 0.05-Se, 0.10-Se and 0.15-Se) on (<b>a</b>) total phytic acid concentration, along with the phytate molar ratios of (<b>b</b>) Se (PA:Se), (<b>c</b>) Ca (PA:Ca), (<b>d</b>) Fe (PA:Fe), (<b>e</b>) Mg (PA:Mg), and (<b>f</b>) Zn (PA:Zn) in the broccoli samples. The results are shown as the mean ± standard error of the mean (error bars). Different letters indicate significant differences according to Fisher’s protected LSD (least significant difference) test at <span class="html-italic">p</span> ≤ 0.05.</p>
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<p>Effect of the interaction between the plant fraction (Stem+Leaves and raw florets) and the biofortification treatment (Control, 0.05-Se, 0.10-Se, and 0.15-Se) on (<b>a</b>) ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) scavenging activity and (<b>b</b>) TPC (total polyphenol concentration) of the broccoli samples. The results are shown as the mean ± standard error of the mean (error bars). Different letters indicate significant differences according to Fisher’s protected LSD (least significant difference) test at <span class="html-italic">p</span> ≤ 0.05.</p>
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16 pages, 4250 KiB  
Article
Investigating the Endophyte Actinomycetota sp. JW0824 Strain as a Potential Bioinoculant to Enhance the Yield, Nutritive Value, and Chemical Composition of Different Cultivars of Anise (Pimpinella anisum L.) Seeds
by Ahmed M. Mahmoud, Ahmed M. Reyad, Maha H. Khalaf, Mohamed S. Sheteiwy, Mona F. A. Dawood, Ahmed M. El-Sawah, Enas Shaban Ahmed, Abdul Malik, Wahidah H. Al-Qahtani, Mostafa A. Abdel-Maksoud, Nermien H. S. Mousa, Mohammed Alyafei and Hamada AbdElgawad
Biology 2024, 13(8), 553; https://doi.org/10.3390/biology13080553 - 23 Jul 2024
Cited by 1 | Viewed by 663
Abstract
Anise (Pimpinella anisum L.) seeds have various nutritional and therapeutic benefits and are thus considered a valuable addition to animal and human health. Hence, in this study, we aimed to induce the nutritive and biological value of anise seeds. To this end, [...] Read more.
Anise (Pimpinella anisum L.) seeds have various nutritional and therapeutic benefits and are thus considered a valuable addition to animal and human health. Hence, in this study, we aimed to induce the nutritive and biological value of anise seeds. To this end, the potential biofortification effect of the endophytic Actinomycetota sp. JW0824 strain, isolated during the fall of 2023 from the medicinal plant Achyranthes aspera, exhibiting natural distribution in the Jazan region of Saudi Arabia, was investigated in four varieties of anise seeds from Egypt, Tunisia, Syria, and Morocco. Results revealed significant increments (p < 0.05) in the seed dry weight percentage (DW%) and oil yields. In line with increased biomass accumulation, the metabolism of the primary and secondary metabolites was increased. There were differential increases in proteins, sugars, flavonoids, alkaloids, phenols, vitamins (e.g., β-carotene, ascorbic acid), and essential oil components (e.g., phenylpropanoids and monoterpenes), along with their precursor phenylalanine. Consistently, the activity of L-phenylalanine aminolyase (PAL) was increased in the Egyptian and Tunisian varieties at 83.88% and 77.19%, respectively, while 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase (DAHPS) activity increased in all varieties, with a significant 179.31% rise in the Egyptian variety. These findings highlight the beneficial effects of Actinomycetota sp. JW0824 as a bioinoculant for anise seeds, suggesting its potential application in agricultural practices to improve seed yield and quality. Further field trials are recommended to assess the commercial viability of this endophyte for enhancing anise seed production and potentially benefiting other plant species. Full article
(This article belongs to the Section Microbiology)
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<p>Phylogenetic analysis of the endophytic <span class="html-italic">Actinomycetota</span> sp JW0824. The neighbor-joining method was utilized to construct the tree based on 16S rRNA sequences. The bootstrap values for each node were determined from 100 replicates. <span class="html-italic">Actinomadura hibisca</span> JCM 9627 and <span class="html-italic">Escherichia coli</span> were used as the outgroup for this analysis.</p>
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<p>Percentage of dry weight (<b>A</b>) and water content (<b>B</b>) in control and different <span class="html-italic">Actinomycetota</span>-treated aniseed varieties. Data are represented by the mean of at least three replicates ± standard error. Stars (** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001) above columns refer to significant differences between controls and treated seeds at <span class="html-italic">p</span> &lt; 0.05. ns &gt; 0.05 (non-significant effect).</p>
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<p>Primary and secondary metabolites in control and <span class="html-italic">Actinomycetota</span>-treated aniseed varieties; <b>A</b> = Saponin, <b>B</b> = steroid, <b>C</b> = total protein, <b>D</b> = total sugar, <b>E</b> = ash, <b>F</b> = crude fiber, <b>G</b> = total phenols, <b>H</b> = total falvonoids, <b>I</b> = total alkaloids, and <b>J</b> = tanins. Data are represented by the mean of at least three replicates ± standard error. Stars (*) above columns indicate significant differences between the control and the bacteria-treated samples at <span class="html-italic">p</span> &lt; 0.05. * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, and **** <span class="html-italic">p</span> ≤ 0.0001. ns &gt; 0.05 (non-significant effect).</p>
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<p>Vitamins in control and <span class="html-italic">Actinomycetota</span>-treated aniseed varieties. (<b>A</b>) tocopherol, (<b>B</b>) β-carotene, (<b>C</b>) thiamine and (<b>D</b>) ascorbic acid. Data are represented by the means of at least three replicates ± standard error. Stars (*) above columns indicate significant differences between the control and the bacteria-treated samples at <span class="html-italic">p</span> &lt; 0.05. * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001. ns &gt; 0.05 (non-significant effect).</p>
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<p>The total oil yield (<b>A</b>) and essential oil percentage (<b>B</b>) in the control and <span class="html-italic">Actinomycetota</span>-treated aniseed varieties. Data are represented by the mean of at least three replicates ± standard error. Stars (*) above columns indicate significant differences between the control and the bacteria-treated samples; * <span class="html-italic">p</span> ≤ 0.05 and ** <span class="html-italic">p</span> ≤ 0.01. ns &gt; 0.05 (non-significant effect).</p>
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<p>Essential oil-related precursors and related enzyme activities in the control and <span class="html-italic">Actinomycetota</span>-treated aniseed varieties; <b>A</b> = L-phenylalanine aminolyase, <b>B</b> = cinnamic acid, <b>C</b> = shikimic acid, and <b>D</b> = o-methyltransferase. Data are represented by the mean of at least three replicates ± standard error. Stars (*) above columns indicate significant differences between the control and the bacteria-treated samples; * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, and **** <span class="html-italic">p</span> ≤ 0.0001. ns &gt; 0.05 (non-significant effect).</p>
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17 pages, 3818 KiB  
Article
Effects of Selenium Content on Growth, Antioxidant Activity, and Key Selenium-Enriched Gene Expression in Alfalfa Sprouts
by Yaru Ren, Qian Zhang, Xiang Li, Tianyi Zhang, Daicai Tian, Liang Liu, Xuyan Dong, Zeng-Yu Wang and Maofeng Chai
Foods 2024, 13(14), 2261; https://doi.org/10.3390/foods13142261 - 18 Jul 2024
Viewed by 642
Abstract
To enhance the selenium (Se) intake of the general public, the present study implemented biofortification techniques in alfalfa sprouts. Alfalfa sprouts possess unique nutritional value and provide an optimal Se-enriched supplemental Se source. The impact of sodium selenite (Na2SeO3) [...] Read more.
To enhance the selenium (Se) intake of the general public, the present study implemented biofortification techniques in alfalfa sprouts. Alfalfa sprouts possess unique nutritional value and provide an optimal Se-enriched supplemental Se source. The impact of sodium selenite (Na2SeO3) on alfalfa shoot germination, shoot length, and biomass was assessed experimentally, and changes in the antioxidant capacity of sprouts treated with optimal Se concentrations were investigated. In addition, the transcriptome of alfalfa sprouts treated with the optimal Na2SeO3 concentration was sequenced. Gene co-expression networks, constructed through differential gene analysis and weighted gene co-expression network analysis, were used to identify the core genes responsible for Se enrichment in alfalfa sprouts. The findings of the present study offer novel insights into the effects of Se treatment on the nutrient composition of alfalfa sprouts, in addition to introducing novel methods and references that could facilitate production of Se-enriched alfalfa sprouts and associated products. Full article
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<p>Growth and physiological characteristics of alfalfa sprouts. (<b>A</b>) Effect of selenium concentration on germination percentage of alfalfa seeds after a 7-day germination cycle. Analysis of variance (ANOVA) was performed using Origin, and different letters indicate statistically significant differences. The germination data of each concentration treatment were collected from 100 alfalfa seeds of each replicate with three replicates. (<b>B</b>) Effect of selenium concentration on alfalfa shoot length (excluding root and cotyledon parts) after a 7-day germination cycle. Analysis of variance (ANOVA) was performed using Origin; different letters indicate statistically significant differences; the data were presented as mean. (<b>C</b>) Effect of selenium concentration on the biomass of alfalfa sprouts after a 7-day germination cycle. Analysis of variance (ANOVA) was performed using Origin; different letters indicate statistically significant differences. (<b>D</b>) Total and organic selenium content of samples treated with varying selenium concentrations; different letters indicate statistically significant differences.</p>
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<p>The seed germination velocity (<b>A</b>) and the appearance of representative alfalfa sprouts (<b>B</b>) grown from 1 to 7 days at Se concentrations of 0 (CK) and 60 mg/L (Treatment). Scale bar = 1 cm. Alfalfa sprouts in the transparent dish were grown for 7 days in the black tray and photographed. The alfalfa seeds were measured for growth velocity in three replicates with 50 seeds per replicate.</p>
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<p>Analysis of the antioxidant capacity of selenium-enriched alfalfa sprouts. (<b>A</b>) Hydroxyl radical scavenging rate. (<b>B</b>) DPPH radical scavenging rate. (<b>C</b>) Changes in GPx content. (<b>D</b>) Changes in CAT content. (<b>E</b>) Changes in MDA content in CK (0 mg/L Na<sub>2</sub>SeO<sub>3</sub>) and Treatment (60 mg/L Na<sub>2</sub>SeO<sub>3</sub>) groups.</p>
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<p>Transcriptomic overview of selenium-induced gene expression in selenium-enriched alfalfa sprouts. (<b>A</b>) Differential gene MA map. (<b>B</b>) GO categorization statistics following up- and down-regulation of differentially expressed genes. (<b>C</b>) KEGG pathway of DEGs.</p>
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<p>DEGs in selenium metabolic pathways of KEGG metabolic pathway map. Green indicates down-regulated genes, red indicates up-regulated genes, and white indicates no significant change in gene expression levels.</p>
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<p>The qRT-PCR analysis of the genes related to selenium metabolic pathways in selenium-enriched alfalfa sprouts.</p>
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<p>Analysis of the regulation of key gene expression modules. (<b>A</b>) Correlation network diagram of key genes in the yellow module. (<b>B</b>) Correlation network diagram of key genes in the magenta module.</p>
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16 pages, 9519 KiB  
Article
Foliar Spraying with ZnSO4 or ZnO of Vitis vinifera cv. Syrah Increases the Synthesis of Photoassimilates and Favors Winemaking
by Diana Daccak, Ana Coelho Marques, Cláudia Campos Pessoa, Ana Rita F. Coelho, Inês Carmo Luís, Graça Brito, José Carlos Kullberg, José C. Ramalho, Ana Paula Rodrigues, Paula Scotti-Campos, Isabel P. Pais, José N. Semedo, Maria Manuela Silva, Paulo Legoinha, Carlos Galhano, Manuela Simões, Fernando H. Reboredo and Fernando C. Lidon
Plants 2024, 13(14), 1962; https://doi.org/10.3390/plants13141962 - 17 Jul 2024
Viewed by 812
Abstract
Zinc enrichment of edible food products, through the soil and/or foliar application of fertilizers, is a strategy that can increase the contents of some nutrients, namely Zn. In this context, a workflow for agronomic enrichment with zinc was carried out on irrigated Vitis [...] Read more.
Zinc enrichment of edible food products, through the soil and/or foliar application of fertilizers, is a strategy that can increase the contents of some nutrients, namely Zn. In this context, a workflow for agronomic enrichment with zinc was carried out on irrigated Vitis vinifera cv. Syrah, aiming to evaluate the mobilization of photoassimilates to the winegrapes and the consequences of this for winemaking. During three productive cycles, foliar applications were performed with ZnSO4 or ZnO, at concentrations ranging between 150 and 1350 g.ha−1. The normal vegetation index as well as some photosynthetic parameters indicated that the threshold of Zn toxicity was not reached; it is even worth noting that with ZnSO4, a significant increase in several cases was observed in net photosynthesis (Pn). At harvest, Zn biofortification reached a 1.2 to 2.3-fold increase with ZnSO4 and ZnO, respectively (being significant relative to the control, in two consecutive years, with ZnO at a concentration of 1350 g.ha−1). Total soluble sugars revealed higher values with grapes submitted to ZnSO4 and ZnO foliar applications, which can be advantageous for winemaking. It was concluded that foliar spraying was efficient with ZnO and ZnSO4, showing potential benefits for wine quality without evidencing negative impacts. Full article
(This article belongs to the Special Issue Nutrients Uptake, Transport, and Function in Plant Metabolism)
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<p>(<b>A</b>) Orthophotomap of the 1st year (outlined with a red line) and 2nd and 3rd year (outlined with a black line) (<b>B</b>) digital map of slopes of the vineyard of <span class="html-italic">Vitis vinifera</span> cv. Syrah grapes.</p>
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<p>Soil characterization (at about 30 cm depth) in the vineyard. (<b>A</b>) Mineral elements (Ca, K, P, and Fe (in %) and Mn, S, Zn, and Cu (in ppm)); (<b>B</b>) organic matter (%), moisture (%), pH, and conductivity (µS.cm<sup>−1</sup>) of the soil.</p>
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<p>Physicochemical characterization of irrigation water in the vineyard of Syrah during the 2nd and 3rd years of the experimental period. Projection of water sample with (<b>A</b>) a ternary Piper diagram; (<b>B</b>) a Wilcox diagram.</p>
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<p>Normalized difference vegetation index (NDVI) of the vineyard with <span class="html-italic">Vitis vinifera</span> cv. Syrah during the experimental period (2nd and 3rd year, after the 4th and 1st foliar applications with ZnO or ZnSO<sub>4</sub>, respectively). Syrah: 1—control; 2—ZnO (900 g.ha<sup>−1</sup>); 3—ZnO (1350 g.ha<sup>−1</sup>); 4—ZnSO<sub>4</sub> (900 g.ha<sup>−1</sup>); 5—ZnSO<sub>4</sub> (1350 g.ha<sup>−1</sup>). (<b>A</b>) Second year of the experimental period (rows 1 to 5 were used); (<b>B</b>) third year of the experimental period (the 2nd and 4th rows were not used).</p>
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<p>Average ± S.E (<span class="html-italic">n</span> = 3) total soluble solids (expressed in <sup>o</sup>Brix) in grapes of <span class="html-italic">Vitis vinifera</span> variety Syrah at harvest during the 1st, 2nd, and 3rd years of the productive cycle. Letters a, b, and c, d indicate significant differences among the treatments (statistical analysis using the one-way ANOVA test, <span class="html-italic">p</span> ≤ 0.05).</p>
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