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Search Results (491)

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15 pages, 1175 KiB  
Article
Investigating the Synergistic Effect of Tillage System and Manure Application Rates on Selected Properties of Two Soil Types in Limpopo Province, South Africa
by Matome J. Mokgolo, Jestinos Mzezewa and Mussie G. Zerizghy
Sustainability 2024, 16(20), 8941; https://doi.org/10.3390/su16208941 (registering DOI) - 16 Oct 2024
Viewed by 126
Abstract
Sustainable agricultural practices are needed to find a solution to the problem of soil erosion and decreased soil quality. A study was conducted during the 2021/2022 and 2022/2023 cropping seasons to evaluate the synergistic effect of the tillage system (TS) and manure rates [...] Read more.
Sustainable agricultural practices are needed to find a solution to the problem of soil erosion and decreased soil quality. A study was conducted during the 2021/2022 and 2022/2023 cropping seasons to evaluate the synergistic effect of the tillage system (TS) and manure rates (MR) on selected soil properties at the University of Limpopo Experimental Farm (Syferkuil) and University of Venda Experimental Farm (UNIVEN). The experiment had a split plot design with three replications. The main plots used conventional (CON) and in-field rainwater harvesting (IRWH) tillage systems, while subplots used poultry and cattle manure at rates of 0, 20, and 35 t ha−1. Bulk density (BD), aggregate stability (AS), pH, total N, organic carbon (OC), available P, and exchangeable cations (Ca, Mg, and K) were determined. IRWH significantly increased AS in the 0–20 cm soil layer at Syferkuil. TS × MR interaction significantly influenced AS and total N in the 20–40 cm soil layer during the 2022/2023 season at Syferkuil. IRWH significantly increased Mg content in the 2021/2022 season and total N, OC, and Mg content in the 2022/2023 season at Syferkuil over CON. At UNIVEN, CON significantly increased total N, whereas IRWH increased available P in the 2022/2023 season. MR significantly increased AS, exchangeable Ca, Mg, and K at both sites. At Syferkuil, MR significantly increased total N, OC, and available P during both seasons, whereas at UNIVEN the significant increase was observed on OC and available P during both seasons and total N in the 2021/2022 season. It was found that IRWH and poultry manure (35 t ha−1) improved most soil properties at both sites; however, this study recommends long-term experiments to investigate the combined effect of IRWH and manure rate on soil properties to validate the findings observed in this study. Full article
(This article belongs to the Section Soil Conservation and Sustainability)
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Figure 1
<p>Means of exchangeable cations as affected by tillage system during 2021/2022 and 2022 and 2022/2023 cropping seasons at Syferkuil. Same letters show no significant difference between treatments.</p>
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<p>Means of exchangeable cations as affected by tillage system during 2021/2022 and 2022 and 2022/2023 cropping seasons at UNIVEN. Same letters show no significant difference between treatments.</p>
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<p>Means of exchangeable cations as affected by manure rate during 2021/2022 cropping season at Syferkuil. Same letters show no significant difference among treatments.</p>
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<p>Means of exchangeable cations as affected by manure rate during 2022/2023 cropping season at Syferkuil. Same letters show no significant difference among treatments.</p>
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<p>Means of exchangeable cations as affected by manure rate during 2021/2022 cropping season at UNIVEN. Same letters show no significant difference among treatments.</p>
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<p>Means of exchangeable cations as affected by manure rate during 2022/2023 cropping season at UNIVEN. Same letters show no significant difference among treatments.</p>
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19 pages, 1500 KiB  
Article
Impact of Poultry Manure-Derived Biochar and Bio-Fertilizer Application to Boost Production of Black Cumin Plants (Nigella sativa L.) Grown on Sandy Loam Soil
by Yasser A. Sayed, Ahmed M. Ali, Mostafa F. Ibrahim, Mohamed E. Fadl, Cristiano Casucci, Marios Drosos, Antonio Scopa and Hassan M. Al-Sayed
Agriculture 2024, 14(10), 1801; https://doi.org/10.3390/agriculture14101801 - 13 Oct 2024
Viewed by 593
Abstract
Biochar derived from poultry manure increases nutrient availability and promotes plant growth. This study investigated the effect of biochar with mycorrhizal and/or plant growth-promoting rhizobacteria on soil fertility, chemical properties, oil, and seed yield of Black Cumin (Nigella sativa L.) plants. A [...] Read more.
Biochar derived from poultry manure increases nutrient availability and promotes plant growth. This study investigated the effect of biochar with mycorrhizal and/or plant growth-promoting rhizobacteria on soil fertility, chemical properties, oil, and seed yield of Black Cumin (Nigella sativa L.) plants. A split-plot design with three replicates was employed, with biochar derived from poultry litter (BC) applied at rates of 0, 5, and 10 t ha−1, with beneficial microbes such as arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) affecting the growth of Black Cumin plants, and some soil properties, such as pH, electrical conductivity (EC), soil organic matter (SOM) and fertility index (FI), showing significant differences (p ≤ 0.05) among biochar and/or bio-fertilizer treatments. All biochar treatments with or without bio-fertilizers significantly increased pH, EC, OM and FI in comparison to the control treatment. The results demonstrated that applying biochar at the highest rate (10 t ha−1) increased fresh and dry capsule weights by 94.51% and 63.34%, respectively, compared to the control treatment (C). These values were significantly increased by 53.05 and 18.37%, compared to untreated plants when combined with AMF and PGPR. Furthermore, when biochar was applied in conjunction with both AMF and PGPR, fresh and dry capsule weights saw significant increases of 208.84% and 91.18%, respectively, compared to the untreated control treatment. The interaction between biochar, AMF, and PGPR significantly improved plant growth, yield, soil properties, and the fixed and volatile oil content of Black Cumin. These findings suggest that the combined application of biochar, AMF, and PGPR enhances nutrient availability and uptake, leading to improved growth and higher yields in Black Cumin plants, resulting in increased yield production. Full article
(This article belongs to the Section Crop Production)
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<p>The design of field plots.</p>
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<p>Effect of biochar and/or bio-fertilizer on uptake nitrogen N of (<b>a</b>), (<b>b</b>) phosphorous P, and (<b>c</b>) potassium K of Black Cumin plants. BC0, BC1 and BC2, biochar at rates of 0, 5 and 10 t ha<sup>−1</sup>; AMF, arbuscular mycorrhizal fungi and PGPR, plant growth-promoting rhizobacteria. Means in each column followed by the same letters are not significantly different (<span class="html-italic">p</span> &lt; 0.05) by Duncan’s multiple range test.</p>
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26 pages, 6450 KiB  
Article
High-Gain Multi-Band Koch Fractal FSS Antenna for Sub-6 GHz Applications
by Atul Varshney and Duygu Nazan Gençoğlan
Appl. Sci. 2024, 14(19), 9022; https://doi.org/10.3390/app14199022 - 6 Oct 2024
Viewed by 662
Abstract
This study introduces a novel antenna based on the binary operation of a modified circular patch in conjunction with the Koch fractal. The antenna is intended for applications in the sub-6 GHz band, partial C-band, and X-band. The low-cost antenna is fabricated on [...] Read more.
This study introduces a novel antenna based on the binary operation of a modified circular patch in conjunction with the Koch fractal. The antenna is intended for applications in the sub-6 GHz band, partial C-band, and X-band. The low-cost antenna is fabricated on a 1.6-mm-thick FR-4 substrate. A frequency-selective surface (FSS) is used to overcome the decreased values of the gain and bandwidth due to the fractal operations. The introduced split ring resonator (SRR) and the antenna substrate dimension reduction reduce the bandwidth and antenna gain. The air gap between the FSS and the antenna not only enhances the antenna gain but also controls the frequency tuning at the design frequency. The antenna size is miniaturized to 36.67%. A monopole antenna ground loaded with an SRR results in improved closest tuning (3.44 GHz) near the design frequency. The antenna achieves a peak gain of 9.37 dBi in this band. The FSS-based antenna results in a 4.65 dBi improvement in the gain value with the FSS. The measured and simulated plots exhibit an excellent match with each other in all three frequency bands at 2.96–4.72 GHz. These bands cover Wi-MAX (3.5 GHz), sub-6 GHz n77 (3300–3800 MHz), n78 (3300–4200 MHz), and approximately n79 (4400–4990 MHz), in addition to C-band applications. Full article
(This article belongs to the Special Issue Antenna Design and Microwave Engineering)
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<p>Koch fractal principle.</p>
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<p>Development of Koch fractal iteration 0 stage.</p>
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<p>Fractal antenna patch development: (<b>a</b>) iteration 0, (<b>b</b>) iteration 1, and (<b>c</b>) iteration 2.</p>
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<p>Frequency-selective surface: (<b>a</b>) FSS structure and (<b>b</b>) equivalent circuit of FSS.</p>
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<p>Step-by-step design development.</p>
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<p>Koch fractal antenna (<b>a</b>) with FSS; (<b>b</b>) side view; (<b>c</b>) top patch, bottom ground, and FSS view; and (<b>d</b>) antenna 3D model.</p>
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<p>Split ring resonator (SRR) structure designed at 3.5 GHz.</p>
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<p>Effects of iterations.</p>
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<p>Effects of reduced ground and SRR loading.</p>
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<p>Miniaturization process.</p>
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<p>FSS loading effect on miniaturized Koch fractal antenna: (<b>a</b>) frequency tuning and gain enhancement and (<b>b</b>) effect of air gap on resonance frequency and cumulative effective permittivity.</p>
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<p>SRR loading effect on FSS miniaturized Koch fractal antenna.</p>
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<p>FSS loading effect on miniaturized Koch fractal antenna: (<b>a</b>) antenna radiator (top view), (<b>b</b>) antenna ground (bottom view), (<b>c</b>) FSS structure, and (<b>d</b>) antenna prototype model.</p>
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<p>FSS loading effect on miniaturized Koch fractal antenna: (<b>a</b>) antenna radiator (top view), (<b>b</b>) antenna ground (bottom view), (<b>c</b>) FSS structure, and (<b>d</b>) antenna prototype model.</p>
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<p>Simulated vs. measured reflection coefficients: (<b>a</b>) without FSS and (<b>b</b>) with FSS.</p>
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<p>Simulated vs. measured radiation patterns in E-plane and H-plane at (<b>a</b>) 3.62 GHz, (<b>b</b>) 7.82 GHz, and (<b>c</b>) 10.58 GHz.</p>
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<p>Simulated vs. measured radiation patterns in E-plane and H-plane at (<b>a</b>) 3.62 GHz, (<b>b</b>) 7.82 GHz, and (<b>c</b>) 10.58 GHz.</p>
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<p>Simulated vs. measured antenna gains.</p>
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<p>Current density distribution of the proposed fractal antenna: (<b>a</b>) current density without FSS at 3.5 GHz, (<b>b</b>) current density with FSS at 3.5 GHz, (<b>c</b>) current density with FSS at 3.62 GHz, (<b>d</b>) current density with FSS at 7.82 GHz, and (<b>e</b>) current density with FSS at 10.58 GHz.</p>
Full article ">Figure 17 Cont.
<p>Current density distribution of the proposed fractal antenna: (<b>a</b>) current density without FSS at 3.5 GHz, (<b>b</b>) current density with FSS at 3.5 GHz, (<b>c</b>) current density with FSS at 3.62 GHz, (<b>d</b>) current density with FSS at 7.82 GHz, and (<b>e</b>) current density with FSS at 10.58 GHz.</p>
Full article ">Figure 17 Cont.
<p>Current density distribution of the proposed fractal antenna: (<b>a</b>) current density without FSS at 3.5 GHz, (<b>b</b>) current density with FSS at 3.5 GHz, (<b>c</b>) current density with FSS at 3.62 GHz, (<b>d</b>) current density with FSS at 7.82 GHz, and (<b>e</b>) current density with FSS at 10.58 GHz.</p>
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17 pages, 3055 KiB  
Article
Growth Performance of Sabia Grass Irrigated by Drippers Installed in Subsurface
by Mayara Oliveira Rocha, Amilton Gabriel Siqueira de Miranda, Policarpo Aguiar da Silva, Job Teixeira de Oliveira and Fernando França da Cunha
AgriEngineering 2024, 6(3), 3443-3459; https://doi.org/10.3390/agriengineering6030196 - 18 Sep 2024
Viewed by 353
Abstract
Studies to improve the use of subsurface drippers in pasture formation are needed. Therefore, the objective of this study was to evaluate the germination and emergence of Sabia grass as a function of drippers installed at different depths. The study was conducted in [...] Read more.
Studies to improve the use of subsurface drippers in pasture formation are needed. Therefore, the objective of this study was to evaluate the germination and emergence of Sabia grass as a function of drippers installed at different depths. The study was conducted in pots in Viçosa, Minas Gerais State, Brazil. The experiment was conducted using a completely randomized design with four replicates. The experimental layout featured split plots over time, where the main plots consisted of three cultivation cycles and the subplots represented various dripper installation depths. The three sowing dates were 26 March, 12 April, and 29 April 2022. Drip tapes were installed at seven different depths: 0 (superficial), 5, 10, 15, 20, 25, and 30 cm. The results showed that the reduction in water potential, associated with increased temperature, resulted in lower performance of Sabia grass seeds. Seed germination and parameters related to germination speed were negatively impacted by the increase in dripper installation depth, with a 30–40% reduction in germination speed observed at depths greater than 15 cm. Drippers installed at 15–20 cm depth in clayey soil were ideal, providing a balance between reducing soil water evaporation and maintaining seedling emergence rates. Compared to surface installation, this depth improved seed performance by up to 25%, while enhancing operability and minimizing water loss. It is recommended to install drippers at a depth of 15–20 cm in subsurface drip irrigation systems in clayey soil areas to achieve benefits such as decreased soil water evaporation and improved operability compared to surface systems. Full article
(This article belongs to the Section Agricultural Irrigation Systems)
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<p>Daily values of mean air temperature (°C), solar radiation (MJ m<sup>−2</sup> d<sup>−1</sup>), and mean relative humidity (%) in three cycles of initial development of Sabia grass. Viçosa, MG, Brazil, DEA-UFV, 2022.</p>
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<p>Cumulative values of reference evapotranspiration (ETo) and irrigations carried out in three cycles of germination and emergence of Sabia grass. Viçosa, MG, Brazil, DEA-UFV, 2022.</p>
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<p>Final germination (FG) and times required for germination of 10%, 50%, and 90% of seeds (T10, T50 and T90) of Sabia grass as a function of irrigation with drippers installed at different depths and in different germination cycles. Viçosa, MG, Brazil, DEA-UFV, 2022. *, **, *** = significant at 5%, 1%, and 0.1% probability levels, respectively.</p>
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<p>Final germination (FG) and times required for germination of 10%, 50%, and 90% of seeds (T10, T50 and T90) of Sabia grass as a function of irrigation with drippers installed at different depths and in different germination cycles. Viçosa, MG, Brazil, DEA-UFV, 2022. *, **, *** = significant at 5%, 1%, and 0.1% probability levels, respectively.</p>
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<p>Germination speed index (GSI), mean germination time (MGT), mean germination rate (MGR), and germination uniformity (GUnif) of Sabia grass as a function of irrigation with drippers installed at different depths and in different germination cycles. Viçosa, MG, Brazil, DEA-UFV, 2022. **, *** = significant at 1%, and 0.1% probability levels, respectively.</p>
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<p>Root length (RL), shoot length (SL), and fresh (SFM) and dry (SDM) mass of Sabia grass seedlings as a function of irrigation with drippers installed at different depths and in different cultivation cycles. Viçosa, MG, Brazil, DEA-UFV, 2022. **, *** = significant at 1%, and 0.1% probability levels, respectively.</p>
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<p>Root length (RL), shoot length (SL), and fresh (SFM) and dry (SDM) mass of Sabia grass seedlings as a function of irrigation with drippers installed at different depths and in different cultivation cycles. Viçosa, MG, Brazil, DEA-UFV, 2022. **, *** = significant at 1%, and 0.1% probability levels, respectively.</p>
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25 pages, 4117 KiB  
Article
Modeling the Effects of Irrigation and Its Interaction with Silicon on Quinoa Seed Yield and Water Use Efficiency in Arid Regions
by Amira M. El-Tahan, Mohamed Emran, Fatmah A. Safhi, Asal M. Wali, Sherien E. Sobhy and Omar M. Ibrahim
Agronomy 2024, 14(9), 2088; https://doi.org/10.3390/agronomy14092088 - 12 Sep 2024
Viewed by 652
Abstract
Despite quinoa (Chenopodium quinoa Willd.) gaining international popularity in the early 21st century for its nutritional benefits, there remains a critical need to optimize its cultivation practices in arid regions. Current research often overlooks the combined effects of supplemental irrigation and foliar [...] Read more.
Despite quinoa (Chenopodium quinoa Willd.) gaining international popularity in the early 21st century for its nutritional benefits, there remains a critical need to optimize its cultivation practices in arid regions. Current research often overlooks the combined effects of supplemental irrigation and foliar treatments on quinoa’s yield and water efficiency, particularly under challenging environmental conditions like those in Borg El-Arab, Egypt. Field studies were conducted in Borg El-Arab, Alexandria, Egypt, during the winter seasons of 2021/2022 and 2022/2023 to determine the influence of supplemental irrigation (rainfed, 2000, and 4000 m3/hectare, respectively) and foliar spraying of sodium silicate (control, 200, and 400 ppm) on yield, yield components, seed quality, and water usage efficiency in quinoa cv. Chibaya grown in arid lands. Three replications were used in a split-plot design. The main plots were designated for irrigation, while the subplots were designated for foliar spraying. The results indicate that applying irrigation at a rate of 4000 m3/hectare significantly increased leaf dry weight per plant by 23.5%, stem dry weight per plant by 18.7%, total dry weight per 25 plants by 21.4%, leaf area per plant by 19.2%, and straw yield by 26.8% compared to the control treatment. There were no significant differences between irrigation with the rate of 4000 m3 or 2000 m3/hectare on biological yield kg/hectare, N (%), P (mg/100 g), and protein (%). The utilization of sodium silicate had no significance on all studied features except for straw yield kg ha−1 at the rate of 200 or 400 ppm. The results regarding the RAPD1 primer revealed that the 2000+0 silicon treatment was the only treatment that resemble the control with no up- or downregulated fragment. Moreover, 20 upregulated fragments were observed in all treatments, while 19 DNA fragments were downregulated. Furthermore, the results obtained regarding the RAPD2 primer revealed that 53 fragments were upregulated and 19 downregulated. Additionally, the RAPD3 primer demonstrated that 40 DNA fragments were upregulated, whereas 18 downregulated DNA fragments were detected. It may be inferred that the application of irrigation at a rate of 4000 m3 ha−1 might serve as a supplemental irrigation method. Spraying sodium silicate at a 400 mg L−1 concentration could alleviate the dry climate on the Egyptian shore. Full article
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<p>Relation between the first two factor structures obtained by running factor analysis using soil data of irrigation treatments (I1, I2, and I3 in the first three graphs, respectively) and the overall soil data over the observed period (fourth graph).</p>
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<p>Seed yield, biological yield, and straw yield of quinoa (kg ha<sup>−1</sup>) as affected by the interaction between irrigation and silicon. Different lowercase letters indicate significant differences among the treatments based on the interaction between irrigation and silicon. Treatments followed by the same letter are not significantly different from each other at the 0.05 significance level.</p>
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<p>The structure of the used artificial neural network using inputs (irrigation and silicon), bias (B1 and B2), hidden layer neurons (H1–H6), and output (seed yield).</p>
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<p>Relative importance of the studied traits to the yield.</p>
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<p>Gene expression of dd-PCR using different arbitrary RAPD primers (RAPD 1, 2, and 3), where M (DNA marker), 1 (control), 2 (100 silicon), 3 (200 silicon), 4 (800+0 silicon), 5 (800+100 silicon), 6 (800+200 silicon), 7 (1200+0 silicon), 8 (1200+100 silicon), 9 (1200+200 silicon), 10 (1600+0 silicon), 11 (1600+100 silicon), and 12 (1600+200 silicon).</p>
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<p>Cluster dendrogram of treated and untreated quinoa based on molecular data generated from three RAPD primers.</p>
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<p>Effect of irrigation and silicon on the expression level of DRF1 (<b>a</b>) and CBF3 (<b>b</b>) genes in quinoa. Different letters indicate statistically significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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14 pages, 714 KiB  
Article
Pre-Crop and Residue Management Effects on Photosynthesis Efficiency and Grain Yield of Dryland Wheat Genotypes
by Ramin Lotfi, Saber Golkari, Amin Abbasi, Reza Rahimzadeh, Arash Mohammadzadeh and Mohammad Pessarakli
Crops 2024, 4(3), 426-439; https://doi.org/10.3390/crops4030030 - 6 Sep 2024
Viewed by 438
Abstract
To evaluate dryland wheat genotypes’ performance under different pre-crop and residue managements under dryland conditions, a split–split plot experiment based on the RCB design, with three replications, was conducted for two years (2017–2018 and 2018–2019). The site of the study has a long-term [...] Read more.
To evaluate dryland wheat genotypes’ performance under different pre-crop and residue managements under dryland conditions, a split–split plot experiment based on the RCB design, with three replications, was conducted for two years (2017–2018 and 2018–2019). The site of the study has a long-term average precipitation, temperature, and relative humidity of 376 mm, 9 °C, and 50%, respectively. Wheat–wheat and vetch–wheat cropping systems were considered in the main plots, different wheat and vetch residue levels, including 0, 2, and 4 t ha−1, were located in the subplots, and five dryland wheat genotypes, including Sadra, Hashtroud, Baran, Varan, and Ohadi, were allocated in the sub-sub plots. The results indicated that the leaf chlorophyll content index (CCI) and stomatal conductance (gs) were greater in the vetch–wheat cropping system compared to the wheat monoculture system for all genotypes. The normalized difference vegetation index (NDVI) of the genotypes improved by applying the crop residue. Over two years, the application of crop residues resulted in higher variable fluorescence at the J and I steps, as well as an increase in the photosynthesis performance index (PI). The Varan and Baran genotypes stood out as the superior genotype, exhibiting the highest values in physiological characteristics and grain yield under the application of 4 t ha−1 of vetch residue. The grain-filling rate (GFR) was reduced, while the grain-filling duration (GFD) was increased with increasing the crop residue levels. The enhanced grain yield of the wheat genotypes grown under vetch residue was attributed to factors such as improvement in leave pigments and photosynthetic efficiency, which facilitate longer grain filling duration, with high grain weight. As a result, it is advisable to adopt a vetch–wheat cropping system with a high proportion of crop residue in dryland regions to achieve increased and sustainable wheat production. Full article
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<p>Changes in chlorophyll content index (CCI) of the wheat genotypes under different crop residue levels. Means followed by the same letter are not significantly different at <span class="html-italic">p</span> &lt; 0.05 according to the Duncan multiple range test. ** is significant at 1% probability levels.</p>
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<p>Changes in Fv/Fo (<b>A</b>), Fv/Fm (<b>B</b>), and VI (<b>C</b>) of wheat genotypes under wheat–wheat (w-w) and forage (vetch)–wheat (f-w) rotation during 2017–2018 and 2018–2019. Means followed by the same letter are not significantly different at <span class="html-italic">p</span> &lt; 0.05 according to the Duncan multiple range test. Fv, Fo, FV/Fm, and VI refer to the water-splitting complex in PSII, the maximum quantum efficiency of the PSII, and relative variable fluorescence at I step, respectively.</p>
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16 pages, 4066 KiB  
Article
Higher Seed Rates Enlarge the Effects of Wide-Belt Sowing on Root Length Density, Thereby Improving Nitrogen Uptake and Use Efficiencies in Winter Wheat
by Yuechao Wang, Wen Li, Yaoyao Deng, Jianfu Xue and Zhiqiang Gao
Plants 2024, 13(17), 2476; https://doi.org/10.3390/plants13172476 - 4 Sep 2024
Viewed by 386
Abstract
The optimized sowing method and appropriate seed rate can improve wheat N use efficiency. However, the interactive effect of the sowing method and seed rate on N use efficiency, particularly N uptake and root length density, are unclear. A field experiment was conducted [...] Read more.
The optimized sowing method and appropriate seed rate can improve wheat N use efficiency. However, the interactive effect of the sowing method and seed rate on N use efficiency, particularly N uptake and root length density, are unclear. A field experiment was conducted for two growing seasons in southern Shanxi province, China, using a split-plot design with the sowing method as the main plot (wide-belt sowing, WBS, and conventional narrow-drill sowing, NDS) and seed rate as the sub-plot (100–700 m−2). Our results showed that WBS had a significant and positive effect on N use efficiency (yield per unit of available N from the fertilizer and soil, by 4.7–15.4%), and the relatively higher seed rates (>300 or 400 m−2) enlarged the effects. The N use efficiency increases under WBS were mainly attributed to the increases in N uptake before anthesis, resulting from the promoted nodal roots per plant and per unit area, and root length density in the top layer(s). WBS promoted N translocation and the N harvest index, resulting in equivalent grain protein concentration and processing quality compared to NDS. Thus, adopting higher seed rates (>300 m−2) combined with WBS is recommended for achieving greater N efficiencies while maintaining the grain protein concentration and processing quality of winter wheat. Full article
(This article belongs to the Special Issue Ecophysiology and Quality of Crops)
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Figure 1
<p>N use efficiency, uptake efficiency, and utilization efficiency of winter wheat with narrow-drill sowing (NDS) and wide-belt sowing (WBS) in two growing seasons. Data are means and error bars are SEs (n = 4). The dashed line is a reference line indicating that the difference in the percentage of efficiency between WBS and NDS is zero. * and ** indicate that there is a significant difference between WBS and NDS at the specific seed rate, according to Student’s <span class="html-italic">t</span>-test at α = 0.05 and 0.01, respectively.</p>
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<p>N uptake at anthesis and maturity of winter wheat with narrow-drill sowing (NDS) and wide-belt sowing (WBS) in the 2020–2021 and 2021–2022 growing seasons. Data are means and error bars are SEs (n = 4). The dashed line is a reference line indicating that the difference in the percentage between WBS and NDS is zero. * and ** indicate that there is a significant difference between WBS and NDS at the specific seed rate, according to Student’s <span class="html-italic">t</span>-test at α = 0.05 and 0.01, respectively.</p>
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<p>Root length density in the 0–100 cm soil layer (RLD<sub>0–100</sub>) in the 2020–2021 and 2021–2022 growing seasons. Data are means and error bars are SEs (n = 4). The dashed line is a reference line indicating that the difference percentage between WBS and NDS is zero. * and ** indicate that there is a significant difference between WBS and NDS at the specific seed rate, according to Student’s <span class="html-italic">t</span>-test at α = 0.05 and 0.01, respectively.</p>
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<p>Root length density at anthesis at the 0–100 cm soil depth in the 2020–2021 and 2021–2022 growing seasons. * and ** indicate there is a significant difference between narrow-drill sowing (NDS) and wide-belt sowing (WBS) at the specific seed rate and soil layer, according to Student’s <span class="html-italic">t</span>-test at α = 0.05 and 0.01, respectively.</p>
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<p>The nodal roots per plant before winter at jointing and anthesis of winter wheat with narrow-drill sowing (NDS) and wide-belt sowing (WBS) in two growing seasons. Data are means and error bars are SEs (n = 4). * and ** indicate there is a significant difference between WBS and NDS at the specific seed rate, according to Student’s <span class="html-italic">t</span>-test at α = 0.05 and 0.01, respectively.</p>
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<p>The nodal roots per unit area before winter at jointing and anthesis of winter wheat with narrow-drill sowing (NDS) and wide-belt sowing (WBS) in two growing seasons. Data are means and error bars are SEs (n = 4). * and ** indicate there is a significant difference between WBS and NDS at the specific seed rate, according to Student’s <span class="html-italic">t</span>-test at α = 0.05 and 0.01, respectively.</p>
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<p>The relationship between differences in yield, N uptake, and root traits.</p>
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<p>Sketch maps of the sowing methods and root sampling at anthesis.</p>
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21 pages, 5788 KiB  
Article
Effect of Sowing Date on Some Agronomical Characteristics of Rye Cultivars in Iraq
by Dhurgham Sabeeh Kareem Altai, Ali H. Noaema, Ali R. Alhasany, Ágnes Hadházy, Nóra Mendler-Drienyovszki, Waleed A. E. Abido and Katalin Magyar-Tábori
Agronomy 2024, 14(9), 1995; https://doi.org/10.3390/agronomy14091995 - 2 Sep 2024
Viewed by 446
Abstract
The introduction of rye cultivation in Iraq necessitates the implementation of agrotechnological experiments. Two-year irrigated field experiments were carried out in Al-Muthanna Governorate (in the southwestern region of Iraq) in 2021/2022 and 2022/2023 to evaluate the performance of three European rye cultivars introduced [...] Read more.
The introduction of rye cultivation in Iraq necessitates the implementation of agrotechnological experiments. Two-year irrigated field experiments were carried out in Al-Muthanna Governorate (in the southwestern region of Iraq) in 2021/2022 and 2022/2023 to evaluate the performance of three European rye cultivars introduced to Iraq, focusing on the most significant agronomical and morphological characteristics. Three sowing dates (01 November, 15 November and 01 December) were tested in a split plot, randomized complete block design. We observed that both the cultivar and sowing date, but not the crop year, influenced the studied characteristics. In general, the early sowing dates enhanced the growth and development of rye and resulted in a higher yield compared to the later sowing dates. We observed that all evaluated rye cultivars can be grown safely in the agroclimatic and soil characteristics of this region. The grain yield was 3.1, 4.2 and 6.9 t ha−1 on average for all the sowing dates, and the above ground biomass results were 13.6, 12.0 and 22.9 on average for all sowing dates in ‘Krzyca’, ‘Dańkowskie złote’ and ‘Horyzo’, respectively. In addition, the highest grain yield (8.8 t ha−1) was harvested in ‘Horyzo’ when it was sown on 01 November; thus, we recommend choosing ‘Horyzo’ for cultivation in Iraq and sowing it in early November. Although further study is required to improve agro-technology (such as the nutrient supply) by using a larger number of cultivars, we can conclude that rye can be grown safely in Iraq under irrigated conditions. Full article
(This article belongs to the Special Issue Crop Biology and Breeding under Environmental Stress)
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<p>Location map of experimental site.</p>
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<p>Experimental plots of rye adaptation field experiments near the city of Al-Rumaitha (Al-Muthanna Governorate), in crop year 2021/2022 (<b>A</b>) and 2022/2023 (<b>B</b>).</p>
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<p>Effect of rye cultivar on the plant height (<b>A</b>); the flag leaf area (<b>B</b>); the number of spikes m<sup>−2</sup> (<b>C</b>); the number of grains per spike (<b>D</b>); the spike length (<b>E</b>); the thousand-grain weight (<b>F</b>); the total grain yield (<b>G</b>); the above ground biomass (<b>H</b>), and the harvest index (<b>I</b>). Each column shows the means of each cultivar with standard error (±SE) (the average of each sowing date). Different lowercase letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) in the means between cultivars according to the LSD.</p>
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<p>Effect of sowing date on the plant height (<b>A</b>); the flag leaf area (<b>B</b>); the number of spikes per m<sup>−2</sup> (<b>C</b>); the number of grains per spike (<b>D</b>); the spike length (<b>E</b>); the thousand-grain weight (<b>F</b>); the total grain yield (<b>G</b>); the above ground biomass (<b>H</b>), and the harvest Index (<b>I</b>). Each column shows the means ± SE of sowing date (the average of each cultivar). Different lowercase letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) in the means between sowing dates according to the LSD.</p>
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<p>Effect of cultivar and sowing date on the plant height (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cultivar and sowing date on the size of the flag leaf area (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cultivar and sowing date on the number of spikes m<sup>−2</sup> (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cultivar and sowing date on the number of grains per spike (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cultivar and sowing date on the length of spikes (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cultivar and sowing date on the thousand-grain weight (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cultivar and sowing date on the total grain yield (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cultivar and sowing date on the AGB (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cultivar and sowing date on the harvest index (mean ± SE). Different lowercase letters indicate significant differences between the means of plots sown on different dates (within the same cultivar), whereas capital letters indicate significant differences between the means of cultivars within the same sowing date (LSD Post Hoc Test; <span class="html-italic">p</span> &lt; 0.05).</p>
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13 pages, 2064 KiB  
Article
Flowering Periods, Seed Yield Components, Seed Quality, and Patterns of Seed Shattering in Paspalum: Effect of Taxonomy and Nitrogen Fertilization
by Luis Leandro Chamorro, Elsa Andrea Brugnoli, Alex Leonel Zilli, Roberto Ramón Schulz, Florencia Marcón and Carlos Alberto Acuña
Plants 2024, 13(17), 2411; https://doi.org/10.3390/plants13172411 - 29 Aug 2024
Viewed by 425
Abstract
Perennial warm-season grasses typically have reduced seed yield, making it essential to identify the critical seed yield components. An induced increase in nitrogen could help determine which components are most limiting. This research aimed to estimate seed yield components in Paspalum; evaluate [...] Read more.
Perennial warm-season grasses typically have reduced seed yield, making it essential to identify the critical seed yield components. An induced increase in nitrogen could help determine which components are most limiting. This research aimed to estimate seed yield components in Paspalum; evaluate N fertilization effects on the reproductive phase, seed yield components, and seed quality; and establish the pattern of seed shattering over time. Nine genotypes covering different reproductive periods were used. The experimental design was a randomized complete block design in a split-plot arrangement with three replications. The main plots had two nitrogen levels (0 and 150 Kg N ha−1), and the sub-plots contained different genotypes. Seed yield variation was mainly related to reproductive tiller density among germplasm with different flowering periods. Early-flowering germplasm showed an extended flowering period (159%), greater tiller density (27.7%), greater reproductive tiller density (157%), and higher yield (302%) in response to nitrogen fertilization. Seed-quality traits and seed retention were not affected by nitrogen fertilization. Seed retention over time followed an inverted sigmoid pattern, though there was considerable variation among taxonomic groups. Early-flowering germplasm exhibited superior seed retention. Seed yield in Paspalum is mainly influenced by the density of reproductive tillers and seed retention. Full article
(This article belongs to the Special Issue Tropical Forages)
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<p>Number of inflorescences per m<sup>2</sup> for 9 genotypes of <span class="html-italic">Paspalum</span> during the 2018–2019 growing season in Subtropical Argentina. Boy, C14, G37, and B7 belong to <span class="html-italic">P. notatum</span> (early flowering), and R93, U100, U44, A23, and B29 belong to the Plicatula Group (intermediate and late flowering).</p>
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<p>Effect of nitrogen fertilization (N 0–N 150: 0 and 150 Kg N ha<sup>−1</sup>) on the time to beginning and extent of flowering in a group of 9 <span class="html-italic">Paspalum</span> genotypes. Boy, C14, G37, and B7 belong to <span class="html-italic">P. notatum</span> (early flowering), and R93, U100, U44, A23, and B29 belong to the Plicatula Group (intermediate and late flowering). The stars indicate significant differences in the extent of the flowering period between nitrogen levels for each genotype (Tukey test (<span class="html-italic">p</span> ≤ 0.05)).</p>
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<p>Seed shattering over time for 9 <span class="html-italic">Paspalum</span> genotypes cultivated on nitrogen-fertilized and non-fertilized plots. Boy, C14, G37, and B7 belong to <span class="html-italic">P. notatum</span> (early flowering), and R93, U100, U44, A23, and B29 belong to the Plicatula Group (intermediate and late flowering). ES-150N: empty spikelets fertilized with 150 kg N, ES-0N: empty spikelets non-fertilized, FS-150N: full seed fertilized with 150 kg N, FS-0N: full seed non-fertilized.</p>
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<p>Seed retention over time in <span class="html-italic">Paspalum</span>. (<b>a</b>) Group of 4 genotypes of tetraploid <span class="html-italic">Paspalum notatum</span> (early flowering); (<b>b</b>) group of 5 tetraploid genotypes from the Plicatula Group (intermediate and late flowering).</p>
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<p>Principal component analysis (PCA) of 11 seed-related traits measured for 9 genotypes of <span class="html-italic">Paspalum</span> across two N-fertilization rates (0 and 150 Kg N ha<sup>−1</sup>). Boy, C14, G37, and B7 belong to <span class="html-italic">P. notatum</span> (early flowering), and R93, U100, U44, A23, and B29 belong to the Plicatula Group (intermediate and late flowering). Different colors represent different genotypes with different nitrogen levels, blue: 150 kg ha<sup>−1</sup>, green: 0 kg ha<sup>−1</sup>. Measured traits were %SS: percentage of seed set, FP: flowering period, F/I: N° flowers/inflorescence, T/m<sup>2</sup>: N° tillers per m<sup>2</sup>, RT/m<sup>2</sup>: reproductive tiller per m<sup>2</sup>, VT/m<sup>2</sup>: vegetative tillers per m<sup>2</sup>; SY: seed yield, NS/m<sup>2</sup>: N° of seeds per m<sup>2</sup>, SW: seed width, SL: seed length, 1000 SW: 1000 seed weight.</p>
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<p>Proportion of reproductive tillers for a group of 9 <span class="html-italic">Paspalum</span> genotypes under two nitrogen fertilization levels, 0 (N 0) and 150 (N 150) kg N ha<sup>−1</sup>. Boy, C14, G37, and B7 belong to <span class="html-italic">P. notatum</span> (early flowering), and R93, U100, U44, A23, and B29 belong to the Plicatula Group (intermediate and late flowering). Bars represent the standard error.</p>
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<p>Registered rainfall and temperatures in the experimental site in Corrientes, Argentina (27°28′ S, 58°47′ W) during the evaluation period.</p>
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12 pages, 1758 KiB  
Article
Supplemental Irrigation with Recycled Drainage Water: Outcomes for Corn and Soybean in a Fine-Textured Soil
by Ali R. Niaghi, Axel Garcia y Garcia and Jeffrey S. Strock
Agronomy 2024, 14(9), 1948; https://doi.org/10.3390/agronomy14091948 - 29 Aug 2024
Viewed by 533
Abstract
Drought and heavier spring storms from climate change will increase crop water stress and affect productivity. A study was conducted to determine whether supplemental irrigation on fine-textured soils with recycled drainage and surface runoff water, combined with nitrogen (N) management, could mitigate these [...] Read more.
Drought and heavier spring storms from climate change will increase crop water stress and affect productivity. A study was conducted to determine whether supplemental irrigation on fine-textured soils with recycled drainage and surface runoff water, combined with nitrogen (N) management, could mitigate these effects. This study was set as a randomized complete block design in a split-plot arrangement with three replicates. The main plots, which were individually drained, corresponded to three water management strategies (full irrigation, limited irrigation, and rainfed), and the subplots corresponded to six N rates (0, 90, 134, 179, 224, and 269 kg/ha) in the corn phase of the rotation. In the soybean phase, the same water management strategies were uniformly applied across the subplots. Irrigation and drainage water, volumetric soil water content (SWC), and grain yield data were collected. The full irrigation significantly increased the SWC in the top 60 cm of the soil across crops during the driest year, where it increased by an average of 30% compared with the rainfed conditions. The limited irrigation increased the SWC in the top 20 cm only for the soybean during the driest year, where it increased by as much as 25%. As a result, the supplemental irrigation prevented yield reduction in one year. While the irrigation alone did not significantly affect the grain yield of either crop, the irrigation × N interaction for the corn was consistently significant, which suggests that the N effectively enhanced the corn productivity. The results suggest that reusing drainage water could be a valuable practice for reducing the effects of limited soil water on crops in fine-textured soils. Full article
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<p>(<b>a</b>) Experimental site and (<b>b</b>) plots and subplots design.</p>
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<p>Average monthly volumetric soil water content (SWC) in the 30–60 cm layer for the full, limited, and rainfed condition during the 2016 and 2017 growing seasons.</p>
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<p>Average monthly drainage flow from each irrigation treatment during study years. Graph captions represent year and month, for example, 2016:07 represents July 2016.</p>
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<p>Effect of irrigation × nitrogen (N) on yield of corn and irrigation on soybean yield in 2016 and 2017 growing seasons. Values in boxes denote significant (blue) and not significant (red) percent difference on yield at α = 0.05. Full irrigation (F), limited irrigation (L; 50% F), and rainfed (R) conditions.</p>
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22 pages, 4922 KiB  
Article
Biomass Partitioning, Carbon Storage, and Pea (Pisum sativum L.) Crop Production under a Grewia optiva-Based Agroforestry System in the Mid-Hills of the Northwestern Himalayas
by Alisha Keprate, Daulat Ram Bhardwaj, Prashant Sharma, Dhirender Kumar and Rajesh Kumar Rana
Sustainability 2024, 16(17), 7438; https://doi.org/10.3390/su16177438 - 28 Aug 2024
Viewed by 581
Abstract
A well-designed tree-based culture provides multiple benefits, aiding in achieving sustainable development goals (SDGs), especially SDG1 (no poverty), SDG2 (zero hunger), SDG13 (climate action), and SDG15 (life on land). A split-plot field experiment near Solan, Himachal Pradesh, tested the following Grewia optiva tree [...] Read more.
A well-designed tree-based culture provides multiple benefits, aiding in achieving sustainable development goals (SDGs), especially SDG1 (no poverty), SDG2 (zero hunger), SDG13 (climate action), and SDG15 (life on land). A split-plot field experiment near Solan, Himachal Pradesh, tested the following Grewia optiva tree spacings as main plots: S1 10 m × 1 m, S2 10 m × 2 m, S3 10 m × 3 m, and sole cropping (S0—Open) of pea (Pisum sativum L.). Pea cultivation included the following six fertilizer treatments as subplots: control (no application), farmyard manure (FYM), vermicompost (VC), Jeevamrut, FYM + VC, and the recommended dose of fertilizers (RDFs), each replicated three times. The results indicated that the leaves, branches, total biomass, carbon density, and carbon sequestration rate of G. optiva alleys at 10 m × 1 m were greater than those at the other spacings. However, peas intercropped at 10 m × 3 m produced the highest yield (5.72 t ha−1). Compared with monocropping, G. optiva-based agroforestry significantly improved soil properties. Among fertilizers, FYM had the highest yield (6.04 t ha−1) and improved soil health. The most lucrative practice was the use of peas under a 10 m × 1 m spacing with FYM, with economic gains of 2046.1 USD ha−1. This study suggests integrating pea intercropping with G. optiva at broader spacing (10 m × 3 m) and using FYM for optimal carbon sequestration, soil health, and economic returns, and this approach is recommended for the region’s agroecosystems. Full article
(This article belongs to the Section Sustainable Agriculture)
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<p>Representation of the experimental layout showing the planting design of pea in a <span class="html-italic">G. optiva</span>-based agroforestry system under different spacings: (<b>a</b>) S<sub>1</sub>—10 m × 1 m, (<b>b</b>) S<sub>2</sub>—10 m × 2 m, (<b>c</b>) S<sub>3</sub>—10 m × 3 m.</p>
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<p>Photosynthetic active radiation (μmol m<sup>−2</sup> s<sup>−1</sup>) of different grewia-based agroforestry systems and monocropping systems during the experimental period. Here, S<sub>0</sub>—sole cropping; tree spacing—S<sub>1</sub> (10 m × 1 m), S<sub>2</sub> (10 m × 2 m), S<sub>3</sub> (10 m × 3 m).</p>
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<p>Available chemical nutrients in the soil for different tree densities and fertilization treatments: (<b>a</b>) nitrogen (kg ha<sup>−1</sup>), (<b>b</b>) phosphorous (kg ha<sup>−1</sup>), and (<b>c</b>) potassium (kg ha<sup>−1</sup>). Here, S<sub>0</sub>—sole cropping; tree spacing—S<sub>1</sub> (10 m × 1 m), S<sub>2</sub> (10 m × 2 m), S<sub>3</sub> (10 m × 3 m); fertilizer treatment—T<sub>0</sub>—control; T<sub>1</sub>—farmyard manure; T<sub>2</sub>—vermicompost (VC); T<sub>3</sub>−jeevamrut; T<sub>4</sub>—farmyard manure + vermicompost; T<sub>5</sub>—recommended dose of fertilizer. The values carrying different alphabetical superscripts (<sup>a</sup>, <sup>b</sup>, <sup>c</sup>, <sup>d</sup>, etc.) for the bars above differ significantly among themselves (<span class="html-italic">p</span> &lt; 0.05). The error bars indicate the standard deviation.</p>
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<p>Available chemical nutrients in the soil for different tree densities and fertilization treatments: (<b>a</b>) nitrogen (kg ha<sup>−1</sup>), (<b>b</b>) phosphorous (kg ha<sup>−1</sup>), and (<b>c</b>) potassium (kg ha<sup>−1</sup>). Here, S<sub>0</sub>—sole cropping; tree spacing—S<sub>1</sub> (10 m × 1 m), S<sub>2</sub> (10 m × 2 m), S<sub>3</sub> (10 m × 3 m); fertilizer treatment—T<sub>0</sub>—control; T<sub>1</sub>—farmyard manure; T<sub>2</sub>—vermicompost (VC); T<sub>3</sub>−jeevamrut; T<sub>4</sub>—farmyard manure + vermicompost; T<sub>5</sub>—recommended dose of fertilizer. The values carrying different alphabetical superscripts (<sup>a</sup>, <sup>b</sup>, <sup>c</sup>, <sup>d</sup>, etc.) for the bars above differ significantly among themselves (<span class="html-italic">p</span> &lt; 0.05). The error bars indicate the standard deviation.</p>
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<p>Available chemical nutrients in the soil for different tree densities and fertilization treatments: (<b>a</b>) nitrogen (kg ha<sup>−1</sup>), (<b>b</b>) phosphorous (kg ha<sup>−1</sup>), and (<b>c</b>) potassium (kg ha<sup>−1</sup>). Here, S<sub>0</sub>—sole cropping; tree spacing—S<sub>1</sub> (10 m × 1 m), S<sub>2</sub> (10 m × 2 m), S<sub>3</sub> (10 m × 3 m); fertilizer treatment—T<sub>0</sub>—control; T<sub>1</sub>—farmyard manure; T<sub>2</sub>—vermicompost (VC); T<sub>3</sub>−jeevamrut; T<sub>4</sub>—farmyard manure + vermicompost; T<sub>5</sub>—recommended dose of fertilizer. The values carrying different alphabetical superscripts (<sup>a</sup>, <sup>b</sup>, <sup>c</sup>, <sup>d</sup>, etc.) for the bars above differ significantly among themselves (<span class="html-italic">p</span> &lt; 0.05). The error bars indicate the standard deviation.</p>
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<p>Bioeconomic evaluation of <span class="html-italic">G. optiva</span>-based agroforestry systems. Here, S<sub>0</sub>—sole cropping; tree spacing—S<sub>1</sub> (10 m × 1 m), S<sub>2</sub> (10 m × 2 m), S<sub>3</sub> (10 m × 3 m); fertilizer treatment—T<sub>0</sub> —control; T<sub>1</sub>—farmyard manure; T<sub>2</sub>—vermicompost (VC); T<sub>3</sub>—jeevamrut; T<sub>4</sub>—farmyard manure + vermicompost; T<sub>5</sub>—recommended dose of fertilizer.</p>
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23 pages, 1795 KiB  
Article
The Effects of Nitrogen Application and Varietal Variation on the Product Quality and In Vitro Bioaccessibility of Bioactive Compounds of Baby Spinach Varieties Grown in a Soilless Growth Medium
by Nhlanzeko Mbalenhle Bhengu, Sephora Mutombo Mianda, Martin Makgose Maboko and Dharini Sivakumar
Foods 2024, 13(17), 2667; https://doi.org/10.3390/foods13172667 - 24 Aug 2024
Viewed by 661
Abstract
Baby spinach is becoming increasingly popular as a salad ingredient and needs high fertiliser rates to grow well and attain higher-quality leaves (dark green leaves). Chemical fertilisers, especially nitrogen (N), boost yields. There are many risks associated with nitrogen fertilisation. Additionally, spinach contains [...] Read more.
Baby spinach is becoming increasingly popular as a salad ingredient and needs high fertiliser rates to grow well and attain higher-quality leaves (dark green leaves). Chemical fertilisers, especially nitrogen (N), boost yields. There are many risks associated with nitrogen fertilisation. Additionally, spinach contains phenolic compounds and carotenoids. Nitrogen fertilisation affects growth, development, yield and metabolites. This study examined the impact of lower concentrations of N (0, 30, 60, 90, 120, 150 mg/L) on yield and colour properties [light intensity (L*) colour coordinates, unique for green colour (a*) and yellow colour (b*)], as well as the impact of varying N concentrations on the total phenolic content and p-coumaric acid, quercetin, ferulic acid, kaempferol, lutein, zeaxanthin, β-carotene and antioxidant activities in the baby spinach varieties ‘Acadia’, ‘Crosstrek’ and ‘Traverse’, and it was established that N fertilisation improves phytochemical bioaccessibility and antioxidant activity. In a split strip plot design, three baby spinach varieties were treated with different N concentrations, including 0, 30, 60, 90, 120 and 150 mg/L. For 40 days, three baby spinach varieties were grown on soilless Mikskaar Professional substrate 300. During both seasons, ’Crosstrek’ had the highest fresh mass (921.4 g/m2, 856.3 g/m2) at 120 mg/L N, while ‘Traverse’ had the highest fresh mass at 554.8 g/m2 and at 564.3 g/m2 at 90 mg/L N and did not differ significantly from 90 to 150 mg/L N during either season. During both seasons, ‘Acadia’ at 90 mg/L N increased fresh mass to 599 g/m2 and 557.9 g/m2. The variety × N supply interaction significantly affected the leaf colour; chlorophyll content across seasons; the levels of bioactive compounds, p-coumaric acid, quercetin, ferulic acid, kaempferol, lutein, zeaxanthin and β-carotene in spinach varieties; the in vitro bioaccessibility; and the antioxidant activity. Varietal differences influenced the bioaccessibility of phenolic compounds and carotenoid components. The appropriate N levels can be used during plant cultivation to optimise the bioaccessibility of this spinach variety. Thus, fertilising ‘Traverse’ with 90 mg/N mL increased the in vitro bioaccessibility of β-carotene (35.2%), p-coumaric acid (7.13%), quercetin (8.29%) and ferulic acid (1.92%) without compromising the yield. Full article
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<p>An unsupervised PCA scores plot of phenolic and carotenoid metabolites obtained via the HPLC-UV analysis of three spinach varieties and different nitrogen supplies. ‘Acadia’ (A), ‘Crosstrek’ (C) and ‘Traverse’ (T) were treated with different N concentrations including 0, 30, 60, 90, 120 and 150 mg/L.</p>
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<p>VIP scores in PLS-DA assigned to phenolic and carotenoid compounds found in baby spinach cultivars grown with different N concentration levels. ‘Acadia’ (A), ‘Crosstrek’ (C) and ‘Traverse’ (T) were treated with different N concentrations including 0, 30, 60, 90, 120 and 150 mg/L.</p>
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<p>Heat map showing the phenolic and carotenoid compounds found in different baby spinach varieties grown with different nitrogen concentration levels. The rows represent the compounds, and the columns represent the spinach varieties at different N concentrations. The colours red and blue indicate high and low levels, respectively. ‘Acadia’ (A), ‘Crosstrek’ (C) and ‘Traverse’ (T) were treated with different N concentrations including 0, 30, 60, 90, 120 and 150 mg/L.</p>
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20 pages, 1671 KiB  
Article
Optimizing Maize Productivity and Soil Fertility: Insights from Tillage, Nitrogen Management, and Hydrochar Applications
by Waleed Iqbal, Ahmad Khan, Aftab Jamal, Emanuele Radicetti, Mohamed Farouk Elsadek, Mohammad Ajmal Ali and Roberto Mancinelli
Land 2024, 13(8), 1329; https://doi.org/10.3390/land13081329 - 22 Aug 2024
Viewed by 585
Abstract
Enhancing soil fertility and maize productivity is crucial for sustainable agriculture. This study aimed to evaluate the effects of tillage practices, nitrogen management strategies, and acidified hydrochar on soil fertility and maize productivity. The experiment used a randomized complete block design with split-split [...] Read more.
Enhancing soil fertility and maize productivity is crucial for sustainable agriculture. This study aimed to evaluate the effects of tillage practices, nitrogen management strategies, and acidified hydrochar on soil fertility and maize productivity. The experiment used a randomized complete block design with split-split plot arrangement and four replications. Main plots received shallow tillage and deep tillage. Subplots were treated with nitrogen (120 kg ha−1) from farmyard manure (FYM) and urea, including control, 33% FYM + 67% urea (MU), and 80% FYM + 20% urea (MF). Acidified hydrochar treatments H0 (no hydrochar) and H1 (with hydrochar, 2 t ha−1) were applied to sub-sub plots. Deep tillage significantly increased plant height, biological yield, grain yield, ear length, grains ear−1, thousand-grain weight, and nitrogen content compared to shallow tillage. MU and MF improved growth parameters and yield over the control. Hydrochar effects varied; H1 enhanced yield components and soil properties such as soil organic matter and nitrogen availability compared to H0. Canonical discriminant analysis linked deep tillage and MU/MF nitrogen management with improved yield and soil characteristics. In conclusion, deep tillage combined with integrated nitrogen management enhances maize productivity and soil properties. These findings highlight the importance of selecting appropriate tillage and nitrogen strategies for sustainable maize production along with hydrochar addition. These insights guide policymakers, agronomists, and agricultural extension services in adopting evidence-based strategies for sustainable agriculture, enhancing food production, and mitigating environmental impacts. The implication of this study suggests to undertake long-term application of hydrochar for further clarification and validation. Full article
(This article belongs to the Special Issue Tillage Methods on Soil Properties and Crop Growth)
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<p>Rainfall (mm), temperature maximum (°C) and minimum (°C) at the experimental site during the growing season of maize.</p>
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<p>The main effect of tillage practices, nitrogen management, and hydrochar application on Chl a, Chl b, Total Chlorophyll and total carotenoids content in the flag leaves of maize plants at flowering stage, respectively. S<sub>T</sub> = shallow tillage; D<sub>T</sub> = deep tillage; M<sub>C</sub> = control; M<sub>U</sub> = 33% FYM + 67% Urea; M<sub>F</sub> = 80% FYM + 20% Urea; H<sub>0</sub> = control (no hydrochar); and H<sub>1</sub> = acidified hydrochar. The data represent means of four replicates. Means with different letters indicate statistically significant differences at <span class="html-italic">p</span> &lt; 0.05. Error bars denote standard deviation.</p>
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<p>The effect of tillage practice × nitrogen management interaction and hydrochar application on organic matter, total nitrogen, and mineral nitrogen of soil cultivated with maize crop at harvesting. S<sub>T</sub> = shallow tillage; D<sub>T</sub> = deep tillage; M<sub>C</sub> = control; M<sub>U</sub> = 33% FYM + 67% Urea; M<sub>F</sub> = 80% FYM + 20% Urea; H<sub>0</sub> = control (no hydrochar); and H<sub>1</sub> = acidified hydrochar. The data represent means of four replicates. Means with different letters indicate statistically significant differences at <span class="html-italic">p</span> &lt; 0.05. Error bars denote standard deviation.</p>
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<p>The relationships between Nitrogen Use Efficiency (NUE) and N uptake of maize plants against soil organic matter, total maize leaves’ chlorophyll and soil mineral nitrogen (n = 48), respectively. Data correspond to tillage practices, nitrogen management, and hydrochar application and the significance level is * and ** significant at <span class="html-italic">p</span> ≤ 0.05 and <span class="html-italic">p</span> ≤ 0.01 level, respectively.</p>
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<p>The canonical discriminant analysis (CDA) of the yield characteristics of maize subjected to tillage practices (<b>A</b>), nitrogen management (<b>B</b>), and hydrochar application (<b>C</b>). S<sub>T</sub> = shallow tillage; D<sub>T</sub> = deep tillage; M<sub>C</sub> = control; M<sub>U</sub> = 33% FYM + 67% Urea; M<sub>F</sub> = 80% FYM + 20% Urea; H<sub>0</sub> = control (no hydrochar); and H<sub>1</sub> = acidified hydrochar.</p>
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<p>The canonical discriminant analysis (CDA) of soil characteristics of maize subjected to tillage practices (<b>A</b>), nitrogen management (<b>B</b>), and hydrochar application (<b>C</b>). S<sub>T</sub> = Shallow tillage; D<sub>T</sub> = deep tillage; M<sub>C</sub> = control; M<sub>U</sub> = 33% FYM + 67% Urea; M<sub>F</sub> = 80% FYM + 20% Urea; H<sub>0</sub> = control (no hydrochar); and H<sub>1</sub> = acidified hydrochar.</p>
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20 pages, 3524 KiB  
Article
Can Rice Growth Substrate Substitute Rapeseed Growth Substrate in Rapeseed Blanket Seedling Technology? Lesson from Reactive Oxygen Species Production and Scavenging Analysis
by Kaige Yi, Yun Ren, Hui Zhang, Baogang Lin, Pengfei Hao and Shuijin Hua
Antioxidants 2024, 13(8), 1022; https://doi.org/10.3390/antiox13081022 - 22 Aug 2024
Viewed by 651
Abstract
Rapeseed (Brassica napus L.) seedlings suffering from inappropriate growth substrate stress will present poor seedling quality. However, the regulatory mechanism for the production and scavenging of reactive oxygen species (ROS) caused by this type of stress remains unclear. In the current study, [...] Read more.
Rapeseed (Brassica napus L.) seedlings suffering from inappropriate growth substrate stress will present poor seedling quality. However, the regulatory mechanism for the production and scavenging of reactive oxygen species (ROS) caused by this type of stress remains unclear. In the current study, a split plot experiment design was implemented with two crop growth substrates—a rice growth substrate (RIS) and rapeseed growth substrate (RAS)—as the main plot and two genotypes—a hybrid and an open-pollinated variety (Zheyouza 1510 and Zheyou 51, respectively)—as the sub-plot. The seedling quality was assessed, and the ROS production/scavenging capacity was evaluated. Enzymatic and non-enzymatic systems, including ascorbic acid and glutathione metabolism, and RNA-seq data were analyzed under the two growth substrate treatments. The results revealed that rapeseed seedling quality decreased under RIS, with the plant height, maximum leaf length and width, and aboveground dry matter being reduced by 187.7%, 64.6%, 73.2%, and 63.8% on average, respectively, as compared to RAS. The main type of ROS accumulated in rapeseed plants was hydrogen peroxide, which was 47.8% and 14.1% higher under RIS than under RAS in the two genotypes, respectively. The scavenging of hydrogen peroxide in Zheyouza 1510 was the result of a combination of enzymatic systems, with significantly higher peroxidase (POD) and catalase (CAT) activity as well as glutathione metabolism, with significantly higher reduced glutathione (GSH) content, under RAS, while higher oxidized glutathione (GSSH) was observed under RIS. However, the scavenging of hydrogen peroxide in Zheyou 51 was the result of a combination of elevated oxidized ascorbic acid (DHA) under RIS and higher GSH content under RAS. The identified gene expression levels were in accordance with the observed enzyme expression levels. The results suggest that the cost of substituting RAS with RIS is a reduction in rapeseed seedling quality contributing to excessive ROS production and a reduction in ROS scavenging capacity. Full article
(This article belongs to the Section ROS, RNS and RSS)
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<p>Phenotype of blanket rapeseed seedlings at 30 d old: Zheyouza 1510 and Zheyou 51 varieties under rice growth substrate (RIS) and rapeseed growth substrate (RAS) in the red box.</p>
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<p>ROS production under rice and rapeseed growth substrates in Zheyouza 1510 and Zheyou 51 and the correlations between ROS contents and seedling quality: (<b>A</b>) hydrogen peroxide; (<b>B</b>) superoxide anions; and (<b>C</b>) Pearson’s correlation coefficients between ROS and seedling quality. Different lowercase letters indicate a significant difference among treatments using Duncan’s method (<span class="html-italic">p</span> &lt; 0.05). “*” indicates a significant difference at <span class="html-italic">p</span> &lt; 0.05. Error bars indicate the standard deviation (SD) values.</p>
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<p>ROS scavenging capacity under rice growth substrate and rapeseed growth substrate in Zheyouza 1510 and Zheyou 51: (<b>A</b>) hydroxyl free radical scavenging capacity (HFRS); (<b>B</b>) superoxide peroxide anion scavenging capacity (SOAS); and (<b>C</b>) total antioxidant capacity (T-AOC). Different lowercase letters indicate significant difference among treatments using Duncan’s method (<span class="html-italic">p</span> &lt; 0.05). Error bars indicate standard deviation (SD) values.</p>
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<p>Alteration of enzyme activities in rapeseed leaves under rice growth substrate and rapeseed growth substrate in Zheyouza 1510 and Zheyou 51: (<b>A</b>) superoxide dismutase (SOD); (<b>B</b>) peroxidase (POD); and (<b>C</b>) catalase (CAT). Different lowercase letters indicate significant difference among treatments using Duncan’s method (<span class="html-italic">p</span> &lt; 0.05). Error bars indicate standard deviation (SD) values.</p>
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<p>Analysis of ascorbic acid metabolism in rapeseed leaves under rice growth substrate (RIS) and rapeseed growth substrate (RAS) in Zheyouza 1510 and Zheyou 51: (<b>A</b>) reduced ascorbic acid (AsA); (<b>B</b>) oxidized ascorbic acid (DHA); (<b>C</b>) dehydroascorbate reductase (DHAR); (<b>D</b>) monodehydroascorbate reductase (MDHAR); (<b>E</b>) ascorbic acid oxidase (AAO); (<b>F</b>) ascorbate peroxidase (APX); and (<b>G</b>) L-galactose-1,4-lactone dehydrogenase (Gal LDH). Different lowercase letters indicate significant difference among treatments using Duncan’s method (<span class="html-italic">p</span> &lt; 0.05). Error bars indicate standard deviation (SD) values.</p>
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<p>Analysis of ascorbic acid metabolism in rapeseed leaves under rice growth substrate (RIS) and rapeseed growth substrate (RAS) in Zheyouza 1510 and Zheyou 51: (<b>A</b>) reduced ascorbic acid (AsA); (<b>B</b>) oxidized ascorbic acid (DHA); (<b>C</b>) dehydroascorbate reductase (DHAR); (<b>D</b>) monodehydroascorbate reductase (MDHAR); (<b>E</b>) ascorbic acid oxidase (AAO); (<b>F</b>) ascorbate peroxidase (APX); and (<b>G</b>) L-galactose-1,4-lactone dehydrogenase (Gal LDH). Different lowercase letters indicate significant difference among treatments using Duncan’s method (<span class="html-italic">p</span> &lt; 0.05). Error bars indicate standard deviation (SD) values.</p>
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<p>Analysis of glutathione metabolism in rapeseed leaves under rice growth substrate (RIS) and rapeseed growth substrate (RAS) in Zheyouza 1510 and Zheyou 51: (<b>A</b>) reduced glutathione (GSH); (<b>B</b>) oxidized glutathione (GSSG); (<b>C</b>) glutathione peroxidase (GPX); (<b>D</b>) glutathione reductase (GR); (<b>E</b>) glutathione-S-transferase (GST); (<b>F</b>) thioredoxin peroxidase (TPX); (<b>G</b>) glutamate cysteine ligase (GCL); and (<b>H</b>) total sulfhydryls (TSHs). Different lowercase letters indicate significant difference among treatments using Duncan’s method (<span class="html-italic">p</span> &lt; 0.05). Error bars indicate standard deviation (SD) values.</p>
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<p>Analysis of glutathione metabolism in rapeseed leaves under rice growth substrate (RIS) and rapeseed growth substrate (RAS) in Zheyouza 1510 and Zheyou 51: (<b>A</b>) reduced glutathione (GSH); (<b>B</b>) oxidized glutathione (GSSG); (<b>C</b>) glutathione peroxidase (GPX); (<b>D</b>) glutathione reductase (GR); (<b>E</b>) glutathione-S-transferase (GST); (<b>F</b>) thioredoxin peroxidase (TPX); (<b>G</b>) glutamate cysteine ligase (GCL); and (<b>H</b>) total sulfhydryls (TSHs). Different lowercase letters indicate significant difference among treatments using Duncan’s method (<span class="html-italic">p</span> &lt; 0.05). Error bars indicate standard deviation (SD) values.</p>
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<p>RNA-seq analysis on effects of rice growth substrate (RIS) and rapeseed growth substrate (RAS) on seedling quality in Zheyouza 1510: (<b>A</b>) volcano plot of differentially expressed genes under two crop growth substrates; (<b>B</b>) KEGG analysis of differentially expressed genes under two crop growth substrates; (<b>C</b>) identified genes in enzymatic and non-enzymatic systems for ROS scavenging; and (<b>D</b>) correlation analysis between expression levels of selected genes via RNA-seq and qRT-PCR.</p>
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18 pages, 12379 KiB  
Article
Optimizing Wheat Planting Density by Adjusting Population Structure and Stabilizing Stem Strength to Achieve High and Stable Yields
by Suwei Feng, Chenchen Shi, Peiyu Wang, Sujing Chang, Chaoyang Liu, Chenwei Shen, Shilong Li, Tiezhu Hu and Zhengang Ru
Agronomy 2024, 14(8), 1853; https://doi.org/10.3390/agronomy14081853 - 21 Aug 2024
Viewed by 434
Abstract
Increasing wheat (Triticum aestivum L.) planting density is the most effective production management method for increasing yields; however, excessive crop populations under high planting densities may experience elevated risk of stem lodging. We conducted this study to assess the relationship between reduced [...] Read more.
Increasing wheat (Triticum aestivum L.) planting density is the most effective production management method for increasing yields; however, excessive crop populations under high planting densities may experience elevated risk of stem lodging. We conducted this study to assess the relationship between reduced lodging and increased yield, investigate the effects of planting density on wheat population structure, stem strength, and material transport, and provide a basis for rationale planting densities. The experiments were carried out using a split-plot design with three replicates. The main plots contained two wheat varieties: Bainong 5819 (BN5819) and Bainong 4199 (BN4199), and the sub-plots contained four planting density treatments: 90 × 104 plants/ha (D1), 180 × 104 plants/ha (D2), 270 × 104 plants/ha (D3), and 360 × 104 plants/ha (D4). A two-year field trial was conducted in 2021–2023. The relationships between population structure characteristics, changes in stem strength, activation, and retransport of stem material after anthesis, and achievement of high and stable yields were investigated at the different planting densities. When the planting density of wheat increased from D1 to D4 treatment, the activity of fructan hydrolase was significantly increased. Compared with D1 treatment, the highest activity of fructan hydrolase was increased by 457.47 μg/h/g under D4 treatment. At the same time, the increase of density also increased the contribution rate of dry matter accumulation (CDMA) to grain after anthesis increased, with the highest increase in CDMA at 33.67%, which significantly reduced stem strength. Correlation analysis revealed a significant negative association between CDMA and stem strength. Specifically, CDMA levels were significantly lower with the D3 treatment than the D4 treatment, while stem strength remained higher after anthesis as an adaptive response to mitigate lodging risk. Stem storage compounds can promote grain filling and a weight increase in inferior grains. The number of spikes per unit area increased significantly with increasing planting density, but the number of grains per spike and 1000-grain weight decreased significantly. In two years, the number of spikes in D3 treatment increased by a maximum of 211.67 × 104 ha−1 and 99.17 × 104 ha−1, respectively, compared to D1 and D2 treatments. The number of grains per spike was significantly higher than that of D4 treatment, the highest being 3.68 grains. Therefore, in the North China Plain with suitable water, fertilizer, and temperature, the sowing density of 270 × 104 plants/ha established population structure, significantly reduced CDMA, maintained post-anthesis stem strength, enhanced resilience of stems against post-anthesis lodging, and resulted in high yields by stabilizing the number of grains per spike and increasing the number of wheat spikes. Full article
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<p>Weather data during 2021−2022 and 2022−2023 wheat growing seasons. The figure shows monthly average maximum and minimum air temperature (°C) and monthly precipitation (mm).</p>
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<p>Dynamic changes of basal stem strength in wheat after anthesis under BN5819 and BN4199 varieties and four planting densities from 2021 to 2023. Error bars are standard errors. Values within a column followed by different letters are significantly different among different treatments (<span class="html-italic">p</span> &lt; 0.05). The order of the letters in the same column from top to bottom is consistent with the change of line segments from top to bottom. The same as below.</p>
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<p>The contribution rate of dry matter accumulation to the grain (CDMA) after anthesis at different varieties and planting densities during wheat maturation in 2021–2023. D1, D2, D3, and D4, respectively, indicated that the planting density of wheat was 90 × 10<sup>4</sup> plants/ha, 180 × 10<sup>4</sup> plants/ha, 270 × 10<sup>4</sup> plants/ha, and 360 × 10<sup>4</sup> plants/ha. Error bars are standard errors. Values within a column followed by different letters are significantly different among different treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>From 2021 to 2023, the <sup>13</sup>C assimilate accumulation amount of superior and inferior wheat grains per unit mass at maturity stage, with different lowercase letters in the same column indicating significant difference between the same varieties and different seeding densities at maturity stage (<span class="html-italic">p</span> &lt; 0.05). Error bars are standard errors.</p>
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<p>In 2021–2023, the activity of fructan hydrolase in wheat stems under different varieties and planting density treatments at anthesis stage. D1, D2, D3, and D4, respectively, indicated that the planting density of wheat was 90 × 10<sup>4</sup> plants/ha, 180 × 10<sup>4</sup> plants/ha, 270 × 10<sup>4</sup> plants/ha, and 360 × 10<sup>4</sup> plants/ha. The same row of different lowercase letters indicates that there were significant differences between the same variety and different planting density treatments at anthesis stage (<span class="html-italic">p</span> &lt; 0.05). Error bars are standard errors.</p>
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<p>In 2021–2023, the dynamic changes of superior grain filling rate of winter wheat under different varieties and planting density treatments; D1, D2, D3, and D4 indicate that the planting density of wheat was 90 × 10<sup>4</sup> plants/ha, 180 × 10<sup>4</sup> plants/ha, 270 × 10<sup>4</sup> plants/ha, and 360 × 10<sup>4</sup> plants/ha, respectively. Error bars are standard errors. Values within a column followed by different letters are significantly different among different treatments (<span class="html-italic">p</span> &lt; 0.05). The order of the letters in the same column from top to bottom is consistent with the change of line segments from top to bottom.</p>
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<p>In 2021–2023, the dynamic changes of inferior grain filling rate of winter wheat under different varieties and planting density treatments; D1, D2, D3, and D4 indicated that the planting density of wheat was 90 × 10<sup>4</sup> plants/ha, 180 × 10<sup>4</sup> plants/ha, 270 × 10<sup>4</sup> plants/ha, and 360 × 10<sup>4</sup> plants/ha, respectively. Error bars are standard errors. Values within a column followed by different letters are significantly different among different treatments (<span class="html-italic">p</span> &lt; 0.05). The order of the letters in the same column from top to bottom is consistent with the change of line segments from top to bottom.</p>
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<p>Correlation of grain yield, panicle number, thousand grain weight, CDMA, stem strength at anthesis stage, and fructan hydrolase activity at anthesis stage under different varieties and planting density treatments in 2021–2023. r stands for Pearson correlation coefficient; ** indicates the significance of difference when <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Schematic diagram of optimizing wheat planting density to achieve high and stable yield by coordinating grain composition factors and increasing stem strength. ** indicates the significance of difference when <span class="html-italic">p</span> &lt; 0.01.</p>
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