Search Results (11,667)

During storage, infestation by insect pests occurs, causing quantitative and qualitative losses in grains, which requires the control of these insects with phosphine gas. Rice husk has a high phosphine adsorption capacity, influencing the gas concentration during fumigation and potentially leading to inefficient fumigation. Additionally, the high sorption of rice husk results in a higher residue of phosphine in the grain. Therefore, the objective of this study was to evaluate the phosphine sorption and phosphine residue in rice husk, paddy rice, and brown rice, as well as the industrial quality (head rice yield, rehydration capacity, cooking time, colorimetric profile) of brown and white rice during storage. To achieve this, fumigation of paddy rice, brown rice, and rice husks with 3.0 g·m⁻³ of phosphine was carried out for 240 h (recommended duration in the industry). A high sorption rate was observed in the rice husk (94.77%), paddy rice (97.61%), and, lastly, brown rice (35.17%). Due to the high sorption rate, only brown rice maintained a concentration above the recommended level for effective pest control (400 ppm for 120 h). Higher phosphine residues than permitted were observed in the rice husk (0.25 ppm). Lower rice head yields were observed in non-fumigated rice samples when analyzing the brown rice samples (66.21% for paddy rice and 65.01% for brown rice). A greater rehydration capacity was observed in fumigated samples at the beginning of storage when analyzing the brown rice samples (1.21 for paddy rice, 1.23 for brown rice), reducing the cooking time (24.00 for paddy rice, 23.80 for brown rice). More studies should be carried out to evaluate the effectiveness of fumigation on paddy rice, considering the high sorption rate of the paddy. Full article

The prediction of crop growth and nitrogen status is essential for agricultural development and food security under climate change scenarios. Crop models are powerful tools for simulating crop growth and their responses to environmental variables, but accurately capturing the dynamic changes in crop nitrogen remains a considerable challenge. Data assimilation can reduce uncertainties in crop models by integrating observations with model simulations. However, current data assimilation research is primarily focused on a limited number of observational variables, and insufficiently utilizes nitrogen observations. To address these challenges, this study developed a new multivariable data assimilation system, ORYZA-EnKF, that is capable of simultaneously integrating multivariable observations (including development stage, DVS; leaf area index, LAI; total aboveground dry matter, WAGT; and leaf nitrogen concentration, LNC). Then, the system was tested through three consecutive years of field experiments from 2021 to 2023. The results revealed that the ORYZA-EnKF model significantly improved the simulations of crop growth compared to the ORYZA2000 model. The relative root mean squared error (RRMSE) for LAI simulations decreased from 23–101% to 16–47% in the three-year experiment. Moreover, the incorporation of LNC observations enabled more accurate predictions of rice nitrogen dynamics, with RRMSE for LNC simulations reduced from 16–31% to 14–26%. And, the RRMSE decreased from 32–50% to 30–41% in the simulations of LNC under low-nitrogen conditions. The multivariable data assimilation system demonstrated its effectiveness in improving crop growth simulations and nitrogen status predictions, providing valuable insights for precision agriculture. Full article

Porous starch has been created through hydrolysis by amyloglucosidase and α-amylase. However, little information is known about the precise evolution of multi-scale structures of starch during digestion. In this study, rice starch and potato starch, containing different crystalline structures, were hydrolyzed by amyloglucosidase and α-amylase for 20 and 60 min, respectively, and their resulting structural changes were examined. The digestion process caused significant degradation of the molecular structures of rice and potato starches. In addition, the alterations in the ordered structures varied between the two starches. Rice starch exhibited porous structures, thicker crystalline lamellae as determined by small-angle X-ray scattering, and enhanced thermostability after digestion using differential scanning calorimetry. For rice starch, the extent of crystalline structures was analyzed with an X-ray diffractometer; it was found to first increase after 20 min of digestion and then decrease after 60 min of digestion. In contrast, potato starch did not display porous structures but exhibited thicker crystalline lamellae and a reduction in ordered structures after digestion. These findings suggest that it is possible to intentionally modulate the multi-scale structures of starch by controlling the digestion time, thereby providing valuable insights for the manipulation of starch functionalities. Full article

This paper investigates the complexity of real functions through proof techniques inspired by formal language theory. Productiveness, which is a stronger form of non-recursive enumerability, is employed to analyze the complexity of various problems related to real functions. Our work provides a deep reexamination of Hilbert’s tenth problem and the equivalence to the identically 0 function problem, extending the undecidability results of these problems into the realm of productiveness. Additionally, we study the complexity of the equivalence to the identically 0 function problem over different domains. We then construct highly efficient many-one reductions to establish Rice-style theorems for the study of real functions. Specifically, we show that many predicates, including those related to continuity, differentiability, uniform continuity, right and left differentiability, semi-differentiability, and continuous differentiability, are as hard as the equivalence to the identically 0 function problem. Due to their high efficiency, these reductions preserve nearly any level of complexity, allowing us to address both complexity and productiveness results simultaneously. By demonstrating these results, which highlight a more nuanced and potentially more intriguing aspect of real function theory, we provide new insights into how various properties of real functions can be analyzed. Full article

Rice spikelet size, spikelet length and spikelet width, are very important traits directly related to a rice crop’s yield. The accurate measurement of these parameters is quite significant in research such as breeding, yield evaluation and variety improvement for rice crops. Traditional measurement methods still mainly rely on manual labor, which is time-consuming, labor-intensive and error-prone. In this study, a novel method, dubbed the “SSM-Method”, based on convolutional neural network and traditional image processing technology has been developed for the efficient and precise measurement of rice spikelet size parameters on rice panicle structures. Firstly, primary branch images of rice panicles were collected at the same height to build an image database. The spikelet detection model using convolutional neural network was then established for spikelet recognition and localization. Subsequently, the calibration value was obtained through traditional image processing technology. Finally, the “SSM-Method” integrated with a spikelet detection model and calibration value was developed for the automatic measurement of spikelet sizes. The performance of the developed SSM-Method was evaluated through testing 60 primary branch images. The test results showed that the root mean square error (RMSE) of spikelet length for two rice varieties (Huahang15 and Qingyang) were 0.26 mm and 0.30 mm, respectively, while the corresponding RMSE of spikelet width was 0.27 mm and 0.31 mm, respectively. The proposed algorithm can provide an effective, convenient and low-cost tool for yield evaluation and breeding research. Full article

Rice (Oryza sativa L.), a globally staple food crop, frequently encounters growth, developmental, and yield limitations due to phosphate deficiency. LOW PHOSPHATE ROOT1/2 (LPR1/2) are essential genes in plants that regulate primary root growth and respond to local phosphate deficiency signals under low phosphate stress. In rice, five LPR genes, designated OsLPR1–OsLPR5 based on their sequence identity with AtLPR1, have been identified. OsLPR3 and OsLPR5 are specifically expressed in roots and induced by phosphate deficiency, contributing to rice growth, development, and the maintenance of phosphorus homeostasis under low phosphate stress. In contrast, OsLPR2 is uniquely expressed in shoots, suggesting it may have distinct functions compared with other family members. This study employed Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (CRISPR/Cas9) gene editing technology to generate oslpr2 mutant transgenic lines and subsequently investigated the effect of OsLPR2 gene knockout on rice growth, phosphate utilization, and salt stress tolerance in the seedling stage, as well as the effect of OsLPR2 gene knockout on rice development and agronomic traits in the maturation stage. The results indicated that the knockout of OsLPR2 did not significantly impact rice seedling growth or phosphate utilization, which contrasts significantly with its homologous genes, OsLPR3 and OsLPR5. However, the mutation influenced various agronomic traits at maturity, including plant height, tiller number, and seed setting rate. Moreover, the OsLPR2 mutation conferred enhanced salt stress tolerance in rice. These findings underscore the distinct roles of OsLPR2 compared with other homologous genes, establishing a foundation for further investigation into the function of the OsLPR family and the functional differentiation among its members. Full article

Fully utilizing solid waste as supplementary cementitious materials (SCMs) while ensuring the mechanical properties of cement-based materials is one of the pathways for carbon reduction in the cement industry. Understanding the effects of the two solid wastes-limestone powder (LP) and rice husk ash (RHA) on the mechanical properties of cement-based materials is of great significance for their application in concrete. This study investigates the impact of LP and RHA on the strength of cement mortar at various ages and the microhardness of hardened cement paste. The results suggest that two materials have a certain synergistic effect on the mechanical properties of the cementitious materials. The addition of RHA effectively addresses the issues of slow strength development, insufficient late-stage strength of the cementitious material, and the low strength blended with a large amount of LP, while a suitable amount of LP can promote the strength increase in the cement-RHA system. Based on the comprehensive analysis of compressive strength and microhardness, the optimal solution for achieving high mechanical properties in composite cementitious materials is to use 10% each of LP and RHA, resulting in a 9.5% increase in 28 d strength compared to a pure cement system. The higher the content of LP, the greater the increase caused by 10% RHA in compressive strength of the composite system, which makes the strength growth rate of cementitious material mixed with 10% LP at 3–56 d 62.1%. When the LP content is 20% and 30%, the addition of 10% RHA increases the 28 d strength by 44.8% and 38.8%, respectively, with strength growth rates reaching 109.8% and 151.1% at 3–56 d. Full article

Global food security is at risk due to climate change. Soil fertility loss is among the impacts of climate change which reduces the productivity of rice–wheat cropping systems. This study investigated the effects of varying nitrogen levels and transplanting/sowing dates on the grain yield (GY) and biological yield (BY) of rice and wheat cultivars over two growing seasons (2017–2019). Additionally, the impact of climate change on the productivity of both crops was tested under a 1.5 °C temperature increase and 510 ppm CO₂ concentration while nitrogen fertilization and sowing window adjustments were evaluated as adaptation options using the DSSAT and APSIM models. Results indicated that the application of 120 kg N ha⁻¹ significantly enhanced both GY and BY in all rice cultivars. The highest wheat yields were obtained with 140 kg N ha⁻¹ for all cultivars. Rice transplanting on the 1st of July and wheat sowing on the 15th of November showed the best yields. The statistical indices of the model’s forecast results were satisfactory for rice (R² = 0.83–0.85, root mean square error (RMSE) = 341–441, model efficiency (EF) = 0.82–0.89) and wheat (R² = 0.84–0.89, RMSE = 213–303, EF = 0.88–0.91). Both models predicted yield loss in wheat (20–25%) and rice (28–30%) under a climate change scenario. The models also predicted that increased nitrogen application and earlier planting would be necessary to reduce the impacts of climate change on the productivity of both crops. Full article

Erwinia amylovora, the causative agent of fire blight, causes significant economic losses for farmers worldwide by inflicting severe damage to the production and quality of plants in the Rosaceae family. Historically, fire blight control has primarily relied on the application of copper compounds and antibiotics, such as streptomycin. However, the emergence of antibiotic-resistant strains and growing environmental concerns have highlighted the need for alternative control methods. Recently, there has been a growing interest in adopting bacteriophages (phages) as a biological control strategy. Phages have demonstrated efficacy against the bacterial plant pathogen E. amylovora, including strains that have developed antibiotic resistance. The advantages of phage therapy includes its minimal impact on microbial community equilibrium, the lack of a detrimental impact on plants and beneficial microorganisms, and its capacity to eradicate drug-resistant bacteria. This review addresses recent advances in the isolation and characterization of E. amylovora phages, including their morphology, host range, lysis exertion, genomic characterization, and lysis mechanisms. Furthermore, this review evaluates the environmental tolerance of E. amylovora phages. Despite their potential, E. amylovora phages face certain challenges in practical applications, including stability issues and the risk of lysogenic conversion. This comprehensive review examines the latest developments in the application of phages for controlling fire blight and highlights the potential of E. amylovora phages in plant protection strategies. Full article

In this work, composites made of polylactide (PLA) and filled with alkali-pretreated rice husk (RH) were investigated. Composites containing 20, 30, and 40 wt.% of RH were synthesized. It was shown that alkaline treatment, along with the change in crystal lattice, led to an increase in the content of non-crystalline parts and the volume of intercrystalline spaces, and the internal surface of the cellulose fiber increased, which resulted in improved adhesion of the fiber with the matrix. The addition of rice husk to the PLA matrix led to an increase in the flexural modulus, which increased to 2881 MPa for the PLA/RH (80/20 wt.%) and 3034 MPa for the PLA/RH (70/30 wt.%) composites and lowered the peak load stress by approximately 43% for the composite with 20 wt.% RH and 56% for the composite with 30 wt.% RH. The reduction in the degree of PLA crystallinity allows macromolecules to move more freely in amorphous regions, which has a positive effect on increasing the flexibility of materials in general. The optimal formulation is a composite consisting of 30% RH and 70% PLA matrix. Full article

RNA-sequencing enables the comprehensive detection of gene expression levels at specific time points and facilitates the identification of stress-related genes through co-expression network analysis. Understanding the molecular mechanisms and identifying key genes associated with salt tolerance is crucial for developing rice varieties that can thrive in saline environments, particularly in regions affected by soil salinization. In this study, we conducted an RNA-sequencing-based time-course transcriptome analysis of ‘Jao Khao’, a salt-tolerant Thai rice variety, grown under normal or saline (160 mM NaCl) soil conditions. Leaf samples were collected at 0, 3, 6, 12, 24, and 48 h. In total, 36 RNA libraries were sequenced. ‘Jao Khao’ was found to be highly salt-tolerant, as indicated by the non-significant differences in relative water content, cell membrane stability, leaf greenness, and chlorophyll fluorescence over a 9-day period under saline conditions. Plant growth was slightly retarded during days 3–6 but recovered by day 9. Based on time-series transcriptome data, we conducted differential gene expression and weighted gene co-expression network analyses. Through centrality change from normal to salinity network, 111 key hub genes were identified among 1,950 highly variable genes. Enriched genes were involved in ATP-driven transport, light reactions and response to light, ATP synthesis and carbon fixation, disease resistance and proteinase inhibitor activity. These genes were upregulated early during salt stress and RT-qPCR showed that ‘Jao Khao’ exhibited an early upregulation trend of two important genes in energy metabolism: RuBisCo (LOC_Os10g21268) and ATP synthase (LOC_Os10g21264). Our findings highlight the importance of managing energy requirements in the initial phase of the plant salt-stress response. Therefore, manipulation of the energy metabolism should be the focus in plant resistance breeding and the genes identified in this work can serve as potentially effective candidates. Full article

Research indicates that, owing to the enhanced grain-filling rate of tetraploid rice, its yield has notably improved compared to previous levels. Studies conducted on diploid rice have revealed that optimal planting density and fertilization rates play crucial roles in regulating rice yield. In this study, we investigated the effects of different nitrogen application and planting density treatments on the growth, development, yield, and nitrogen utilization in tetraploid (represented by T7, an indica–japonica conventional allotetraploid rice) and diploid rice (Fengliangyou-4, represented by FLY4, a two-line super hybrid rice used as a reference variety for the approval of super rice with a good grain yield performance). The results indicated that the highest grain-filling rate of T7 could reach 77.8% under field experimental conditions due to advancements in tetraploid rice breeding. This is a significant improvement compared with the rate seen in previous research. Under the same conditions, T7 exhibited a significantly lower grain yield than FLY4, which could be attributed to its lower grain-filling rate, spikelets per panicle, panicle number m⁻², and harvest index score. Nitrogen application and planting density displayed little effect on the grain yield of both genotypes. A higher planting density significantly enhanced the leaf area index and biomass accumulation, but decreased the harvest index score. Compared with T7, FLY4 exhibited a significantly higher nitrogen use efficiency (NUE_g), which was mainly due to the higher nitrogen content in the straw. Increasing nitrogen application significantly decreased NUE_g due to its minimal effect on grain yield combined with its significant enhancement of nitrogen uptake. Our results suggest that the yield and grain-filling rate of T7 have been improved compared with those of previously tested polyploid rice, but are still lower than those of FLY4, and the yield of tetraploid rice can be further improved by enhancing the grain-filling rate, panicle number m⁻², and spikelets per panicle via genotype improvement. Full article

Rapid Alkalization Factor (RALF) is a signaling molecule in plants that plays a crucial role in growth and development, reproductive processes, and responses to both biotic and abiotic stresses. Although RALF peptides have been characterized in Arabidopsis and rice, a comprehensive bioinformatics analysis of the ZmRALF gene family in maize is still lacking. In this study, we identified 20 RALF genes in the maize genome. Sequence alignment revealed significant structural variation among the ZmRALF family genes. Phylogenetic analysis indicates that RALF proteins from Arabidopsis, rice, and maize can be classified into four distinct clades. Duplication events suggest that the expansion of the RALF gene family in maize primarily relies on whole-genome duplication. ZmRALF genes are widely expressed across various tissues; ZmRALF1/15/18/19 are highly expressed in roots, while ZmRALF6/11/14/16 are predominantly expressed in anthers. RNA-seq and RT-qPCR demonstrated that the expression levels of ZmRALF7, ZmRALF9, and ZmRALF13 were significantly up-regulated and down-regulated in response to PEG and NaCl stresses, respectively. Overall, our study provides new insights into the role of the RALF gene family in abiotic stress. Full article

Phylloporia pulla, a macrofungal species in the Hymenochaetales, Basidiomycota, is known to enhance the nutritional and bioactive properties of rice through co-fermentation; however, its own secondary metabolites are not well understood. In this study, an integrative analysis of transcriptome and metabolome data revealed that the accumulation of steroids, steroid derivatives, and triterpenoids in P. pulla peaks during the mid-growth stage, while the genes associated with these metabolites show higher expression levels from the early to mid-growth stages. Weighted gene co-expression network analysis identified several modules containing candidate genes involved in the synthesis of steroids, steroid derivatives, and triterpenoids. Specifically, six key hub genes were identified, along with their connectivity to other related genes, as potential catalysts in converting the precursor lanosterol to celastrol. This study enhances our understanding of the secondary metabolites of P. pulla and is essential for the selective utilization of these bioactive compounds. Full article

Rice (Oryza sativa L.) serves as a substitute for bread and is a staple food for half of the world’s population, but it is heavily affected by insect pests. The fall armyworm (Spodoptera frugiperda) is a highly destructive pest, threatening rice and other crops in tropical regions. Despite its significance, little is known about the molecular mechanisms underlying rice’s response to fall armyworm infestation. In this study, we used transcriptome analysis to explore the global changes in gene expression in rice leaves during a 1 h and 12 h fall armyworm feeding. The results reveal 2695 and 6264 differentially expressed genes (DEGs) at 1 and 12 h post-infestation, respectively. Gene Ontology (GO) and KEGG enrichment analyses provide insights into biological processes and pathways affected by fall armyworm feeding. Key genes associated with hormone regulation, defense metabolic pathways, and antioxidant and detoxification processes were upregulated, suggesting the involvement of jasmonic acid (JA) signaling, salicylic acid biosynthesis pathways, auxin response, and heat shock proteins in defense during 1 h and 12 h after fall armyworm infestation. Similarly, key genes involved in transcriptional regulation and defense mechanisms reveal the activation of calmodulins, transcription factors (TFs), and genes related to secondary metabolite biosynthesis. Additionally, MYB, WRKY, and ethylene-responsive factors (ERFs) are identified as crucial TF families in rice’s defense response. This study provides a comprehensive understanding of the molecular dynamics in rice responding to fall armyworm infestation, offering valuable insights for developing pest-resistant rice varieties and enhancing global food security. The identified genes and pathways provide an extensive array of genomic resources that can be used for further genetic investigation into rice herbivore resistance. This also suggests that rice plants may have evolved strategies against herbivorous insects. It also lays the groundwork for novel pest-resistance techniques for rice. Full article