Soil surface texture is an important environmental factor that influences crop productivity because of its direct effect on soil water and complex interactions with other environmental factors. Using 30-year data, an agricultural system model (DSSAT-CERES-Wheat) was calibrated and validated. After validation, the modelled yield and water use (WU) of spring wheat (Triticum aestivum L.) from two soil textures (silt loam and clay) under rain-fed condition were analyzed. Regression analysis showed that wheat grown in silt loam soil is more sensitive to WU than wheat grown in clay soil, indicating that the wheat grown in clay soil has higher drought tolerance than that grown in silt loam. Yield variation can be explained by WU other than by precipitation use (PU). These results demonstrated that the DSSAT-CERES-Wheat model can be used to evaluate the WU of different soil textures and assess the feasibility of wheat production under various conditions. These outcomes can improve our understanding of the long-term effect of soil texture on spring wheat productivity in rain-fed condition.
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http://dx.doi.org/10.1038/srep05736 | DOI Listing |
J Adv Res
January 2025
Agronomy College / National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou 450046 China. Electronic address:
Introduction: High-density Wheat 660 K and 90 K SNP arrays are powerful tools for understanding the genetic basis of wheat traits. However, their inconsistantly physical positions that were caused by different versions of Chinese Spring genome during developing arrays are confused and inconvenient for further application.
Objective: With the repid development of wheat geonome sequencing, we aim to reconciliate Wheat 660 K and 90 K SNP arrays in modern cultivar and reveal the genetic basis of dough rheological properties in bread wheat.
Plant Cell Environ
January 2025
State Key Laboratory for Biology of Plant Disease and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, People's Republic of China.
Allohexaploid wheat (Triticum aestivum L.) is one of the major crops worldwide, however there is very limited research on the transcriptional programmes of underlying cell type specification. Single-cell RNA sequencing (scRNA-seq) was used to unravel the transcriptome heterogeneity of cells and the composition of cell types in broad-spectrum organisms.
View Article and Find Full Text PDFBrief Bioinform
November 2024
State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road, Beijing, 100193, China.
Nonadditive genetic effects pose significant challenges to traditional genomic selection methods for quantitative traits. Machine learning approaches, particularly kernel-based methods, offer promising solutions to overcome these limitations. In this study, we developed a novel machine learning method, KPRR, which integrated a polynomial kernel into ridge regression to effectively capture nonadditive genetic effects.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
Agronomy Department, Faculty of Agriculture, Al-Azhar University, Cairo, Egypt.
Drought stress significantly impacts wheat productivity, but plant growth regulators may help mitigate these effects. This study examined the influence of gibberellic acid (GA3) and abscisic acid (ABA) on wheat (Triticum aestivum L., CV: Giza 171) growth and yield under different water regimes.
View Article and Find Full Text PDFSci Rep
December 2024
Key Laboratory of the Pest Monitoring and Safety Control of Crops and Forests of the Xinjiang Uygur Autonomous Region, College of Agronomy, Xinjiang Agricultural University, Urumqi, 830052, China.
Wheat stripe rust is a fungal disease caused by Puccinia striiformis f. sp. tritici.
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