Waterlogging constrains crop yields in many regions around the world. Despite this, key drivers of crop sensitivity to waterlogging have received little attention. Here, we compare the ability of the SWAGMAN Destiny and CERES models in simulating soil aeration index, a variable contemporaneously used to compute three distinct waterlogging indices, denoted hereafter as WI , WI, and WI. We then account for effects of crop growth stage and soil temperature on waterlogging impact by introducing waterlogging severity indices, WI , which accommodates growth stage tolerance, and WI , which accounts for both soil temperature and growth stage. We evaluate these indices using data collected in pot experiments with genotypes "Yang mai 11" and "Zheng mai 7698" that were exposed to both single and double waterlogging events. We found that WI exhibited the highest correlation with yield (-0.82 to -0.86) suggesting that waterlogging indices which integrate effects of temperature and growth stage may improve projections of yield penalty elicited by waterlogging. Importantly, WI not only allows insight into physiological determinants, but also lends itself to remote computation through satellite imagery. As such, this index holds promise in scalable monitoring and forecasting of crop waterlogging.
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http://dx.doi.org/10.3389/fpls.2023.1262001 | DOI Listing |
Adv Sci (Weinh)
January 2025
Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, 210009, P. R. China.
Patients with ulcerative colitis (UC) have a higher risk of developing colorectal cancer (CRC), however, the metabolic shifts during the UC-to-CRC transition remain elusive. In this study, an AOM-DSS-induced three-stage colitis-associated colorectal cancer (CAC) model is constructed and targeted metabolomics analysis and pathway enrichment are performed, uncovering the metabolic changes in this transition. Spatial metabolic trajectories in the "normal-to-normal adjacent tissue (NAT)-to-tumor" transition, and temporal metabolic trajectories in the "colitis-to-dysplasia-to-carcinoma" transition are identified through K-means clustering of 74 spatially and 77 temporally differential metabolites, respectively.
View Article and Find Full Text PDFFront Plant Sci
January 2025
Institute of Food Crops, Hainan Academy of Agricultural Sciences/Hainan Key Laboratory of Crop Genetics and Breeding, Haikou, China.
Introduction: Sweet potato is an important food, feed and industrial raw material, and its tubers are rich in starch, carotenoids and anthocyanins.
Methods: To elucidate the gene expression regulation and metabolic characteristics during the development of sweet potato tubers, transcriptomic and metabolomic analyses were performed on the tubers of three different sweet potato varieties at three developmental stages (70, 100, and 130 days (d)).
Results: RNA-seq analysis revealed that 16,303 differentially expressed genes (DEGs) were divided into 12 clusters according to their expression patterns, and the pathways of each cluster were annotated.
Front Plant Sci
January 2025
State Key Laboratory for Crop Stress Resistance and High-Efficiency Production, College of Agronomy, Northwest A & F University, Yangling, Shaanxi, China.
Background: Blending controlled-release nitrogen fertilizer (CRNF) with ordinary nitrogen fertilizer (ONF) is a strategic approach to improve winter wheat nutrient management. This blend provides nitrogen (N) to winter wheat in a balanced and consistent manner, ensuring long-term growth, reducing nutrient loss due to leaching or volatilization, and increasing N use efficiency (NUE).
Aims: CRNF aims to enhance N application suitability, optimizes soil nutrient dynamics, and its widespread use can boost crop NUE and yield.
Front Plant Sci
January 2025
Information and Communication Engineering, Yeungnam University, Gyeongsan, Republic of Korea.
Smart farming is a hot research area for experts globally to fulfill the soaring demand for food. Automated approaches, based on convolutional neural networks (CNN), for crop disease identification, weed classification, and monitoring have substantially helped increase crop yields. Plant diseases and pests are posing a significant danger to the health of plants, thus causing a reduction in crop production.
View Article and Find Full Text PDFFood Sci Anim Resour
January 2025
Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Korea.
Meat analogs are a burgeoning industry, with plant-based meat analogs, insect-based meat analogs, algae-based meat analogs, mycoprotein-based meat analogs, and cell-based meat analogs. However, despite the industry's growth potential, market expansion faces hurdles due to taste and quality disparities compared to traditional meats. The composition and characteristics of meat analogs currently available in the market are analyzed in this study to inform the development of future products in this sector.
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