Background: The Songhua River Basin, a vital grain-producing area in China, faces challenges due to the uneven distribution of water resources and the intensive water demands of agriculture. To enhance agricultural development and effectively manage water scarcity, it is essential to identify the water-saving potential of major staple crops - corn, wheat, and rice. This study enhances the World Food Studies (WOFOST) model by refining the day of year for the developmental vegetative stage (DVS), thereby improving the representation of phenological stages for spring maize, spring wheat, and rice within the model. This refinement offers a detailed analysis of the potential and rainfed yields.
Results: The results from the modified WOFOST model show promising simulation outcomes for the biomass and yield of maize, wheat, and rice, with Nash-Sutcliffe efficiency (NS) and index of agreement (IoA) values all exceeding 0.7. An analysis of photothermal potential yields (Y) and rainfed yields (Y) revealed minimal differences in yields for spring maize and rice across various rainfall frequencies. Specifically, the average photothermal utilization rates (LTs) are 93.57% for maize and 85.25% for rice. In contrast, the rainfed yield for wheat is lower than its photothermal yield, with an LT of 43.66%.
Conclusions: These findings suggest that in the Songhua River Basin, maize and rice offer greater potential for water conservation compared to wheat. It is recommended to judiciously reduce irrigation during the growing seasons of spring maize and rice to help alleviate agricultural water use pressures. © 2024 Society of Chemical Industry.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/jsfa.13630 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Rape Yield Estimation Considering Non-Foliar Green Organs Based on the General Crop Growth Model.
Plant Phenomics
September 2024
State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China (the Institute of Agricultural Resources and Regional Planning), Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Article Synopsis
- This study addresses the inaccuracies in rape yield estimates produced by traditional crop models by incorporating the photosynthesis of siliques, enhancing modeling accuracy.
- Two new calibration methods, TPAI-SPA and TPAI-Curve, were developed using a Total Photosynthetic Area Index (TPAI) that accounts for silique photosynthesis, improving yield predictions.
- Validation of these methods showed significant increases in estimation accuracy for total weight of storage organs and above-ground biomass, demonstrating their practical importance for oilseed crop yield simulations.
Research on fertilization decision method for rice tillering stage based on the coupling of UAV hyperspectral remote sensing and WOFOST.
Front Plant Sci
June 2024
College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang, China.
Introduction: The use of chemical fertilizers in rice field management directly affects rice yield. Traditional rice cultivation often relies on the experience of farmers to develop fertilization plans, which cannot be adjusted according to the fertilizer requirements of rice. At present, agricultural drones are widely used for early monitoring of rice, but due to their lack of rationality, they cannot directly guide fertilization.
View Article and Find Full Text PDFThe adaptability and irrigation constraints analysis of the WOFOST model for grain production in the Songhua River Basin.
J Sci Food Agric
October 2024
College of Hydraulic and Environmental Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou, China.
Background: The Songhua River Basin, a vital grain-producing area in China, faces challenges due to the uneven distribution of water resources and the intensive water demands of agriculture. To enhance agricultural development and effectively manage water scarcity, it is essential to identify the water-saving potential of major staple crops - corn, wheat, and rice. This study enhances the World Food Studies (WOFOST) model by refining the day of year for the developmental vegetative stage (DVS), thereby improving the representation of phenological stages for spring maize, spring wheat, and rice within the model.
View Article and Find Full Text PDFDaily bias-corrected weather data and daily simulated growth data of maize, millet, sorghum, and wheat in the changing climate of sub-Saharan Africa.
Data Brief
June 2024
Plant Production Systems Group, Wageningen University & Research, P.O. Box 430, 6700AK Wageningen, the Netherlands.
Crop models are the primary means by which agricultural scientists assess climate change impacts on crop production. Site-based and high-quality weather and climate data is essential for agronomically and physiologically sound crop simulations under historical and future climate scenarios. Here, we describe a bias-corrected dataset of daily agro-meteorological data for 109 reference weather stations distributed across key production areas of maize, millet, sorghum, and wheat in ten sub-Saharan African countries.
View Article and Find Full Text PDFEffects of warming and drought on growth and development of soybean in Hailun region.
Open Life Sci
October 2023
School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, China.
As a result of global warming, drought, flooding, change in the rainfall pattern, etc. occur frequently. All these natural disasters could cause serious damage to the food security.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!