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开发DSSAT-CERES-谷子模型以动态模拟不同灌溉和施氮制度下谷子()籽粒蛋白质和淀粉的积累

Developing the DSSAT-CERES-Millet Model for Dynamic Simulation of Grain Protein and Starch Accumulation in Foxtail Millet () Under Varying Irrigation and Nitrogen Regimes.

作者信息

Zhou Shiwei, Liu Zijin, Chen Fu

机构信息

College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China.

Key Laboratory of Farming System, Ministry of Agriculture and Rural Affairs of China, Beijing 100193, China.

出版信息

Plants (Basel). 2025 Mar 14;14(6):910. doi: 10.3390/plants14060910.

DOI:10.3390/plants14060910
PMID:40265845
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11945140/
Abstract

Foxtail millet (), vital in northern China, has its quality and taste influenced by starch and protein. Existing models do not simulate the accumulation of these components during growth. To address this, we enhanced the DSSAT-CERES-Millet model (referred to as DSSAT) by integrating two newly developed modules: the protein simulation module and the starch simulation module. The protein simulation module uses a nitrogen-to-protein conversion coefficient to determine grain protein accumulation based on grain nitrogen accumulation simulated by the DSSAT model. In the starch simulation module, the carbon source supply (carbohydrates) received by millet grains is calculated based on the simulated aboveground and vegetative dry matter by the DSSAT model, and starch synthesis is modeled using the Michaelis-Menten equation to convert carbohydrates into starch within the grains. The integrated model demonstrates good performance in simulating grain protein and starch accumulation, with NRMSE (normalized root mean square error) values of 3.06-26.22% and 4.06-26.88%, respectively. It also accurately simulates grain amylopectin and amylose accumulation at maturity, achieving an NRMSE of less than 14%. The enhanced DSSAT-CERES-Millet model can provide guidance for optimizing irrigation and nitrogen management to enhance the protein and starch quality of millet grains.

摘要

谷子在中国北方至关重要,其品质和口感受淀粉和蛋白质影响。现有模型无法模拟这些成分在生长过程中的积累情况。为解决这一问题,我们通过整合两个新开发的模块:蛋白质模拟模块和淀粉模拟模块,对DSSAT-CERES-Millet模型(简称DSSAT)进行了改进。蛋白质模拟模块使用氮-蛋白质转化系数,根据DSSAT模型模拟的籽粒氮积累量来确定籽粒蛋白质积累。在淀粉模拟模块中,根据DSSAT模型模拟的地上部和营养干物质计算谷子籽粒获得的碳源供应(碳水化合物),并使用米氏方程对淀粉合成进行建模,将碳水化合物转化为籽粒内的淀粉。整合后的模型在模拟籽粒蛋白质和淀粉积累方面表现良好,归一化均方根误差(NRMSE)值分别为3.06-26.22%和4.06-26.88%。它还能准确模拟成熟期籽粒支链淀粉和直链淀粉的积累,NRMSE小于14%。改进后的DSSAT-CERES-Millet模型可为优化灌溉和氮肥管理提供指导,以提高谷子籽粒的蛋白质和淀粉品质。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/264e41264815/plants-14-00910-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/6f1fe2767f39/plants-14-00910-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/92ef1a0170e7/plants-14-00910-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/40fb53a3c231/plants-14-00910-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/649597f9b7c1/plants-14-00910-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/7fcb088b56cc/plants-14-00910-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/ddfd7bdaee5c/plants-14-00910-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/264e41264815/plants-14-00910-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/6f1fe2767f39/plants-14-00910-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/92ef1a0170e7/plants-14-00910-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/40fb53a3c231/plants-14-00910-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/649597f9b7c1/plants-14-00910-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/7fcb088b56cc/plants-14-00910-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/ddfd7bdaee5c/plants-14-00910-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cb6/11945140/264e41264815/plants-14-00910-g007.jpg