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Cotton growth model under drip irrigation with film mulching: A case study of Xinjiang, China
Author(s) -
Wang Kang,
Su Lijun,
Wang Quanjiu
Publication year - 2021
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.1002/agj2.20667
Subject(s) - growing degree day , leaf area index , drip irrigation , irrigation , sowing , growing season , mathematics , crop , mulch , crop coefficient , agronomy , environmental science , horticulture , biology
Crop growth depends on the cumulative temperature of the crop growing season, and growing degree days (GDD) is presently widely used as an index of the effective accumulated temperature. However, there are few reports on the relationship model between cotton ( Gossypium hirsutum L.) growth and GDD. Based on meteorological data and published document from the Xinjiang region in the past 12 yr, we used GDD to replace days after sowing to establish a model for the growth of cotton under drip irrigation with film mulch in Xinjiang, China. In order to analyze the effects of temperature on cotton growth under the different regions and management measures, a correction coefficient method was proposed to obtain the uniform growth law. Then a standardized logistic model was used to analyze growth indices based on GDD, and the relationships between maximum leaf area index (LAI max ), maximum dry‐matter accumulation (DMA max ), the harvest index (HI), and total irrigation amount are discussed. Finally, the irrigation amount during the whole growth period is used as an independent variable to predict seed‐cotton yield. The results showed that plant height and growth rate were highest when GDD increased to about 1,100 and 530 °C, respectively. The rates of increase in LAI and DMA were highest when GDD increased to about 900 and 1,000 °C, respectively. Maximum leaf area index was 4.65 and HI was near optimal when irrigation amount for the entire growing season was 500 mm. The GDD could thus improve the accuracy of yield prediction. This study provides an available method for the further establishment of a universal cotton model.