Cotton growth model under drip irrigation with film mulching: A case study of Xinjiang, China

Abstract

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 drymatter 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. INTRODUCTIONGlobal warming has a significant impact on China's agricultural production by altering crop growth. According to the

A new regional cotton growth model based on reference crop evapotranspiration for predicting growth processes

“…Every crop has biologically defined upper and lower temperature limits beyond which its growth and development can be adversely affected. For cotton, the upper and lower temperature limits are 40 ℃ and 10 ℃, respectively, as demonstrated by numerous studies 24 , 45 – 47 . Growing degree days ( GDD ) are a measure of heat accumulation used to estimate crop development and growth.…”

“…The cotton growth index data used in this study were obtained from previously published studies on cotton growth in China. The portion of the data used for analyzing the characteristics of cotton growth index in Xinjiang came from Wang 24 , and data from other regions are summarized in Table 1 . The main cotton planting areas in China are concentrated in Central China, North China, and the Xinjiang region (Fig.…”

“…GDD can be used to analyze thermal conditions under certain meteorological conditions, which can determine the optimal sowing date, growth period, and corresponding physiological growth characteristics of crops 21 . Therefore, some scholars have used GDD instead of time to establish crop growth models 9 , 23 , 24 . Logistic models based on GDD , rather than time, better describe the change processes in major crop growth indicators 9 , 23 – 26 .…”

“…Recently, numerous scholars have established cotton growth logistic models based on either time or GDD . For example, Wang 24 developed a cotton growth logistic model based on GDD , using the Xinjiang region as an example. Gao 32 described the biomass accumulation process of main stem leaves, boll subtending leaves, capsule wall, and seed cotton weight using the logistic growth model, while Zhang 16 used the logistic model to simulate the effects of planting densities and nitrogen rates on cotton biomass accumulation.…”

Simulating Growth and Evaluating the Regional Adaptability of Cotton Fields with Non-Film Mulching in Xinjiang

“…Although there are some differences in the simulated methods, details, and yield components of existing cotton models, the main processes include phenology, light energy interception, carbon (C) assimilation, respiration, organ formation, biomass accumulation and distribution, and stress factor simulation [13]. These models have been used in irrigation management [14][15][16][17][18][19][20][21] and water use efficiency evaluation [22][23][24], assessment of effects of deficit irrigation on cotton growth and yield [25][26][27][28], evaluation of saline water irrigation on cotton growth and yield [29], nitrogen and phosphorus dynamics and fertilization management [14,30,31], fiber quality, embryo oil and protein accumulation simulation [32][33][34], and topping management [35].…”