Evaluation of DSSAT‐CROPGRO‐cotton model to simulate phenology, growth, and seed cotton yield in northwestern India

Abstract

Crop simulation models are widely used in developed countries to understand the impact of uncertain weather situations on crop production and consequent strategies formulation but their application in developing countries like India is limited and thus needs to be strengthened. The main objective of this study was to evaluate the DSSAT-CROPGRO-cotton (Gossypium hirsutum L.) model for assessing impact of varying weather on productivity dynamics of cotton in northwestern India. To ascertain this, field experiments were carried out under a 3 yr study at two distinct agro-climatic zones/locations for testing and validation of CROPGRO-cotton model (version 4.7) for phenological development and seed cotton yield of four diverse cotton cultivars (F2228, F1861, NCS855BGII, and RCH650BGII) grown under three sowing dates (20 April, 10 May, and 30 May). The results elucidated that phenological events like anthesis and physiological maturity were fairly predicted with high d-index value ≥0.83 and ≥0.89 and low root mean square error (RMSE), that is, ≤2.27 and ≤4.98 d, respectively. Furthermore, aboveground biomass and seed cotton yield also exhibited a RMSE of ≤706 kg haź (≥0.72, d-index) and ≤126 kg ha -1 (≥0.97, d-index), respectively, indicative of high accuracy. These findings revealed that DSSAT-CROPGRO-cotton model could be exploited for simulating cotton growth, phenology, and yield in northwestern India besides its application in similar arid crop environments across the globe. However, further testing with extensive and long-term datasets is required to improve the utility of model. INTRODUCTIONCrop simulation models integrate the scientific knowledge frommany disciplines including agricultural and allied sciences. Models can accurately evaluate individual and/or joint

Dry matter partitioning in Bt and non Bt cotton (Gossypium hirsutum) cultivars under different sowing environments of Punjab

“…Besides better fruiting structures, Bt cultivars also possessed the quality of producing higher total dry matter over non Bt cultivars (Joshi et al 2011). Higher seed cotton yield for Bt cotton hybrids has been evident in accordance with findings of Mishra et al (2021) who reported better yield contributing parameters such as more bolls per plant and bigger boll size to be primary reason for superiority of transgenic cultivars over conventional varieties.…”

Sub-surface drip fertigation improves seed cotton yield and monetary returns

“…Biomass accumulation was measured by cutting the whole aboveground portion of the plant after harvest and then weighing after thorough drying under the sun. SCY constituted the total weight of both the hand pickings and is expressed in kilograms per hectare ( Mishra et al., 2021 ).…”

“…This necessitates the adoption of improved and efficient water application strategies to increase the crop productivity with better irrigation management ( Fernández et al., 2020 ; Mishra et al., 2021 ). To achieve food and fiber security for the ever-increasing population, a globally irrigated agricultural area needs to be increased by 20%, with about 40% increase in irrigated crop yield by year 2025 ( Hashem et al., 2018 ).…”

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

“…Existing studies have shown that the average error of phenological development time simulated by calibrated CROPGRO-Cotton in southern Xinjiang is 2.52% [48], which is close to the simulation accuracy of this study. Other research results show that calibrated CROPGRO-Cotton fairly predicts phenological events such as anthesis and physiological maturity with RMSE of ≤2.27 and ≤4.98 d, respectively, in northwestern India [49], and absolute relative errors of 1.7%, 1.1%, and 1.1% based on modified CROPGRO-Cotton. These differences might result from the effects of cotton cultivar and cultivation.…”