Abstract

Guar (Cyamopsis tetragonoloba L.) is a relatively unexplored seed legume crop with a high interest for production of galactomannan (guar gum), which is highly valued for industrial purposes. Until now no crop simulation models exist for guar. This paper describes the adaptation of the CROPGRO module of the Cropping System Model (CSM) to simulate guar growth and yield based on literature knowledge as well as optimization against growth analysis and yield data collected in multiple field experiments conducted in Texas and New Mexico. CSM-CROPGRO is a mechanistic model that simulates daily crop growth and development dependent on daily weather, soil properties, crop management, and genetic parameters. Model adaptation started with CROPGRO-Soybean as the template and involved setting tissue compositions, and especially the cardinal temperature dependencies of processes including the rate of leaf appearance, rate of progress to reproductive events, photosynthesis, pod addition, and seed growth rate, all parameterized in the species file. Adapted cultivar parameters include life cycle phase durations, duration to end of leaf area expansion, pod adding duration, leaf photosynthesis, seed size, seed protein, seed lipid, and individual seed filling duration. Compared to soybean, guar appears more sensitive to cold temperature because the cardinal base temperatures for photosynthesis, rate of leaf appearance, leaf area expansion, and seed growth had to be increased by 2–4 ˚C. The model adaptations highlight the drought tolerance of guar, with slower leaf and root senescence and greater tolerance of N-fixation under drought. The model simulated well the time-series growth of two cultivars under irrigated and rainfed conditions at Chillicothe, TX and gave acceptable simulations of end-of-season biomass, pod, and seed yield of guar in response to different weather, irrigation, soils, and seasons across three sites. This is the first creation of a crop model for guar and will be released in DSSAT.

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