Assessment of Heat Unit Availability and Potential Lint Yield of Cotton in Oklahoma

Author:

Masasi Blessing,Taghvaeian Saleh,Gowda Prasanna H,Moriasi Daniel N,Starks Patrick J

Abstract

HighlightsWater availability challenges have increased interest in cotton production in Oklahoma.An attempt was made to understand the feasibility of growing cotton in all counties of Oklahoma.Many areas in Oklahoma have sufficient thermal conditions for cotton production.Potential cotton lint yields generally increase from northern to southern areas of the state.Abstract. With the expansion of planted area, Oklahoma is increasingly becoming a major cotton producing state in the United States (U.S.). However, the feasibility of growing cotton in all counties of Oklahoma has not been determined. In this study, a heat unit based model was used to estimate the potential cotton lint yields (PCLYs) for all 77 counties of Oklahoma using 38 years (1981-2018) of air temperature data. PCLYs were estimated for optimal (no stress) conditions. The long-term total heat units (THUs) were more than 1000°C·d in 99% of counties, an indication that many areas in Oklahoma may have conducive thermal conditions for cotton production in most years. Similar to the THUs, the PCLYs generally increased from the northern to the southern counties of the state, and long-term averages ranged from 407 to 2472 kg ha-1. About 97% of the counties achieved long-term average PCLYs of at least 1000 kg ha-1. However, the results showed significant interannual variability of the estimated PCLYs in each county over the 38-year period. Low and high PCLYs mostly coincided with years characterized by cool and warm growing seasons, respectively. Reductions of PCLY ranging from 6% to 29% were observed when planting was delayed by just one week from the optimized planting date. This indicates that cotton producers need to carefully consider planting date to maximize cotton lint yield. As THUs were the only factor considered for calculating PCLYs in this study, future research should incorporate other variables such as rainfall and heat stress to improve PCLY estimations. Keywords: Air temperature, Planting date, Soil temperature, Yield gap, Yield variability.

Funder

Agricultural Research Service, U.S. Department of Agriculture

Publisher

American Society of Agricultural and Biological Engineers (ASABE)

Subject

General Engineering

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