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ARS Home » Southeast Area » Dawson, Georgia » National Peanut Research Laboratory » Research » Publications at this Location » Publication #349727

Research Project: Enhancing the Competitiveness of U.S. Peanuts and Peanut-based Cropping Systems

Location: National Peanut Research Laboratory

Title: Three soil water potential strategies to schedule irrigation events using S3DI in cotton

item Sorensen, Ronald - Ron
item Lamb, Marshall

Submitted to: Journal of Cotton Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/7/2019
Publication Date: 4/1/2019
Citation: Sorensen, R.B., Lamb, M.C. 2019. Three soil water potential strategies to schedule irrigation events using S3DI in cotton. Journal of Cotton Science. 23:14-20.

Interpretive Summary: Cotton is one of the most economically important row crops in Georgia with a farm gate value of $1.35 billion (lint and seed) in crop year (CY) 2012 and an aggregated impact of $3.562 billion per annum. Georgia is the second largest cotton producing state in the United States only behind Texas. Cotton production in the southeastern United States is often limited by sporadic distribution of rainfall during the growing season. Although Georgia averages in excess of 50 in of rainfall annually, unreliable rainfall patterns have prompted producers to increase dependence on irrigation, where available, to supplement water during drought periods. Scheduling irrigation events for cotton has been of great interest for many years to reach a goal of increased water use efficiency, lint production, lint quality, economics, and water conservation. Cotton growers want to be efficient with irrigation water and need an inexpensive technique of when and how much to irrigate. The use of soil water potential sensors and the expert system IrrigatorPro for peanut modified for cotton to schedule irrigation events There are other ways to determine when to schedule an irrigation event such as measuring soil water status (water content or potential), plant water status (leaf temperature, gas exchange, etc.), meteorological data with associated empirical equations, or combinations of these techniques. A study conducted in the Southeast, evaluated cotton yield, quality, and maturity using overhead sprinkler irrigation, subsurface drip irrigation, and non-irrigated production. No yield differences resulted between overhead sprinkler and subsurface drip and both irrigation methods resulted in average yield increases of 54% compared to non-irrigated production. The use of drip irrigation on cotton has been favorable with yields similar to or greater than overhead sprinkler irrigation. The objective of this research was to evaluate three water potential value strategies for irrigation scheduling for lint yield, lint quality, water use efficiency, and economic water use efficiency when using S3DI. This research was conducted at the USDA-ARS Multi-crop Irrigation Research Farm in Shellman, Georgia (31o 47’ 44” N by 84o 36’ 30” W) during the 2012 through the 2016 growing seasons on a Faceville fine sandy loam (Fine, kaolinitic, thermic Typic Kandiudults) with up to 3% slope (cotton was not planted in 2014). The topography was undulating with a general slope towards the east with a north aspect. Irrigation events were treatment 1 (I1) had an irrigation event when the average value of both the 25 and 50-cm sensors was -40 kPa. When this occurred between 20 and 25 mm depth of water was applied. Irrigation treatment 2 (I2) was irrigated when the value of the two sensors averaged -70 kPa and a total of 25 to 30 mm water was applied. Irrigation treatment 3 (I3) scheduled an event when the average value of the sensors was -70 kPa (germination to 1st square/flower), -40 kPa (1st square/flower to 1st cracked boll/flowering at the top of the plant), and -60 kPa thereafter (1st cracked boll/flowering at the top of the plant) till cutout or leaf defoliation. Irrigation events for cotton were determined using soil water potential sensors installed at 10 and 20-in soil. Water potential sensors were connected to a radio equipped datalogger with a 1 hour interrogation time. All data were downloaded daily and evaluated manually to determine irrigation events. Cotton was picked using a 2-row spindle picker. Seed cotton from the picker basket was dumped into a weigh buggy, weights were recorded, a 2 lb subsample was collected, and a small 0.5 lb sub-sample was ginned on a table top gin. This ginned sample was sent to an official classing office to determine lint quality. Irrigation water use efficiency (IWUE) was determined by subtracting the nonirrigated yield from the irrigate

Technical Abstract: Scheduling irrigation events in the humid southeast can be challenging. The objective was to evaluate three water potential strategies for scheduling irrigation events in cotton (Gossypium hirsutum L.) with respect to lint yield and quality, irrigation water use efficiency (IWUE), and value water use efficiency (VWUE). Research was conducted in 2012 through 2016 in southwest Georgia, USA. Irrigation water was applied with a shallow subsurface drip irrigation (S3DI) system. Water potential sensors were installed at 25 and 50 cm soil depth. Irrigation events occurred when the average water potential values were: -40 kPa (I1), -70 kPa (I2), -70/-40/-60 kPa (I3) [germination to 1st square/1st square to 1st cracked boll/1st cracked boll to defoliation]. All irrigated treatments had higher yield (1975 kg ha-1) than dryland (987 kg ha-1) except during 2013 (wet year). When removing 2013 data, there was no lint yield difference across years (p=0.07) or across irrigation treatments (p=0.06). Across dry years, I2 or I3 applied 170 mm less irrigation water compared to I1. There were differences in lint quality by irrigation treatment and year, but all quality values were within acceptable ranges without price deductions. Dry year IWUE for treatments I2 and I3 averaged 3.1 kg lint mm-1 compared with I1 at 2.2 kg lint mm-1. For VWUE, both I2 and I3 had 44% greater value per unit of irrigation applied compared with I1. Either I2 or I3 may be used for scheduling irrigation events efficiently and economically