|Stone, Kenneth - Ken
|BAUER, PHILIP - Retired ARS Employee
|SIGUA, GILBERT - Retired ARS Employee
Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/15/2022
Publication Date: 10/14/2022
Citation: Stone, K.C., Billman, E.D., Bauer, P.J., Sigua, G.C. 2022. Using NDVI for variable rate cotton irrigation prescriptions. Applied Engineering in Agriculture. 38(5):787-795. https://doi.org/10.13031/aea.15071.
Interpretive Summary: Sustainable cotton production in the southeastern U.S. Coastal Plain often requires supplemental irrigation to achieve high yields and lint quality. This irrigation timing is more challenging in the southeastern U.S. Coastal Plain region due to its spatial variable sandy soils with low water and nutrient holding capacities and rainfall variability during the growing season. We designed a two-year experiment to evaluate an irrigation scheduling tool to that measures plant vegetation as a guide for determining how much water to apply to specific areas of the cotton field. This method used a sensing method called the normalized difference vegetative index (NDVI) to measure crop reflectance. Using these NDVI measurements in plots taken throughout the field, we were able to calculate how much water to apply to specific areas (plots) in the field. We compared this method of irrigating to a uniform irrigation method that applied the same amount of irrigation to all of its plots. In both years of the study, we observed no differences in cotton yields between these two irrigation methods and that they both had greater cotton yields than a rainfed control. In the first year of the study, the NDVI method required less water than the uniform irrigation method. Additionally, the water use efficiency was approximately the same for the two irrigation methods. We concluded that the NDVI irrigation application method appears to be a useful tool managing irrigation spatially throughout a field and for developing irrigation prescriptions using plants to let us know how much water it requires.
Technical Abstract: Irrigation timing is crucial for achieving high cotton yields and lint quality. This irrigation timing is more challenging in the southeastern U.S. Coastal Plain region due to its spatial variable sandy soils with low water and nutrient holding capacities and rainfall variability during the growing season. To address these challenges, we conducted a 2-year (2017 and 2018) study evaluating two irrigation scheduling methods under a variable rate irrigation system. The two irrigation methods were: 1) a uniform irrigation management based on weekly crop water usage, and 2) spatial crop coefficients derived from normalized difference vegetative indices (NDVI). We compared cotton yields and water use efficiency using the two irrigation scheduling methods at two different planting densities. The two plant populations were 5.7 and 1.2 plants m2 to provide different NDVI readings and water requirements. In 2017, there were no significant differences in cotton yields due to the adequate rainfall during the growing season that required only three irrigations events. The mean irrigation depth for the NDVI method was significantly lower than the Uniform method (56 and 64 mm, respectively, LSD=4.2). In 2018, there was lower rainfall during the growing season requiring 8 irrigation events and the cotton yields in the two irrigation treatments were significantly higher than the rainfed treatment. Irrigation depths in 2018 were not significantly different for the two irrigation methods. Water use efficiencies were not significantly different for the two irrigation methods. The planting density had little impact on the cotton yields, irrigation depth, water use efficiency or cotton fiber quality. These results indicate that the NDVI derived crop coefficient values were as effective in prescribing irrigation applications as the uniform irrigation method for irrigation management. The NDVI derived crop coefficient irrigation method appears to be a helpful useful tool for managing irrigation and developing irrigation prescriptions.