Estimation of plant health in a sorghum field infected with anthracnose using a fixed-wing unmanned aerial system

Authors: PUGH, NICKOLAS - Texas A&M University; HAN, XIONGZHE - Texas A&M University; COLLINS, DELROY - Texas A&M University; THOMASSON, ALEX - Texas A&M University; COPE, DALE - Texas A&M University; CHANG, ANJIN - Texas A&M University; JUNG, JINHA - Texas A&M University; ISAKEIT, THOMAS - Texas A&M University; Prom, Louis; CARVALHO, GERALDO - Texas A&M University; GATES, IAN - Texas A&M University; VREE, ANDREW - Texas A&M University; BAGNALL, G. CODY - Texas A&M University; ROONEY, WILLIAM - Texas A&M University

Submitted to: Journal of Crop Improvement
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/9/2018
Publication Date: 10/29/2018
Citation: Pugh, N., Han, X., Collins, D., Thomasson, A., Cope, D., Chang, A., Jung, J., Isakeit, T., Prom, L.K., Carvalho, G., Gates, I., Vree, A., Bagnall, G., Rooney, W. 2018. Estimation of plant health in a sorghum field infected with anthracnose using a fixed-wing unmanned aerial system. Journal of Crop Improvement. 32(6):861-877. https://doi.org/10.1080/15427528.2018.1535462.
DOI: https://doi.org/10.1080/15427528.2018.1535462

Interpretive Summary: Anthracnose is one the most common fungal diseases of sorghum and can cause yield losses of up to 100% in infected fields. Field identification of resistance sources can be labor intensive. The use of fixed-wing unmanned aerial system (UAS) to detect early infection correlated with ground-truth, and the association was stronger between ground-truth and fixed-wing UAS later in the growing season. This is significant because it showed that UAS can potentially be effective for evaluating anthracnose disease presence in sorghum, and the greater range of the UAS allows the effective evaluation of larger numbers than ground truth or traditional remote sensing methods.

Technical Abstract: Diseases cause enormous losses of yield and quality for crop producers worldwide. To meet future food demands, crops are bred for resistance to as many of these maladies as possible. One such disease, anthracnose [Colletotrichum sublineola] is a fungal disease of great importance to sorghum [Sorghum bicolor, L. Moench] production because it causes significant annual economic losses in the crop. Breeding for anthracnose resistance requires time-consuming phenotyping which is subjective and conditional to the evaluator. It is possible that quantitative assessment using high-throughput methodologies to estimate the trait may be more effective. In this study, we present an in-depth statistical analysis of fixed-wing UAS evaluation of anthracnose incidence and severity in sorghum using normalized difference vegetation index. In early phases of infection, correlations between ground-truth and UAS estimates of anthracnose are moderate but they increase to very high by the end of the season (r = -0.55 – -0.95). Additionally, both metrics have moderate to high repeatabilities throughout the growth period (R = 0.60 – 0.90), indicating they are consistently able to differentiate genotypes. Finally, we find that the UAS-derived measurements (R2 = 0.377, 0.473) are better associated with ground-truth measurements (R2 = 0.278, 0.347) for grain yield under anthracnose pressure. The results of this study indicate that fixed-wing UAS can potentially be effective for evaluating anthracnose disease presence in sorghum, and the greater range of the UAS allows the effective evaluation of larger numbers than ground truth or traditional remote sensing methods.