TITLE:
Use of Unmanned Aerial System (UAS) Phenotyping to Predict Pod and Seed Yield in Organic Peanuts
AUTHORS:
Aurora Manley, Waltram Ravelombola, John Cason, Brian Bennett, Hanh Pham, Emi Kimura, Caroline Ruhl, Waqas Ahmad, Madeline Brown
KEYWORDS:
Peanut, Unmanned Aerial System, Vegetation Indices, Phenotyping, Pod Yield, Seed Yield
JOURNAL NAME:
American Journal of Plant Sciences,
Vol.14 No.3,
March
31,
2023
ABSTRACT: Peanut (Arachis hypogaea L.) is
a highly nutritious food that is an excellent source of protein and is
associated with increased coronary health, lower risk of type-2 diabetes, lower
risk of breast cancer and a healthy profile of inflammatory biomarkers. The
domestic demand for organic peanuts has significantly increased, requiring new
breeding efforts to develop peanut varieties adapted to the organic farming system. The use of unmanned aerial
system (UAS) has gained scientific attention because of the ability to generate
high-throughput phenotypic data. However, it has not been fully investigated
for phenotyping agronomic traits of organic peanuts. Peanuts are beneficial for
cardio system protection and are widely used. Within the U.S., peanuts are
grown in 11 states on roughly 600,000 hectares and averaging 4500 kg/ha. This
study’s objective was to test the accuracy of UAS data in the phenotyping pod and seed yield of organic peanuts.
UAS data was collected from a field plot with 20 Spanish peanut breeding lines
on July 07, 2021 and September 27, 2021. The study was a randomized complete
block design (RCBD) with 3 blocks. Twenty-five vegetation indices (VIs) were
calculated. The analysis of variance showed significant genotypic effects on
all 25 vegetation indices for both flights (p r = 0.44) and
seed yield (r = 0.64). These results can be used to further advance
organic peanut breeding efforts with high-throughput data collection.