Cotton boll distribution and yield estimation using three-dimensional point cloud data

Nothabo Dube, Benjamin Bryant, Hamed Sari-Sarraf, Glen L. Ritchie

Research output: Contribution to journalArticlepeer-review

Abstract

Node-by-node boll mapping has been used to determine the effects of several environmental and management strategies, including irrigation rate and cultivar, on cotton (Gossypium hirsutum L.) boll distribution. The advent of consumer 3D digital imaging may make rapid node-by-node mapping of greater acreage possible in the future. Effects of irrigation rate and cultivar on boll distribution were determined from line plots of node-specific boll distribution and boll accumulation estimate data and from vertical box and whisker plots of boll fraction using data collected by a 3D sensor system to rapidly detect open bolls before harvest over three seasons. Differences were observed between the dryland (2018 only), low irrigation, and high irrigation rates in terms of boll fraction and boll accumulation for each cultivar. The low irrigation tended to produce bolls more toward the bottom of the plant, while the high irrigation produced bolls towards the top of the plant. Yield correlation between sensor obtained and manually counted measurements was strong, with r2 values as high as 0.87. Results obtained indicated that differences among irrigation rate and cultivar were identifiable using the sensor system during the 3 yr research study. Similar systems may allow rapid, broad-scale identification of boll distribution and yield in breeding and physiology research in the future, leading to improved identification of elite cultivars and improved management practices in cotton.

Original languageEnglish
Pages (from-to)4976-4989
Number of pages14
JournalAgronomy Journal
Volume112
Issue number6
DOIs
StatePublished - Nov 1 2020

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