{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T07:44:09Z","timestamp":1782287049055,"version":"3.54.5"},"reference-count":34,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,18]],"date-time":"2022-06-18T00:00:00Z","timestamp":1655510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the US Department of Agriculture National Institute of Food and Agriculture (USDA-NIFA) competitive projects","award":["1011741"],"award-info":[{"award-number":["1011741"]}]},{"name":"the US Department of Agriculture National Institute of Food and Agriculture (USDA-NIFA) competitive projects","award":["1014919"],"award-info":[{"award-number":["1014919"]}]},{"name":"the US Department of Agriculture National Institute of Food and Agriculture (USDA-NIFA) competitive projects","award":["ERI-20-04"],"award-info":[{"award-number":["ERI-20-04"]}]},{"name":"hatch project","award":["1011741"],"award-info":[{"award-number":["1011741"]}]},{"name":"hatch project","award":["1014919"],"award-info":[{"award-number":["1014919"]}]},{"name":"hatch project","award":["ERI-20-04"],"award-info":[{"award-number":["ERI-20-04"]}]},{"name":"Washington State University\u2019s College of Agricultural, Human, and Natural Resource Sciences\u2019 Emerging Research Issues competitive grant opportunity","award":["1011741"],"award-info":[{"award-number":["1011741"]}]},{"name":"Washington State University\u2019s College of Agricultural, Human, and Natural Resource Sciences\u2019 Emerging Research Issues competitive grant opportunity","award":["1014919"],"award-info":[{"award-number":["1014919"]}]},{"name":"Washington State University\u2019s College of Agricultural, Human, and Natural Resource Sciences\u2019 Emerging Research Issues competitive grant opportunity","award":["ERI-20-04"],"award-info":[{"award-number":["ERI-20-04"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Fruit industries play a significant role in many aspects of global food security. They provide recognized vitamins, antioxidants, and other nutritional supplements packed in fresh fruits and other processed commodities such as juices, jams, pies, and other products. However, many fruit crops including peaches (Prunus persica (L.) Batsch) are perennial trees requiring dedicated orchard management. The architectural and morphological traits of peach trees, notably tree height, canopy area, and canopy crown volume, help to determine yield potential and precise orchard management. Thus, the use of unmanned aerial vehicles (UAVs) coupled with RGB sensors can play an important role in the high-throughput acquisition of data for evaluating architectural traits. One of the main factors that define data quality are sensor imaging angles, which are important for extracting architectural characteristics from the trees. In this study, the goal was to optimize the sensor imaging angles to extract the precise architectural trait information by evaluating the integration of nadir and oblique images. A UAV integrated with an RGB imaging sensor at three different angles (90\u00b0, 65\u00b0, and 45\u00b0) and a 3D light detection and ranging (LiDAR) system was used to acquire images of peach trees located at the Washington State University\u2019s Tukey Horticultural Orchard, Pullman, WA, USA. A total of four approaches, comprising the use of 2D data (from UAV) and 3D point cloud (from UAV and LiDAR), were utilized to segment and measure the individual tree height and canopy crown volume. Overall, the features extracted from the images acquired at 45\u00b0 and integrated nadir and oblique images showed a strong correlation with the ground reference tree height data, while the latter was highly correlated with canopy crown volume. Thus, selection of the sensor angle during UAV flight is critical for improving the accuracy of extracting architectural traits and may be useful for further precision orchard management.<\/jats:p>","DOI":"10.3390\/s22124619","type":"journal-article","created":{"date-parts":[[2022,6,19]],"date-time":"2022-06-19T21:19:26Z","timestamp":1655673566000},"page":"4619","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Optimization and Evaluation of Sensor Angles for Precise Assessment of Architectural Traits in Peach Trees"],"prefix":"10.3390","volume":"22","author":[{"given":"Mugilan Govindasamy","family":"Raman","sequence":"first","affiliation":[{"name":"Department of Biological System Engineering, Washington State University, Pullman, WA 99164, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eduardo Fermino","family":"Carlos","sequence":"additional","affiliation":[{"name":"Department of Biological System Engineering, Washington State University, Pullman, WA 99164, USA"},{"name":"Laboratory of Biotechnology, AMG, IDR-IAPAR-EMATER-Agronomic Institute of Paran\u00e1, Londrina-PR 86001-970, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sindhuja","family":"Sankaran","sequence":"additional","affiliation":[{"name":"Department of Biological System Engineering, Washington State University, Pullman, WA 99164, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2007","DOI":"10.1007\/s11119-021-09813-y","article-title":"Orchard management with small unmanned aerial vehicles: A survey of sensing and analysis approaches","volume":"22","author":"Zhang","year":"2021","journal-title":"Precis. 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