{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T12:43:12Z","timestamp":1768999392357,"version":"3.49.0"},"reference-count":109,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T00:00:00Z","timestamp":1706659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Bulgarian Ministry of Education and Science","award":["866\/26.11.2020 \u0433"],"award-info":[{"award-number":["866\/26.11.2020 \u0433"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Unmanned aerial vehicles (UAVs) are extensively used to gather remote sensing data, offering high image resolution and swift data acquisition despite being labor-intensive. In contrast, satellite-based remote sensing, providing sub-meter spatial resolution and frequent revisit times, could serve as an alternative data source for phenotyping. In this study, we separately evaluated pan-sharpened Pl\u00e9iades satellite imagery (50 cm) and UAV imagery (2.5 cm) to phenotype durum wheat in small-plot (12 m \u00d7 1.10 m) breeding trials. The Gaussian process regression (GPR) algorithm, which provides predictions with uncertainty estimates, was trained with spectral bands and \u0430 selected set of vegetation indexes (VIs) as independent variables. Grain protein content (GPC) was better predicted with Pl\u00e9iades data at the growth stage of 20% of inflorescence emerged but with only moderate accuracy (validation R2: 0.58). The grain yield (GY) and protein yield (PY) were better predicted using UAV data at the late milk and watery ripe growth stages, respectively (validation: R2 0.67 and 0.62, respectively). The cumulative VIs (the sum of VIs over the available images within the growing season) did not increase the accuracy of the models for either sensor. When mapping the estimated parameters, the spatial resolution of Pl\u00e9iades revealed certain limitations. Nevertheless, our findings regarding GPC suggested that the usefulness of pan-sharpened Pl\u00e9iades images for phenotyping should not be dismissed and warrants further exploration, particularly for breeding experiments with larger plot sizes.<\/jats:p>","DOI":"10.3390\/rs16030559","type":"journal-article","created":{"date-parts":[[2024,1,31]],"date-time":"2024-01-31T09:56:34Z","timestamp":1706694994000},"page":"559","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Preharvest Durum Wheat Yield, Protein Content, and Protein Yield Estimation Using Unmanned Aerial Vehicle Imagery and Pl\u00e9iades Satellite Data in Field Breeding Experiments"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9265-9539","authenticated-orcid":false,"given":"Dessislava","family":"Ganeva","sequence":"first","affiliation":[{"name":"Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}]},{"given":"Eugenia","family":"Roumenina","sequence":"additional","affiliation":[{"name":"Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4821-8231","authenticated-orcid":false,"given":"Petar","family":"Dimitrov","sequence":"additional","affiliation":[{"name":"Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}]},{"given":"Alexander","family":"Gikov","sequence":"additional","affiliation":[{"name":"Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1211-991X","authenticated-orcid":false,"given":"Violeta","family":"Bozhanova","sequence":"additional","affiliation":[{"name":"Field Crops Institute, Agricultural Academy, 6200 Chirpan, Bulgaria"}]},{"given":"Rangel","family":"Dragov","sequence":"additional","affiliation":[{"name":"Field Crops Institute, Agricultural Academy, 6200 Chirpan, Bulgaria"}]},{"given":"Georgi","family":"Jelev","sequence":"additional","affiliation":[{"name":"Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6554-7435","authenticated-orcid":false,"given":"Krasimira","family":"Taneva","sequence":"additional","affiliation":[{"name":"Field Crops Institute, Agricultural Academy, 6200 Chirpan, Bulgaria"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1648","DOI":"10.1093\/nutrit\/nuab084","article-title":"Grains\u2014A Major Source of Sustainable Protein for Health","volume":"80","author":"Poutanen","year":"2022","journal-title":"Nutr. 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