{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T14:58:15Z","timestamp":1786460295566,"version":"build-2736575974"},"reference-count":107,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100020326","name":"Universidad Nacional de San Agustin de Arequipa","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100020326","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Plant Sci."],"abstract":"<jats:p>\n                    Within the context of climate change, quinoa (\n                    <jats:italic>Chenopodium quinoa<\/jats:italic>\n                    Willd.) is a climate-resilient crop with high nutritional value. The effects of deficit irrigation on quinoa growth and physiological performance under arid conditions remain insufficiently understood. This study evaluated ten quinoa genotypes (two commercial varieties and eight accessions) under two irrigation regimes to identify traits and spectral indices associated with water-stress tolerance. We combined manual phenotyping of agromorphological and physiological traits with multispectral and spectroradiometer measurements to calculate 35 vegetation indices across 13 and 5 dates, respectively. Deficit irrigation reduced plant height (18%), specific leaf area (8%), yield (43%), harvest index (26%), relative water content (7%), and dry matter accumulation (36%), while relative chlorophyll content (SPAD, Soil Plant Analysis Development) and stomatal density increased by 16% and 13%, respectively; accession ACC_23 exhibited the highest water-use efficiency (5.9\u00a0g kg\n                    <jats:sup>-1<\/jats:sup>\n                    ). A univariate analysis of 35 vegetation indices across 13 dates showed that: Health Index(HIV), Normalized Green-Red Difference Index (NGRD), Red-Green Ratio (RG) and Plant Senescence Reflectance Index (PSRI), were the most sensitive, detecting significant differences between irrigation treatments in up to 32 of the 130 possible genotype-by-date comparisons. Integrating remote\u00a0sensing into crop phenotyping represented a significant methodological improvement by enhancing phenotyping efficiency, improving detection of deficit irrigation effects, and facilitating identification of tolerant quinoa genotypes for arid production systems.\n                  <\/jats:p>","DOI":"10.3389\/fpls.2026.1810225","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T12:41:46Z","timestamp":1786452106000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Quinoa genotypes under deficit irrigation: integrating phenotyping and remote sensing for water use efficiency in arid Peru"],"prefix":"10.3389","volume":"17","author":[{"given":"Raquel Shany","family":"Betancur-Choquehuayta","sequence":"first","affiliation":[{"name":"Facultad de Agronom\u00eda, Universidad Nacional de San Agust\u00edn de Arequipa","place":["Arequipa, Peru"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Esther Emiliana","family":"Molina-Gonzales","sequence":"additional","affiliation":[{"name":"Facultad de Agronom\u00eda, Universidad Nacional de San Agust\u00edn de Arequipa","place":["Arequipa, Peru"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dony Javier","family":"Flores-Subeleta","sequence":"additional","affiliation":[{"name":"Facultad de Agronom\u00eda, Universidad Nacional de San Agust\u00edn de Arequipa","place":["Arequipa, Peru"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raymundo O.","family":"Guti\u00e9rrez-Rosales","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias de Ingenier\u00eda, Universidad de Hu\u00e1nuco","place":["Hu\u00e1nuco, Peru"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alberto","family":"Anculle-Arenas","sequence":"additional","affiliation":[{"name":"Facultad de Agronom\u00eda, Universidad Nacional de San Agust\u00edn de Arequipa","place":["Arequipa, Peru"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natty Wilma","family":"Llasaca-Calizaya","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Hist\u00f3rico Sociales, Universidad Nacional de San Agust\u00edn de Arequipa","place":["Arequipa, Peru"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9 Luis","family":"Bustamante-Mu\u00f1oz","sequence":"additional","affiliation":[{"name":"Facultad de Agronom\u00eda, Universidad Nacional de San Agust\u00edn de Arequipa","place":["Arequipa, Peru"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mayela Elizabeth","family":"Mayta-Anco","sequence":"additional","affiliation":[{"name":"Facultad de Agronom\u00eda, Universidad Nacional de San Agust\u00edn de Arequipa","place":["Arequipa, Peru"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,11]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"2455","DOI":"10.1016\/j.biombioe.2011.02.028","article-title":"A review of remote sensing methods for biomass feedstock production","volume":"35","author":"Ahamed","year":"2011","journal-title":"Biomass Bioenergy"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.14832","article-title":"Adaptive mechanisms in quinoa for coping in stressful environments: an update","volume":"11","author":"Ain","year":"2023","journal-title":"PeerJ"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.3390\/plants14131949","article-title":"Pipecolic acid, a drought stress modulator, boosts chlorophyll assimilation, photosynthetic performance, redox homeostasis, and osmotic adjustment of drought-affected Hordeum vulgare L. seedlings","volume":"14","author":"Aktas","year":"2025","journal-title":"Plants"},{"key":"B4","volume-title":"Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements","author":"Allen","year":"1998"},{"key":"B5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.9734\/AJAAR\/2017\/36655","article-title":"Genotype and drought effects on morphological, physiological and yield traits of quinoa (Chenopodium quinoa Willd.)","volume":"3","author":"Al-Naggar","year":"2017","journal-title":"AJAAR"},{"key":"B6","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.tplants.2013.09.008","article-title":"Field high-throughput phenotyping: the new crop breeding frontier","volume":"19","author":"Araus","year":"2014","journal-title":"Trends Plant Sci."},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1016\/j.agwat.2024.108783","article-title":"How do farmers adapt to water scarcity? 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