Phenotyping for Effects of Drought Levels in Quinoa Using Remote Sensing Tools
Author:
Lupa-Condo Nerio E.1ORCID, Lope-Ccasa Frans C.1, Salazar-Joyo Angel A.1, Gutiérrez-Rosales Raymundo O.2, Jellen Eric N.3ORCID, Hansen Neil C.3, Anculle-Arenas Alberto1ORCID, Zeballos Omar1ORCID, Llasaca-Calizaya Natty Wilma4, Mayta-Anco Mayela Elizabeth1ORCID
Affiliation:
1. Facultad de Agronomía, Universidad Nacional de San Agustín de Arequipa, Arequipa 04001, Peru 2. Facultad de Ingeniería Agrícola, Universidad Nacional Agraria de La Molina, Lima 15012, Peru 3. Department of Plant and Wildlife Sciences, College of Life Sciences, Brigham Young University, Provo, UT 84602, USA 4. Facultad de Ciencias Histórico Sociales, Universidad Nacional de San Agustín de Arequipa, Arequipa 04001, Peru
Abstract
Drought is a principal limiting factor in the production of agricultural crops; however, quinoa possesses certain adaptive and tolerance factors that make it a potentially valuable crop under drought-stress conditions. Within this context, the objective of the present study was to evaluate morphological and physiological changes in ten quinoa genotypes under three irrigation treatments: normal irrigation, drought-stress followed by recovery irrigation, and terminal drought stress. The experiments were conducted at the UNSA Experimental Farm in Majes, Arequipa, Peru. A series of morphological, physiological, and remote measurements were taken, including plant height, dry biomass, leaf area, stomatal density, relative water content, selection indices, chlorophyll content via SPAD, multispectral imaging, and reflectance measurements via spectroradiometry. The results indicated that there were numerous changes under the conditions of terminal drought stress; the yield variables of total dry biomass, leaf area, and plant height were reduced by 69.86%, 62.69%, and 27.16%, respectively; however, under drought stress with recovery irrigation, these changes were less pronounced with a reduction of 21.10%, 27.43%, and 17.87%, respectively, indicating that some genotypes are adapted or tolerant of both water-limiting conditions (Accession 50, Salcedo INIA and Accession 49). Remote sensing tools such as drones and spectroradiometry generated reliable, rapid, and precise data for monitoring stress and phenotyping quinoa and the optimum timing for collecting these data and predicting yield impacts was from 79–89 days after sowing (NDRE and CREDG r Pearson 0.85).
Funder
Universidad Nacional de San Agustín de Arequipa
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