Phenotyping for Effects of Drought Levels in Quinoa Using Remote Sensing Tools

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).

Plant phenotyping relevance

乾燥ストレス実験ではあるが、ドローン、マルチスペクトル画像、分光反射を用いたキヌアの表現型取得とストレス・収量影響のモニタリングが明示され、手法の適時性と予測精度も評価されているため。

Code and data availability

The supplied blocks describe quinoa drought phenotyping with UAV multispectral imaging, spectroradiometry, and R-based analysis, but contain no public phenotype/trait dataset, no deposited images or sensor data, and no authors' analysis code or model release. All referenced URLs (R, corrplot, FactoMineR, factoextra, Ag

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