High‐Throughput Field Phenotyping to Assess Irrigation Treatment Effects in Quinoa

Abstract

Core Ideas Water stress in multiple quinoa varieties were introduced. Remote sensing technologies were evaluated to assess water stress response. Handheld and unmanned aerial system based sensors provided reliable data. Thermal imaging data could capture stress in quinoa varieties. Quinoa (Chenopodium quinoa Willd.) is a crop known for its tolerance to abiotic stress such as drought and salinity. Quinoa is also a versatile superfood, which is gluten‐free and high in protein, vitamins, nutrients, and beneficial antioxidants. Washington State University's quinoa breeding program efforts focus on identification and development of varieties that are resilient to local environmental conditions. In this study, high‐throughput phenotyping techniques were applied to evaluate the performance of quinoa varieties under different irrigation regimes. Handheld multispectral radiometer (Crop Scan), proximal sensing system using ground platform, and remote sensing with unmanned aerial system (UAS) were used to assess the performance of eight quinoa varieties under two irrigation treatments (non‐irrigated and irrigated). Crop Scan data, along with multispectral and thermal infrared images, were acquired at multiple time points at different stages of crop development during the season. In general, the normalized difference vegetation index, water band index, and green normalized difference vegetation index (GNDVI) data extracted from Crop Scan, and GNDVI and canopy temperature data extracted from UAS were able to detect irrigation treatment effects. Comparing the spectral data acquired at multiple scales indicated that Crop Scan data were highly and significantly correlated with remote sensing data (|r| = 0.57–0.85). Rapid data acquisition and the ability to detect differences among varieties under water stress highlight the application of remote sensing techniques as a high‐throughput phenotyping tool to evaluate quinoa.

Seed Composition and Amino Acid Profiles for Quinoa Grown in Washington State

“…Quinoa is grown in a wide range of environments, is resilient to agro-ecological extremes, and is tolerant to several abiotic stressors (e.g., drought, salinity, frost) ( 9 – 11 ). The broad genetic variability and adaptability of quinoa to diverse climates has produced a gene pool that supports the strategic development of germplasm with varying morphological ( 12 ) and physiological ( 13 , 14 ) characteristics, and end-uses ( 15 – 18 ) suitable for adoption in novel agroecological climates worldwide. However, the germplasm pool currently available to facilitate quinoa expansion and adoption in novel production regions is narrow and represents only a small portion of quinoa's genetic diversity.…”

Quinoa Phenotyping Methodologies: An International Consensus

“…Several spectral reflectance indices can be obtained at a high throughput through the use of UAVs. Of these indices, NDVI and green normalized difference vegetation index (GNDVI) have been identified as the most informative for quinoa when assessing irrigation treatment effects [ 136 , 137 ]. Furthermore, spectral reflectance measurements have been identified as the most effective tool in the assessment of disease impacts in quinoa [ 138 ].…”

Morphological and Physiological Traits Associated with Yield under Reduced Irrigation in Chilean Coastal Lowland Quinoa

“…Nevertheless, we were unable to make clear distinctions between quinoa lines employing profligate or conservative water-use strategies [ 86 ] using the data collected in this trial via more traditional methods, as the frequency and number of measurements were relatively low. Canopy temperature and vegetation indices collected using handheld, ground-based or remote sensors could distinguish irrigated from non-irrigated treatments in a study by Sankaran et al [ 38 ]. A significant relationship between water availability and canopy temperature was also detected for a selection of quinoa genotypes grown under different water regimes in the Brazilian Cerrado region [ 70 ].…”

“…Screening of genotypes for pre-breeding can be facilitated by using more high-throughput phenotyping methods to measure photosynthetic status, spectral reflectance and canopy temperature [ 35 , 36 ]. These methods, in particular vegetation indices based on spectral reflectance measurements, have recently begun to be applied in quinoa research on drought stress [ 37 , 38 ].…”