Remote sensing for estimating genetic parameters of biomass accumulation and modeling stability of growth curves in alfalfa

Abstract

Multi-spectral imaging (MSI) collection by unoccupied aerial vehicles (UAV) is an important tool to measure growth of forage crops. Information from estimated growth curves can be used to infer harvest biomass and to gain insights in the relationship of growth dynamics and harvest biomass stability across cuttings and years. In this study, we used MSI to evaluate Alfalfa ( Medicago sativa L. subsp. sativa ) to understand the longitudinal relationship between vegetative indices (VIs) and forage/biomass, as well as evaluation of irrigation treatments and genotype by environment interactions (GEI) of different alfalfa cultivars. Alfalfa is a widely cultivated perennial forage crop grown for high yield, nutritious forage quality for feed rations, tolerance to abiotic stress, and nitrogen fixation properties in crop rotations. The direct relationship between biomass and VIs such as Normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), red edge normalized difference vegetation index (NDRE), and Near infrared (NIR) provide a non-destructive and high throughput approach to measure biomass accumulation over subsequent alfalfa harvests. In this study, we aimed to estimate the genetic parameters of alfalfa VIs and utilize longitudinal modeling of VIs over growing seasons to identify potential relationships between stability in growth parameters and cultivar stability for alfalfa biomass yield across cuttings and years. We found VIs of GNDVI, NDRE, NDVI, NIR and simple ratios to be moderately heritable with median values for the field trial in Ithaca, NY to be 0.64, 0.56, 0.45, 0.45 and 0.40 respectively, Normal Irrigation (NI) trial in Leyendecker, NM to be 0.3967, 0.3813, 0.3751, 0.3239 and 0.3019 respectively, and Summer Irrigation Termination (SIT) trial in Leyendecker, NM to be of 0.11225, 0.1389, 0.1375, 0.2539 and 0.1343, respectively. Genetic correlations between NDVI and harvest biomass ranged from 0.52 - .99 in 2020 and 0.08 - .99 in 2021 in the NY trial. Genetic correlations for NI trial in NM for NDVI ranged from 0.72 - .98 in 2021 and SIT ranged from 0.34-1.0 in 2021. Genotype by genotype by interaction (GGE) biplots were used to differentiate between stable and unstable cultivars for locations NY and NM, and Random regression modeling approaches were used to estimate growth parameters for each cutting. Results showed high correspondence between stability in growth parameters and stability, or persistency, in harvest biomass across cuttings and years. In NM, the SIT trial showed more variation in growth curves due to stress conditions. The temporal growth curves derived from NDVI, NIR and Simple ratio were found to be the best phenotypic indices on studying the stability of growth parameters across different harvests. The strong correlation between VIs and biomass present opportunities for more efficient screening of cultivars, and the correlation between estimated growth parameters and harvest biomass suggest longitudinal modeling of VIs can provide insights into temporal factors influencing cultivar stability.

Plant phenotyping relevance

UAVマルチスペクトル画像から植生指数とバイオマスを推定し、成長曲線・遺伝パラメータ・品種安定性を評価することが研究の中心であり、植物表現型取得と解析手法の実質的な応用に該当する。

Code and data availability

The supplied blocks describe alfalfa UAV multispectral phenotyping, image processing in Pix4D/Imagebreed, and random regression/GGE analyses, but contain no public deposition of the phenotype data, imagery, or analysis code, and no authors' public URL for such assets. Pix4D (https://www.pix4d.com) is a generic third‑p​

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