Reflectance spectroscopy predicts leaf functional traits across wine grape cultivars

作者：Boya Cui, Rachel. O. Mariani, Kimberley A. Cathline, Gavin Robertson, Adam R. Martin · 发表于：Plants People Planet · 年份：2025 · DOI：10.1002/ppp3.70024 · 被引用次数：4 · 研究领域：Horticultural and Viticultural Research、Fermentation and Sensory Analysis、Plant and animal studies

Societal Impact Statement Characterizing variability in crop traits is key for understanding agroecosystem responses to environmental change. However, trait data are often time‐consuming to collect and therefore still limit our understanding and predictions of agriculture responses to environmental change. We tested the ability of reflectance spectroscopy—a high‐throughput technique—to rapidly amass trait data for multiple wine grape cultivars. Reflectance spectroscopy predicts important wine grape leaf traits including photosynthesis and biochemistry with a good degree accuracy, but in a fraction of the time compared to traditional techniques. Reflectance spectroscopy can therefore rapidly characterize wine grape phenotypes and, in doing so, inform predictions of how vines, clones and cultivars will respond to environmental change. Summary Reflectance spectroscopy has emerged as a powerful tool for non‐destructive and high‐throughput phenotyping in plants. While the ability of reflectance spectroscopy to predict traits across diverse plant species and ecosystems has received considerable attention, whether or not this technique is able to quantify within species trait variation—especially physiological traits—has been less extensively explored. Quantifying intraspecific variation in traits through reflectance spectroscopy is especially appealing in agroecology, where it may present an approach for better understanding crop performance, fitness and trait‐based responses to en...