Conventional digital cameras as a tool for assessing leaf area index and biomass for cereal breeding

• Published in: Journal of integrative plant biology Vol. 56; no. 1; pp. 7 - 14
• Main Authors: Casadesús, Jaume, Villegas, Dolors
• Format: Journal Article
• Language: English
• Published: China (Republic : 1949- ) Blackwell Publishing Ltd 2014; Institute of Food and Agricultural Research and Technology, Lleida 25198, Spain
• Subjects: Biomass; Breeding; cameras; Crops, Agricultural - growth & development; Digital camera; Edible Grain - anatomy & histology; Edible Grain - growth & development; flowering; genotype; image analysis; leaf area index; lighting; photography; Photography - instrumentation; plant breeding; Plant Leaves - anatomy & histology; Seasons; Seeds - growth & development; Sunlight; triticale; vegetation; vegetation index; wheat; 叶面积指数; 工具; 指数和; 数码相机; 生物量; 评估; 谷物; 饲养; vegetation index; leaf area index; plant breeding; image analysis; Digital camera
• ISSN: 1672-9072; 1744-7909
• DOI: 10.1111/jipb.12117

Affordable and easy‐to‐use methods for assessing biomass and leaf area index (LAI) would be of interest in most breeding programs. Here, we describe the evaluation of a protocol for photographic sampling and image analysis aimed at providing low‐labor yet robust indicators of biomass and LAI. In this trial, two genotypes of triticale, two of bread wheat, and four of tritordeum were studied. At six dates during the growing cycle, biomass and LAI were measured destructively, and digital photography was taken on the same dates. Several vegetation indices were calculated from each image. The results showed that repeatable and consistent values of the indices were obtained in consecutive photographic samplings on the same plots. The photographic indices were highly correlated with the destructive measurements, though the magnitude of the correlation was lower after anthesis. This work shows that photographic assessment of biomass and LAI can be fast, affordable, have good repeatability, and can be used under bright and overcast skies. A practical vegetation index derived from pictures is the fraction of green pixels over the total pixels of the image, and as it shows good correlations with all biomass variables, is the most robust to lighting conditions and has easy interpretation.