Abstract
Einkorn wheat (Triticum monococcum L. ssp. monococcum) plays an increasingly important role in agriculture, promoted by organic farming. Although the number of comparative studies about modern and ancient types of wheats is increasing, there are still some knowledge gaps about the nutritional and health benefit differences between ancient and modern bread wheats. The aim of the present study was to compare ancient, traditional and modern wheat cultivars—including a field study and a laboratory stress experiment using vision-based digital image analysis—and to assess the feasibility of imaging techniques. Our study shows that modern winter wheat had better yield and grain quality compared to einkorn wheats, but the latter were not far behind; thus the cultivation of various species could provide a diverse and sustainable agriculture which contributes to higher agrobiodiversity. The results also demonstrate that digital image analysis could be a viable alternate method for the real-time estimation of aboveground biomass and for predicting yield and grain quality parameters. Digital area outperformed other digital variables in biomass prediction in relation to drought stress, but height and Feret’s diameter better correlated with yield and grain quality parameters. Based on these results we suggest that the combination of various vision-based methods could improve the performance estimation of modern and ancient types of wheat in a non-destructive and real-time manner.
Funder
Ministry of Human Capacities
National Research, Development and Innovation Office
National Science Foundation of Hungary
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development
Cited by
3 articles.
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