Is Einkorn Wheat ( Triticum monococcum L.) a Better Choice than Winter Wheat ( Triticum aestivum L.)? Wheat Quality Estimation for Sustainable Agriculture Using Vision-Based Digital Image Analysis

Edina Csákvári, Melinda Halassy, Attila Enyedi, Ferenc Gyulai and József Berke
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Edina Csákvári: Environmental Sciences Doctoral School, Hungarian University of Agriculture and Life Sciences, Páter Károly u. 1, 2100 Gödöllő, Hungary
Melinda Halassy: ELKH Centre for Ecological Research, Institute of Ecology and Botany, Alkotmány u. 2-4, 2163 Vácrátót, Hungary
Attila Enyedi: Institute of Information Technology, Dennis Gabor College, Fejér Lipót u. 70, 1119 Budapest, Hungary
Ferenc Gyulai: Environmental Sciences Doctoral School, Hungarian University of Agriculture and Life Sciences, Páter Károly u. 1, 2100 Gödöllő, Hungary
József Berke: Institute of Information Technology, Dennis Gabor College, Fejér Lipót u. 70, 1119 Budapest, Hungary

Sustainability, 2021, vol. 13, issue 21, 1-16

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.

Keywords: agrobiodiversity; ecological farming; einkorn; winter wheat; RGB image; digital image processing; aboveground biomass (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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