Abstract
BackgroundEinkorn wheat (Triticum monococcum L. subs. 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 are increasing, there are still some knowledge gaps. The aim of the present study was to compare ancient, traditional and modern wheats using novel methods, including field study, laboratory stress experiment and vision-based digital image analysis. The yield and grain quality parameters based on the field experiment were measured with a near-infrared optical laboratory analyser. In order to predict the aboveground biomass production under nutrient deficiency and drought stress, a controlled experiment was set up in a growth chamber. Processing was performed by image segmentation using the Adobe Photoshop CC 20.04.4 Camera RAW 11.2 plug-in. Digital image parameters were determined with the open source software ImageJ and expressed in pixels of projected area, perimeter, bounding rectangle and Feret’s diameter.ResultsWe presented a fast, real-time, non-destructive and low-cost method for estimation of wheat quality. Based on the results, digital area is suitable to estimate aboveground biomass. Digital area outperformed other digital variables in biomass prediction in relation to stress, but height and Feret’s diameter better correlated with yield and grain quality parameters. The developed technique is easy to use to assess the growth and health status of plants. An RGB digital camera is easy to operate and image acquisition can be done at will, meanwhile conventional laboratory instruments are relatively expensive, very expert-intensive and time consuming.ConclusionOur study showed that digital image analysis could be a viable alternate means for the real-time estimation of aboveground biomass and for predicting yield and grain quality parameters. We suggest that the combination of various vision-based methods could improve the estimation of wheat performance in a non-destructive and real-time way. The results also demonstrated that modern wheats had better yield production 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.
Wheat Quality Estimation Using Vision-Based Digital Image Analysis
