Abstract
This article describes the development of a fast and inexpensive method based on digital image analysis for the automated quantification of the percentage of defective maize (%DM). Defective kernels tend to foster high levels of mycotoxins like Deoxynivalenol (DON), which represents a risk for the health of humans and of farm animals. In this work, 332 RGB images of 83 mixtures containing different amounts of defective maize kernels were acquired using a digital camera. The mixtures were also analysed with a commercial ELISA test kit to determine their concentration of DON, that resulted highly correlated with the amount of defective kernels. Each image was then converted into a signal, named colourgram, which codifies its colour-related information content. The colourgrams were firstly explored using Principal Component Analysis. Then, calibration models of the %DM values were developed using Partial Least Squares (PLS) and interval PLS. The best interval PLS model allowed to predict the %DM values of external test set samples with a root mean square error value equal to 2.6%. Based on the output of this model it was also possible to highlight the defective-maize areas within the images, confirming the significance of the proposed approach.
Highlights
The great importance of maize (Zea mays L.) is due to its primary role for multiple uses, including human food, livestock feed, biofuels and bioplastics (FAO, 2006)
Concerning the defective maize, the results of ELISA test showed that for both dry and wet types the concentration of DON was greater than the maximum quantification value, equal to 10 ppm
An approach based on multivariate analysis of RGB images for the determination of the percentage of defective maize (%DM) has been presented, that could be used as a fast pre-screening of large maize batches for a preliminary estimate of the degree of maize contamination by DON
Summary
The great importance of maize (Zea mays L.) is due to its primary role for multiple uses, including human food, livestock feed, biofuels and bioplastics (FAO, 2006). Maize mycotoxins can be directly found in the human food or, as animal feed, they are ingested by animals and pass to humans through the food chain. Due to their high toxicity, mycotoxins represent a major risk for human health. The most common mycotoxins in maize are produced by fungi belonging to the genera of Fusarium, Aspergillus and Penicillium (Hossain and Goto, 2014). These microorganisms mainly develop in the field or at the post-harvest stage, when storage conditions are inadequate. Because of the health hazards to humans and animals, the European Parliament has set a limit of 1750 ppb in the unprocessed maize used in foodstuff (Commission Regulation (EC) No 1126/2007), while in the animal feed materials the recommendations generally suggest to not exceed 8 ppm of DON (Commission Directive 2003/100/EC)
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