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An Open Source Conveyor Belt Prototype for Image Analysis-Based Rice Yield Determination

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Abstract

The basic role of industrial rice milling is the transformation of paddy rice into white rice with good appearance while selecting the best quality grain for human consumption. In Italy, the commercial value of paddy rice is assessed calculating whole and free of defect kernel yield after processing. The determination is performed by laboratories utilizing a benchtop yield machine that carries out the husking and kernel bleaching. The aim of the study is the development of a pilot conveyor belt (grain coulter), based on image analysis, to increase the reliability of laboratory yield estimation (discrimination of paddy and white grains). The tests regard rice grains belonging to 26 different genotypes of rice grown in Sardinia (Italy). The low-cost prototype based on open source technologies that aim to substitute the current subjective estimation made by eye with an industrial like optically based one. The method is based on the image analysis and extracts three main qualitative attributes: shape, size (i.e., Fourier descriptors and basic morphometry) and appearance (color), and the use of a multivariate classification technique (i.e., partial least squares discriminant analysis). The models discriminated samples of paddy or white rice for each genotype considered (26 models) and for all the genotypes considered together (1 model). For all the 27 models, the mean sensitivities and specificities were very high, ranging from 99 to 100%, while the mean classification errors were very low. The mean percentage of correct classification in the test set was equal to 99.99% for the “unique model” (i.e., paddy VS white rice) and 100% for the 26 single genotype models. The proposed system appears to be useful not only for paddy and white rice discrimination but also as a flexible apparatus for analyzing many other agro-food products. Indeed, the algorithm was used on other food products, such as red hot chili peppers for other discrimination purposes.

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Acknowledgements

This work was funded by the Italian Ministry of Agriculture, Food and Forestry Policies (MiPAAF), as part of the projects “POLORISO” (D.M. 5337 of December 5th 2011). Authors would like to thank Mr. Stefano Benigni for his help in the preparation of rice samples.

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Authors and Affiliations

  1. Centro di ingegneria e trasformazioni agroalimentari, Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (CREA), Via della pascolare 16, 00015, Monterotondo, Rome, Italy

    F. Antonucci, S. Figorilli, C. Costa, F. Pallottino & P. Menesatti

  2. Dipartimento di Agraria, Università degli Studi di Sassari, Piazza Università 21, 07100, Sassari, Italy

    A. Spanu

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  1. F. Antonucci
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  2. S. Figorilli
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  3. C. Costa
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  4. F. Pallottino
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  5. A. Spanu
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  6. P. Menesatti
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Correspondence to C. Costa.

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Antonucci, F., Figorilli, S., Costa, C. et al. An Open Source Conveyor Belt Prototype for Image Analysis-Based Rice Yield Determination. Food Bioprocess Technol 10, 1257–1264 (2017). https://doi.org/10.1007/s11947-017-1895-2

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