Kiwifruit flesh firmness determination by a NIR sensitive device and image multivariate data analyses
| Autor: | Luigi Ragni, Alessandro Benelli, Annachiara Berardinelli, Marco Tartagni |
|---|---|
| Přispěvatelé: | Berardinelli A., Benelli A., Tartagni M., Ragni L. |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
010302 applied physics
Multivariate statistics Pixel Xenon lamp Flesh Optical measurements Metals and Alloys Infrared-sensitive camera 02 engineering and technology 021001 nanoscience & nanotechnology Condensed Matter Physics 01 natural sciences Grayscale Artificial neural networks (ANN) Surfaces Coatings and Films Electronic Optical and Magnetic Materials Flesh firmne Partial least squares regression (PLS) 0103 physical sciences Electrical and Electronic Engineering Kiwifruit 0210 nano-technology Biological system Instrumentation Mathematics |
| Popis: | A prototype based on a NIR sensitive camera and a Xenon lamp was set up and used to capture 8 bit gray scale (from 0 = black to 255 = white) image of the radiation that passes through the fruit. The count of the pixels with different gray tone was used to build statistical-mathematical models to correlate and predict the kiwifruit flesh firmness. One hundred sixteen fruits conveniently stored to obtain firmness within a range of penetrometric force from 0.8 N to 87 N, were submitted to the optical measurements. Simple regression between the gray tone having the maximum number of pixels and the firmness shown an exponential correlation with R 2 values of 0.717. On the contrary, the tone uniformity (maximum number of the pixels with the same gray tone) resulted linearly correlated with hardness (R 2 = 0.687). PLS algorithm allowed prediction of the flesh firmness with R 2 of 0.777 (RMSE = 13 N). Artificial neural networks given similar results. Although the current technique not fully satisfies the need of an accurate selection, it could be considered for on-line applications by improving performances (e.g. acting on lamp spectral emissions and camera detection) and with easy mechanical modifications of the sorting lines. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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