Application of near infrared spectroscopy in nondestructive quality inspection of agricultural products

2005 ◽  
Author(s):  
Zhengjun Qiu ◽  
Lei Feng ◽  
Weimin Li ◽  
Yong He
2022 ◽  
Vol 951 (1) ◽  
pp. 012112
Author(s):  
A A Munawar ◽  
Z Zulfahrizal ◽  
R Hayati ◽  
Syahrul

Abstract Cocoa is one of main agricultural products cultivated in many tropical countries and processed onto several derivative products. To determine cocoa beans qualities, laboratory procedures based on solvent extractions were mainly used, however most of them are destructive and may cause environmental pollutions. The main purpose of this present study is to employ near infrared spectroscopy (NIRS) for rapid and non-destructive assessment of cocoa beans in form of fat content. Near infrared spectral data of cocoa bean samples were measured as diffuse reflectance in wavelength range from 1000 to 2500 nm. Reference fat contents were measured using standard laboratory methods. Prediction models were developed using principal component regression with raw and baseline corrected spectra data. The results showed that fat contents of cocoa beans can be predicted and determined with maximum correlation coefficient (r) of 0.89 and ratio prediction to deviation (RPD) index of 2.87 for raw spectra and r of 0.91, RPD of 3.18 for baseline spectra correction. It may conclude that NIRS was feasible to be applied as a rapid and non-destructive method for cocoa bean quality assessment.


DYNA ◽  
2020 ◽  
Vol 87 (213) ◽  
pp. 17-21
Author(s):  
Nathalia María Forero-Cabrera ◽  
Carolina Maria Sánchez-Sáenz

The importance of the selection and classification processes in the industry of agricultural products and the increase in the production of fruits make necessary the development and implementation of new techniques to efficiently perform these tasks. Techniques such as NIR spectroscopy have proved to have potential to accomplish this purpose. The aim of this research was to evaluate the performance of near infrared spectroscopy as a classification tool for agraz (Vaccinium meridionale Swartz), according to its state of maturity. In order to obtainthe classification models, the PCA and SIMCA methods were used. Results were obtained close to 100% accuracy in the classification for maturity stages 4 and 5 and between 81 and 90% for maturity stage 3. The NIR spectroscopy appears as a suitable technique for the classification of fruits of agraz according to their state of maturity.


Sign in / Sign up

Export Citation Format

Share Document