Spectral methods for measuring quality changes of fresh fruits and vegetables

 

 

Gamal ElMasry,^1* Atef Nassar,² Ning Wang³ and Clément Vigneault⁴

¹Agricultural Engineering Department, Faculty of Agriculture, Suez Canal University, Ismailia, Egypt

²Plant Science Dept., McGill University, 21111 Ste Anne De Bellevue, QC, Canada

³Biosystems and Agricultural Engineering, Division of Agricultural Sciences and Natural Resources, Oklahoma State University, USA

⁴Agriculture and Agri-Food Canada, 430 Gouin Blvd, Saint-Jean-sur-Richelieu, QC, Canada

 

 

 

Abstract

Purpose of review: One of the most important steps in model development is the validation process. It is thus impossible to develop a model for predicting the quality of horticultural produce throughout the food chain without talking about quality measurement. Visual and chemical methods are either tedious, time or produce consuming, biased or difficult to automate. This paper presents an overview of spectral methods for quality change monitoring and quality evaluation of fruits and vegetables. The number of applications for non-destructive techniques, especially spectral methods, is steadily increasing in the areas of agriculture and food science.

Recent findings: Due to advances in technology and improvements in processing speed, the online implementation of quality monitoring has become increasingly interesting. Numerous methods for quality change evaluation of agricultural products and fresh produce have been developed by different researchers over the past three decades. These methods are based on the detection of various properties that correlate well with certain quality parameters. Spectral technique is one of the most optimising and increasingly growing techniques due to its rapidity, simplicity, safety and low operational costs, as well as its ability to measure multiple attributes simultaneously without monotonous sample preparation. In addition to their rapidity, simplicity, safety and low operational costs, spectral methods offer the great advantage of using intact samples presented directly to the system without any pre-treatment. Essential theory background, configuration, practical aspects and applications in a number of different fields exist. The results of previous research confirmed that spectral methods are well suited for estimating physical and chemical attributes in fruits and vegetables and their spatial distribution in these products, such as firmness, presence of bruises, dry matter, soluble solids content, pH, available acid and sugar content. The fruit industry can benefit from the possibility of performing this non-destructive technique at an early stage of processing without additional laborious chemical analysis. This enables early sorting of produce and thereby improved quality management. The technique was implemented as a key component of computer-integrated manufacturing and provided smart opportunities for various applications not only in horticultural produce industries but also in various food quality monitoring processes in real time.

Directions for future research: Most of the advantages of using spectral methods, besides their rapidity, simplicity, safety and low operational costs, come from the possibility of using intact samples presented directly to the system without any pre-treatment. However, it will be more and more difficult to study the issues involved from a single point of view; multidisciplinary research teams are a necessity. Physiologists must interact with chemists, engineers and statisticians to identify the relationship between the measured attributes and the spectral definition of the signal measured. Determining this relationship will accelerate the process of wavelength determination or optimisation and give a better understanding of the physiological process affecting the produce after harvest based on the environmental conditions. Horticultural produce management systems could gain considerably by reducing losses through knowledge of the initial potential of any produce to reach a given market, while retaining excellent quality. Future research in quality attribute measurement is a key aspect in this domain.

 

Keywords: spectral imaging; VIS-NIR spectroscopy; machine vision; wavelength; quality monitoring

 

Stewart Postharvest Review 2008, 4:3

Published online 01 August 2008

doi: 10.2212/spr.2008.4.3