Nondestructive Quality Measurement of Fruits and Vegetables in the Supply Chain

The decline of relative chlorophyll contents during fruit ripening is considered to be an important indicator of fruit physiological condition. The recent availability of low-cost portable visible spectrum (VIS) spectrometers has spurred research interest towards optical sensing of chlorophyll changes in intact fruit, with many scientists attempting to link the shifts in optical signals, attributed to chlorophyll changes, to different maturity and quality parameters. One of the widely available portable devices for non-destructive estimation of relative chlorophyll contents is the DA meter, which provides a maturity index that is calculated as a difference between absorption at 670 nm (near the chlorophyll-a absorption peak) and 720 nm (background of the spectrum), abbreviated as IAD. In the present study, the evolution of IAD and its relation to starch pattern index (SPI) and fruit flesh firmness (FFF) was monitored in fruit of two cv. ‘Gala’ clones during maturation and storage, aiming to identify a potential existence of a usable IAD range for the assessment and prediction of the optimal harvest window and storage potential. In both clones, canopy positions, fruit sides, and seasons IAD, SPI, and FFF generally changed in a linear fashion over time, but with partially very different slopes, i.e., they were changing at different rates. What all of these parameters had in common was the presence of a very high biological variability, which is typical of apple fruit. Significantly powerful estimations of SPI (r² > 0.7, p < 0.005) and pre- and post-storage FFF (r² > 0.6, p < 0.005) were achieved. However, the very large biological variability could not be neutralized, which means that the predictions always included large confidence intervals of up to 0.46–0.59 units for SPI and 0.82–1.1 kgF FFF, which ultimately makes them unusable for practical applications. Experiments done under real-life conditions in a commercial fruit storage facility on several different fruit batches confirmed that IAD measured at harvest cannot be used indiscriminately for predicting post-storage FFF of cv. ‘Gala’ originating from different orchards. Nevertheless, mean IAD values that were obtained at optimal maturity from samples of the same orchards remained stable over seasons (0.8–1.2), which strongly suggests that, provided that the calibrations and validations are not only cultivar, but also orchard-specific, IAD has a potential for estimating maturity and storability of apple fruit. In this case, IAD could replace standard maturity indices, otherwise it would be suited for use as a supplementary index for determining fruits physiological maturity status. Full article

Water status controls plant physiology and is key to managing vineyard grape quality and yield. Water status is usually estimated by leaf water potential (LWP), which is measured using a pressure chamber; however, this method is difficult, time-consuming, and error-prone. While traditional spectral methods based on leaf reflectance are faster and non-destructive, most are based on vegetation indices derived from satellite imagery (and so only take into account discrete bandwidths) and do not take full advantage of modern hyperspectral sensors that capture spectral reflectance for thousands of wavelengths. We used partial least squares regression (PLSR) to predict LWP from reflectance values (wavelength 350–2500 nm) captured with a field spectroradiometer. We first identified wavelength ranges that minimized regression error. We then tested several common data pre-processing methods to analyze the impact on PLSR prediction precision, finding that derivative pre-processing increased the determination coefficients of our models and reduced root mean squared error (RMSE). The models fitted with raw data obtained their best results at around 1450 nm, while the models with derivative pre-processed achieved their best estimates at 826 nm and 1520 nm. Full article

The goal of this paper is to show that logistic regression is an analytical method of interest to evaluate the marketability of different pepper (Capsicum annuum L.) cultivars. Two studies were conducted on “Italian sweet” pepper cultivars. Fruit samples were introduced in storage chambers and kept at 9 °C and 85–95% relative humidity during the study period. The fruits were evaluated individually and periodically by measuring the deterioration of fruit quality (rot, ageing, etc.). In this study, categorical explanatory variables (rot, etc.) and continuous explanatory variables (days of storage) were integrated and combined to determine the probability of marketability of the fruit. The results show that the binary logistic model is a useful statistical tool to analyse together both categorical and continuous variables in the study of the marketability of pepper cultivars. Full article

Individual sugars were analyzed by High Performance Liquid Chromatography (HPLC) in plum juice samples obtained from “Stanley”, “Vânăt de Italia”, and “Tuleu Gras”. The samples were harvested from the inside and periphery of the crown during six development phases. The aim of the present study was to determine the individual sugars in plum juice by the HPLC and Fourier transform mid-infrared spectroscopy (FT-MIR) methods and to validate them. Our findings were as follows: levels between 0.26–3.73% for fructose, 1.43–1.10% for glucose, and 0.01–10.19% for sucrose. The FT-MIR analyses confirmed the differences between the juice samples, mainly in the spectral region characteristic to sugars which ranged from 900 to 1500 cm⁻¹. FT-MIR coupled with Partial least squares (PLS) was used to develop calibration models for estimating individual plum juice sugars, the predictive characteristics being assessed. The optimal regions and spectral pretreatments were 800–1600 cm⁻¹ and Savitzky Golay first derivative (d1) for fructose, 800–1600 cm⁻¹ for glucose, and 915–1145 cm⁻¹ and second derivative (d2) for sucrose. The selection of optimal spectral zones and pre-treatments led to PLS calibration models with acceptable predictive abilities for glucose, very good for sucrose, and less satisfactory for fructose. Moreover, the FT-MIR results were compared to the HPLC results in external validation tests and reference values included. Full article

Nowadays, consumer awareness of the impact of site of origin and method of production on the quality and safety of foods, and particularly of fresh produce, is driving the research towards developing various techniques to assist present certifications, traceability, and audit procedures. With regard to horticultural produce, consumer preferences have shifted to fruit and vegetables, which are healthy and ecologically produced, and toward processed foods having sustainable or social certifications and with sites of origin clearly reported on the label. Some recent studies demonstrate the potentiality of near infrared (NIR) technology (including hyperspectral imaging) for discriminating fresh and processed horticultural products based on their composition, quality attributes, and origin. These studies principally mention that each biological tissue possesses a fingerprint NIR spectrum, which consists of a unique and characteristic pattern of radiation, distinguishing a particular biological tissue from physically and/or chemically different samples. Particularly, recent studies discriminated apples, wine, wheat kernels, and derived flours based on their geographical origins. Spectral information allowed discrimination among growing methods (organic and conventional) for asparagus and strawberry fruits, and among harvest dates for fennels, table grapes, and artichokes. Moreover, information about freshness and storage days after minimal processing can be obtained. Recent literature and original results will be discussed. From our perspective, present results suggest that these techniques may have a potentiality to increase information about product history, but if and only if the variability captured by the classification models is vast in terms of diverse samples belonging to various cultivars, varieties, harvest times, cultural practices, geographical origins, storage conditions, and maturity stages, while being used as a complementary method to the conventional ones―either to make an initial screening of critical features, or to add to the amount of available information. Lacking the inclusion of these parameters could result in good classification results, but the reliability of the classification in this case would be dubious in terms of assessment of the factor contributing towards correct classification. Full article

The last 10 years of knowledge on near infrared (NIR) applications in the horticultural field are summarized. NIR spectroscopy is considered one of the most suitable technologies of investigation worldwide used as a nondestructive approach to monitoring raw materials and products in several fields. There are different types of approaches that can be employed for the study of key issues for horticultural products. In this paper, an update of the information collected from the main specific International Journals and Symposia was reported. Many papers showed the use of NIR spectroscopy in the horticultural field, and the literature data were grouped per year, per product, and per application, such as studies of direct (chemical composition) and indirect (physical and sensorial) properties (P), process control (PC), and authenticity and classification studies (AC). A mention was made of a recent innovative approach that considers the contribution of water absorption in the study of biological systems. Full article