Non-destructive characterization and volume estimation of pomegranate fruit external and internal morphological fractions using X-ray computed tomography

Persimmon preservation using edible coating of chitosan enriched with ginger oil and visualization of internal structure changes using X-ray computed tomography

The incorporation of ginger oil (GO) influenced the physical, optical, and structural properties of the chitosan (CH) film including the decreases of moisture content (60.15 %), water solubility (35.37 %) and water vapor permeability (WVP) (32.79 %) and the increases of tensile strength (TS) (125 %), elongation at break (EAB) (2.74 %) and opacity (131.08 %). Antifungal capacity of the CH film was enhanced when GO was added to the film. The CH + GO film showed a less homogeneous surface that the presence of the oil droplets on the film surface. Moreover, the CH and CH + GO coatings reduced weight loss of persimmon by 14.87 %, and 21.13 %, respectively, compared to the control. Moisture content loss of the coated CH- and the coated CH + GO- persimmons was decreased by 1.94 % and 4.92 %, respectively, compared to that of the control persimmon. Furthermore, the CH and CH + GO coatings decreased in color changes, respiration rate, ethylene production, changes in pH and TSS, and remained firmness of persimmon during storage at 25 °C. In addition, X-ray CT images can be used to monitor internal changes and observe the tissue breakdown during storage period. The ΔGS value can be used as a predictor of persimmon internal qualities. Thus, the CH film containing GO can be applied as an active packaging material.

Unraveling the Mechanism of Cork Spot-like Physiological Disorders in 'Kurenainoyume' Apples Based on Occurrence Location

Cork spot-like physiological disorder (CSPD) is a newly identified issue in 'Kurenainoyume' apples, yet its mechanism remains unclear. To investigate CSPD, we conducted morphological observations on 'Kurenainoyume' apples with and without pre-harvest fruit-bagging treatment using light-impermeable paper bags. Non-bagged fruit developed CSPD in mid-August, while no CSPD symptoms were observed in bagged fruit. The bagging treatment significantly reduced the proportion of opened lenticels, with only 17.9% in bagged fruit compared to 52.0% in non-bagged fruits. In non-bagged fruit, CSPD spots tended to increase from the lenticels, growing in size during fruit development. The cuticular thickness and cross-sectional area of fresh cells in CSPD spots were approximately 16 µm and 1600 µm², respectively. Healthy non-bagged fruit reached these values around 100 to 115 days after full bloom from mid- to late August. Microscopic and computerized tomography scanning observations revealed that many CSPD spots developed at the tips of vascular bundles. Therefore, CSPD initiation between opened lenticels and vascular bundle tips may be influenced by water stress, which is potentially caused by water loss, leading to cell death and the formation of CSPD spots.

Fruit Sizing in Orchard: A Review from Caliper to Machine Vision with Deep Learning

Forward estimates of harvest load require information on fruit size as well as number. The task of sizing fruit and vegetables has been automated in the packhouse, progressing from mechanical methods to machine vision over the last three decades. This shift is now occurring for size assessment of fruit on trees, i.e., in the orchard. This review focuses on: (i) allometric relationships between fruit weight and lineal dimensions; (ii) measurement of fruit lineal dimensions with traditional tools; (iii) measurement of fruit lineal dimensions with machine vision, with attention to the issues of depth measurement and recognition of occluded fruit; (iv) sampling strategies; and (v) forward prediction of fruit size (at harvest). Commercially available capability for in-orchard fruit sizing is summarized, and further developments of in-orchard fruit sizing by machine vision are anticipated.

Non-destructive Evaluation of the Quality Characteristics of Pomegranate Kernel Oil by Fourier Transform Near-Infrared and Mid-Infrared Spectroscopy

The pomegranate kernel oil has gained global awareness due to the health benefits associated with its consumption; these benefits have been attributed to its unique fatty acid composition. For quality control of edible fats and oils, various analytical and calorimetric methods are often used, however, these methods are expensive, labor-intensive, and often require specialized sample preparation making them impractical on a commercial scale. Therefore, objective, rapid, accurate, and cost-effective methods are required. In this study, Fourier transformed near-infrared (FT-NIR) and mid-infrared (FT-MIR) spectroscopy as a fast non-destructive technique was investigated and compared to qualitatively and quantitatively predict the quality attributes of pomegranate kernel oil (cv. Wonderful, Acco, Herskawitz). For qualitative analysis, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) was applied. Based on OPLS-DA, FT-MIR spectroscopy resulted in 100% discrimination between oil samples extracted from different cultivars. For quantitative analysis, partial least squares regression was used for model development over the NIR region of 7,498-940 and 6,102-5,774 cm-1 and provided the best prediction statistics for total carotenoid content (R 2, coefficient of determination; RMSEP, root mean square error of prediction; RPD, residual prediction deviation; R 2 = 0.843, RMSEP = 0.019 g β-carotene/kg, RPD = 2.28). In the MIR region of 3,996-1,118 cm-1, models developed using FT-MIR spectroscopy gave the best prediction statistics for peroxide value (R 2 = 0.919, RMSEP = 1.05 meq, RPD = 3.54) and refractive index (R 2 = 0.912, RMSEP = 0.0002, RPD = 3.43). These results demonstrate the potential of infrared spectroscopy combined with chemometric analysis for rapid screening of pomegranate oil quality attributes.

Influence of fruit bagging technique on the morphometric and biochemical characteristics of two pomegranate varieties (Punica granatum L.)

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The bagging technique shown influence in the size and shape of the pomegranate fruits.

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TSS, MI, glucose, α punicalagin, α + β punicalagin, and ellagic acid was affected by bagging.

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pH, TA, ABTS, DPPH, FRAP, TP, fructose, organic acids, β punicalagin and anthocyanins were not influenced.

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It can be said that bagging can improve fruit quality by reducing external damage.

The pomegranate tree is cultivated and its fruits consumed since ancient times. This tree is typical of the Mediterranean climate, with high thermal demands to mature properly. The main objective of this work was to study the influence of the fruit bagging technique on the morphometric and biochemical characteristics of the pomegranate fruits of two new varieties that are currently cultivated in the Southeast of Spain. The results indicated that the fruit bagging presented a significant effect on the weight, equatorial diameter, height and shape of the fruit, however, it did not show any influence on the peel thickness. No significant differences have been observed in the number of healthy fruits with and without bagging, however, the number of cracked fruits with Cryptoblabes gnidiella damage was higher for the non-bagged fruits. The fruit bagging presented a significant effect on the total soluble solids, maturity index, glucose, α-punicalagin, α + β-punicalagin and ellagic acid, but it did not show influence on pH, acidity, ABTS, DPPH, FRAP, total phenols, fructose, citric, malic, and quinic acid, β-punicalagin and anthocyanins. The internal fruit color was not affected by the bagging, although it did affect the external color of the fruit, and unevenly depending on the variety. Based on the results, it can be said that bagging can improve the quality of the fruit by reducing damage from pests and pathophysiology, and this benefit compensates or even exceeds the negative effects of bagging on peel color.

Non-Invasive Methods for Predicting the Quality of Processed Horticultural Food Products, with Emphasis on Dried Powders, Juices and Oils: A Review

This review covers recent developments in the field of non-invasive techniques for the quality assessment of processed horticultural products over the past decade. The concept of quality and various quality characteristics related to evaluating processed horticultural products are detailed. A brief overview of non-invasive methods, including spectroscopic techniques, nuclear magnetic resonance, and hyperspectral imaging techniques, is presented. This review highlights their application to predict quality attributes of different processed horticultural products (e.g., powders, juices, and oils). A concise summary of their potential commercial application for quality assessment, control, and monitoring of processed agricultural products is provided. Finally, we discuss their limitations and highlight other emerging non-invasive techniques applicable for monitoring and evaluating the quality attributes of processed horticultural products. Our findings suggest that infrared spectroscopy (both near and mid) has been the preferred choice for the non-invasive assessment of processed horticultural products, such as juices, oils, and powders, and can be adapted for on-line quality control. Raman spectroscopy has shown potential in the analysis of powdered products. However, imaging techniques, such as hyperspectral imaging and X-ray computed tomography, require improvement on data acquisition, processing times, and reduction in the cost and size of the devices so that they can be adopted for on-line measurements at processing facilities. Overall, this review suggests that non-invasive techniques have the potential for industrial application and can be used for quality assessment.

High-Throughput Phenotyping of Morphological Seed and Fruit Characteristics Using X-Ray Computed Tomography

Traditional seed and fruit phenotyping are mainly accomplished by manual measurement or extraction of morphological properties from two-dimensional images. These methods are not only in low-throughput but also unable to collect their three-dimensional (3D) characteristics and internal morphology. X-ray computed tomography (CT) scanning, which provides a convenient means of non-destructively recording the external and internal 3D structures of seeds and fruits, offers a potential to overcome these limitations. However, the current CT equipment cannot be adopted to scan seeds and fruits with high throughput. And there is no specialized software for automatic extraction of phenotypes from CT images. Here, we introduced a high-throughput image acquisition approach by mounting a specially designed seed-fruit container onto the scanning bed. The corresponding 3D image analysis software, 3DPheno-Seed&Fruit, was created for automatic segmentation and rapid quantification of eight morphological phenotypes of internal and external compartments of seeds and fruits. 3DPheno-Seed&Fruit is a graphical user interface design and user-friendly software with an excellent phenotype result visualization function. We described the software in detail and benchmarked it based upon CT image analyses in seeds of soybean, wheat, peanut, pine nut, pistachio nut and dwarf Russian almond fruit. R 2 values between the extracted and manual measurements of seed length, width, thickness, and radius ranged from 0.80 to 0.96 for soybean and wheat. High correlations were found between the 2D (length, width, thickness, and radius) and 3D (volume and surface area) phenotypes for soybean. Overall, our methods provide robust and novel tools for phenotyping the morphological seed and fruit traits of various plant species, which could benefit crop breeding and functional genomics.

X-ray computed tomography for quality inspection of agricultural products: A review

The quality of agricultural products relates to the internal structure, which has long been a matter of interest in agricultural scientists. However, inspection methods of the opaque nature of internal information on agricultural products are usually destructive and require sample separation or preparation. X-ray computed tomography (X-ray CT) technology is one of the important nondestructive testing (NDT) technologies without sample separation and preparation. In this study, X-ray CT technology is used to obtain two-dimensional slice images and three-dimensional tomographic images of samples. The purpose of the review was to provide an overview of the working principle of X-ray CT technology, image processing, and analysis. This review aims to focus on the development of the agricultural products (e.g., wheat, maize, rice, apple, beef) and its applications (e.g., internal quality evaluation, microstructure observation, mechanical property measurement, and others) using CT scanner. This paper covers the aspects regarding the advantages and disadvantages of NDT technology, especially the unique advantages and limitations of X-ray CT technology on the quality inspection of agricultural products. Future prospects of X-ray CT technology are also put forward to become indispensable to the quality evaluation and product development on agricultural products.