Machine Learning Application in Horticulture and Prospects for Predicting Fresh Produce Losses and Waste: A Review.

The current review examines the state of knowledge and research on machine learning (ML) applications in horticultural production and the potential for predicting fresh produce losses and waste. Recently, ML has been increasingly applied in horticulture for efficient and accurate operations. Given the health benefits of fresh produce and the need for food and nutrition security, efficient horticultural production and postharvest management are important. This review aims to assess the application of ML in preharvest and postharvest horticulture and the potential of ML in reducing postharvest losses and waste by predicting their magnitude, which is crucial for management practices and policymaking in loss and waste reduction. The review starts by assessing the application of ML in preharvest horticulture. It then presents the application of ML in postharvest handling and processing, and lastly, the prospects for its application in postharvest loss and waste quantification. The findings revealed that several ML algorithms perform satisfactorily in classification and prediction tasks. Based on that, there is a need to further investigate the suitability of more models or a combination of models with a higher potential for classification and prediction. Overall, the review suggested possible future directions for research related to the application of ML in postharvest losses and waste quantification.

Vis-NIR and SWIR hyperspectral imaging method to detect bruises in pomegranate fruit.

Introduction: Fresh pomegranate fruit is susceptible to bruising, a common type of mechanical damage during harvest and at all stages of postharvest handling. Accurate and early detection of such damages in pomegranate fruit plays an important role in fruit grading. This study investigated the detection of bruises in fresh pomegranate fruit using hyperspectral imaging technique. Methods: A total of 90 sample of pomegranate fruit were divided into three groups of 30 samples, each representing purposefully induced pre-scanning bruise by dropping samples from 100 cm and 60 cm height on a metal surface. The control has no pre-scanning bruise (no drop). Two hyperspectral imaging setups were examined: visible and near infrared (400 to 1000 nm) and short wavelength infrared (1000 to 2500 nm). Region of interest (ROI) averaged reflectance spectra was implemented to reduce the image data. For all hypercubes a principal components analysis (PCA) based background removal were done prior to segmenting the region of interest (ROI) using the Evince® multi-variate analysis software 2.4.0. Then the average spectrum of the ROI of each sample was computed and transferred to the MATLAB 2022a (The MathWorks, Inc., Mass., USA) for classification. A two-layer feed-forward artificial neural network (ANN) is used for classification. Results and discussion: The accuracy of bruise severity classification ranged from 80 to 96.7%. When samples from both bruise severity (Bruise damage induced from a 100cm and 60 cm drop heights respectively) cases were merged, class recognition accuracy were 88.9% and 74.4% for the SWIR and Vis-NIR, respectively. This study implemented the method of selecting out informative bands and disregarding the redundant ones to decreases the data size and dimension. The study developed a more compact classification model by the data dimensionality reduction method. This study demonstrated the potential of using hyperspectral imaging technology in sensing and classification of bruise severity in pomegranate fruit. This work provides the foundation to build a compact and fast multispectral imaging-based device for practical farm and packhouse applications.

Feature Reduction for the Classification of Bruise Damage to Apple Fruit Using a Contactless FT-NIR Spectroscopy with Machine Learning.

Spectroscopy data are useful for modelling biological systems such as predicting quality parameters of horticultural products. However, using the wide spectrum of wavelengths is not practical in a production setting. Such data are of high dimensional nature and they tend to result in complex models that are not easily understood. Furthermore, collinearity between different wavelengths dictates that some of the data variables are redundant and may even contribute noise. The use of variable selection methods is one efficient way to obtain an optimal model, andthis was the aim of this work. Taking advantage of a non-contact spectrometer, near infrared spectral data in the range of 800-2500 nm were used to classify bruise damage in three apple cultivars, namely 'Golden Delicious', 'Granny Smith' and 'Royal Gala'. Six prominent machine learning classification algorithms were employed, and two variable selection methods were used to determine the most relevant wavelengths for the problem of distinguishing between bruised and non-bruised fruit. The selected wavelengths clustered around 900 nm, 1300 nm, 1500 nm and 1900 nm. The best results were achieved using linear regression and support vector machine based on up to 40 wavelengths: these methods reached precision values in the range of 0.79-0.86, which were all comparable (within error bars) to a classifier based on the entire range of frequencies. The results also provided an open-source based framework that is useful towards the development of multi-spectral applications such as rapid grading of apples based on mechanical damage, and it can also be emulated and applied for other types of defects on fresh produce.

Mechanical damages and packaging methods along the fresh fruit supply chain: A review.

Mechanical damage of fresh fruit occurs throughout the postharvest supply chain leading to poor consumer acceptance and marketability. In this review, the mechanisms of damage development are discussed first. Mathematical modeling provides advanced ways to describe and predict the deformation of fruit with arbitrary geometry, which is important to understand their mechanical responses to external forces. Also, the effects of damage at the cellular and molecular levels are discussed as this provides insight into fruit physiological responses to damage. Next, direct measurement methods for damage including manual evaluation, optical detection, magnetic resonance imaging, and X-ray computed tomography are examined, as well as indirect methods based on physiochemical indexes. Also, methods to measure fruit susceptibility to mechanical damage based on the bruise threshold and the amount of damage per unit of impact energy are reviewed. Further, commonly used external and interior packaging and their applications in reducing damage are summarized, and a recent biomimetic approach for designing novel lightweight packaging inspired by the fruit pericarp. Finally, future research directions are provided.HIGHLIGHTSMathematical modeling has been increasingly used to calculate damage to fruit.Cell and molecular mechanisms response to fruit damage is an under-explored area.Susceptibility measurement of different mechanical forces has received attention.Customized design of reusable and biodegradable packaging is a hot topic of research.

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 ß-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.

Antioxidant, Antimicrobial, and Metabolomic Characterization of Blanched Pomegranate Peel Extracts: Effect of Cultivar.

Hot water blanching at 80 °C for 3 min can be used as a novel pre-treatment step in pomegranate peel to preserve the integrity of the phytochemical content within the peel extracts by lowering or inactivating enzymes such as polyphenol (PPO) oxidase and peroxidase (POD) that are responsible for the break-down of phytochemicals within the peel. The aim of this study was to investigate the effect of hot water blanching pre-treatment on yield, bioactive compounds, antioxidants, enzyme inactivation, and antibacterial activity of 'Wonderful', 'Acco', and 'Herskawitz' pomegranate peel extracts. We used a variety of spectrophotometric-based assays and liquid chromatography mass spectrometry (LC-MS)-based approach to characterize and quantify metabolites within the peel extracts. Blanching significantly (p < 0.05) reduced PPO activity in all peel extracts, with the highest PPO reduction in 'Herskawitz' peel extracts at 0.25 U/mL. Furthermore, higher antioxidant activity in 'Herskawitz' blanched peel extracts using 2,2-diphenyl-1-picryl hydrazyl (DPPH) antioxidant activity, ferric ion reducing antioxidant power (FRAP), and 2,2-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid (ABTS) radical scavenging activity at 567.78 ± 9.47 µmol Trolox/g DM, 800.05 ± 1.60 µmol Trolox/g DM, and 915.27 ± 0.61 µmol Trolox/g DM, respectively, was noted. 'Herskawitz' blanched peel extracts were recorded with the lowest minimum inhibitory concentration (MIC) value of 80 µg/mL for Gram-positive Bacillus subtilis and Gram-negative Klebsiella pneumoniae bacteria strains. A total of 30 metabolites were present in 'Acco' and 'Herskawitz' peel extracts and were tentatively identified after LC-MS profiling. This study demonstrates that blanched peel extracts from 'Herskawitz' cultivar have great potential for commercial use in value-added products in the nutraceutical, cosmeceutical, and pharmacological industries.

Changes in Volatile Composition of Cape Hake Fillets under Modified Atmosphere Packaging Systems during Cold Storage.

Fresh ready-to-cook fish fillets are susceptible to loss of freshness and accumulation of off-odour due to accelerated microbial spoilage. Suboptimal storage temperature and packaging conditions accelerate this process, limiting the economic potential. This study investigated the effects of modified atmosphere packaging (MAP) and storage temperature (0 °C and 4 °C) on the volatile compounds (VOCs) of Cape hake (Merluccius capensis) fish fillets as a predictor of shelf life and quality. Fresh Cape hake fillets were packaged under active modified atmosphere (40% CO2 + 30% O2 + 30% N2) and passive modified atmosphere (0.039% CO2 + 20.95% O2 + 78% N2) with or without an absorbent pad and stored at 0 °C and 4 °C for 12 d. The results obtained demonstrated that changes in VOCs and concentration were significantly (p < 0.05) influenced by MAP conditions, storage temperature and duration. A total of 16 volatiles were identified in the packaged Cape hake fillets: 4 primary VOCs and 12 secondary VOCs. The spoilage VOCs identified include tri-methylamine (TMA) (ammonia-like), esters (sickeningly sweet) and sulphur group (putrid). The concentration of secondary VOCs increased continuously during storage. Active-MA-packaged fillets performed better and had lower TMA values of 0.31% at 0 °C on day 12 in comparison to 7.22% at 0 °C under passive on day 6. Ethyl acetate was detected in passive-MA-packaged fillets stored at 0 °C on day 3, and the levels increased to 3.26% on day 6, while active-MA-packaged fillets maintained freshness. This study showed that in conjunction with TMA, VOCs such as esters and sulphur-related compounds could be used as spoilage markers for Cape hake fish fillets.

Effects of Gum Arabic Coatings Enriched with Lemongrass Essential Oil and Pomegranate Peel Extract on Quality Maintenance of Pomegranate Whole Fruit and Arils.

The effects of gum arabic coatings combined with lemongrass oil and/or pomegranate peel extract on freshly harvested mature 'Wonderful' pomegranate fruit were studied. Fruit were coated with gum arabic (GA) (1.5% w/v) alone or enriched with lemongrass oil (LM) (0.1% v/v) and/or pomegranate peel extract (PP) (1% w/v). Fruit were packed into standard open top ventilated cartons (dimensions: 0.40 m long, 0.30 m wide and 0.12 m high), and stored for 6 weeks at 5 ± 1 °C (90% RH). Evaluations were made every 2 weeks of cold storage and after 5 d of shelf life (20 °C and 65% RH). Fruit coated with GA + PP (4.09%) and GA + PP + LM (4.21%) coatings recorded the least cumulative weight loss compared to the uncoated control (9.87%). After 6 weeks, uncoated control and GA + PP + LM recorded the highest (24.55 mg CO2Kg-1h-1) and lowest (10.76 mg CO2Kg-1h-1) respiration rate, respectively. Coating treatments reduced the incidence of decay and treatments GA + LM + PP and GA + PP recorded the highest total flavonoid content between 2 and 6 weeks of storage. The findings suggest that GA coatings with/without LM and PP can be a beneficial postharvest treatment for 'Wonderful' pomegranates to reduce weight loss and decay development during cold storage.

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.

Classification of Browning on Intact Table Grape Bunches Using Near-Infrared Spectroscopy Coupled With Partial Least Squares-Discriminant Analysis and Artificial Neural Networks.

Table grape browning is a complex physiological disorder that occurs during cold storage. There is a need to investigate novel and innovative ways to manage the problem that hampers the progressive and sustainable growth of table grape industries. Given the complex nature of the browning phenomenon, techniques such as near-infrared (NIR) spectroscopy can be utilized for the non-destructive classification of different browning phenotypes. In this study, NIR coupled with partial least squares discriminant analysis (PLS-DA) and artificial neural networks (ANN) were used to classify bunches as either clear or as having chocolate browning and friction browning based on the spectra obtained from intact 'Regal Seedless' table grape bunches that were cold-stored over different periods. Friction browning appears as circular spots close to the pedicel area that are formed when table grape berries move against each other, and chocolate browning appears as discoloration, which originates mostly from the stylar-end of the berry, although the whole berry may appear brown in severe instances. The evaluation of the models constructed using PLS-DA was done using the classification error rate (CER), specificity, and sensitivity and for the models constructed using ANN, the kappa score was used. The CER for chocolate browning (25%) was better than that of friction browning (46%) for weeks 3 and 4 for both class 0 (absence of browning) and class 1 (presence of browning). Both the specificity and sensitivity of class 0 and class 1 for friction browning were not as good as that of chocolate browning. With ANN, the kappa score was tested to classify table grape bunches as clear or having chocolate browning or friction browning and showed that chocolate browning could be classified with a strong agreement during weeks 3 and 4 and weeks 5 and 6 and that friction browning could be classified with a moderate agreement during weeks 3 and 4. These results open up new possibilities for the development of quality checks of packed table grape bunches before export. This has a significant impact on the table grape industry for it will now be possible to evaluate bunches non-destructively during packaging to determine the possibility of these browning types being present when reaching the export market.

Novel seeds pretreatment techniques: effect on oil quality and antioxidant properties: a review.

Seed oil quality is a function of several attributes which include its bioactive compounds, physicochemical and functional properties. These quality attributes are important in seed oil processing as they determine the oil palatability, nutritional and market value. Besides the health, environmental and economic issues related to seed oil extraction using organic solvents such as hexane, other conventional seed oil extraction techniques such as supercritical fluid extraction, enzyme digestion and cold pressing are associated with low recovery of oil and bioactive compounds. Application of novel seeds pretreatments techniques such as microwaving, enzymatic digestion, pulsed electric field and ultrasonication do not only improve the oil yield and quality attributes, but also reduces seed oil extraction time, solvent and energy consumption. Higher phenolic compounds, carotenoids, tocopherols, phytosterols and antioxidant properties in oil from pretreated seeds offer health benefits related to the prevention of cancer, diabetes, obesity, inflammatory and cardiovascular diseases. Increased consumer interest in functional foods and the potential of seeds pretreatments in enhancing the extractability of bioactive compounds from plant material has increased the application of novel pretreatment techniques on diverse oilseeds. This review describes the commonly studied novel seeds pretreatment techniques and critically discusses their influence on the oil physicochemical attributes, oxidation indices, bioactive compounds and antioxidant properties.

Effect of Different Extraction Methods on the Quality and Biochemical Attributes of Pomegranate Juice and the Application of Fourier Transformed Infrared Spectroscopy in Discriminating Between Different Extraction Methods.

This study investigated the effects of extraction methods on the physicochemical, phytochemical, and antioxidant properties of pomegranate juice (cv. Wonderful). In addition, the application of attenuated total reflectance Fourier transformed mid-infrared (ATR-FT-MIR) spectroscopy and chemometrics were explored in order to discriminate between different extraction methods. Juice variants evaluated included juice extracted without crushing the seeds (arils only) using a juice extractor (JE), juice extracted by crushing the seeds using a blender (arils plus seed) (JB), and juice extracted from half fruit using a commercial hand press juicer (CH). Juice extracted from CH had higher total soluble solid (TSS) content (18.20%), TSS/TA ratio (15.83), and color properties (a* = 32.67, b* = 11.80, C* = 34.77) compared with extraction methods JE and JB. The juice extracted from JB showed the highest titratable acidity (2.17%), cloudiness (0.43), and lowest pH value (2.69). The total phenolics and anthocyanin content in the investigated juice ranged from 1.87 to 3.04 g gallic acid equivalent (GAE)/L and 37.74-43.67 mg cyanidin 3-glucoside equivalent/L of crude juice, respectively. Juice extracted from JB and CH was significantly higher in phenolic and anthocyanin compared with JE. Orthogonal partial least squares discriminant analysis (OPLS-DA) and principal component analysis (PCA) were used for classification. Classification accuracy of 100% was achieved between the three methods. The S-line plot revealed that the corresponding wavelength bands within the following regions 1,090, 1,250, 1,750, and 3,200 cm-1 were responsible for discrimination between the different extraction methods. Our results suggest that the main contributor to the discrimination between extraction methods were TSS, TSS/TA, color attributes, and anthocyanin content. Overall, this study has demonstrated that ATR-FT-MIR spectroscopy provides a powerful way to discriminate between juice extraction methods.

Blanching Pre-Treatment Promotes High Yields, Bioactive Compounds, Antioxidants, Enzyme Inactivation and Antibacterial Activity of 'Wonderful' Pomegranate Peel Extracts at Three Different Harvest Maturities.

'Wonderful' pomegranate (Punica granatum L.) peel contains a wide range of phytochemicals including vitamins, dietary fibre, phenolic compounds, and antioxidant properties. Yet, it is often used as animal feed or discarded in landfills, which is not the best eco-friendly way to utilize this phenolic-rich bioresource. Finding novel ways of utilizing pomegranate peel waste could prove a more profitable and eco-friendlier alternative that is far more beneficial to the economy. Adding a blanching pre-treatment step at optimal conditions prior to processing of pomegranate peel aids in the inactivation of quality changing enzymes such as polyphenol oxidase (PPO) and peroxidase (POD), which are accountable for the degradation reactions that cause breakdown of nutrients and phytochemicals. This study aimed to determine the effect of blanching at 80 °C for 3 min on the yield, polyphenol content, antioxidant properties, enzyme inactivation, and antibacterial activity of 'Wonderful' pomegranate peel ethanolic extracts from three different harvest maturities (unripe, ripe, and over ripe), including a comprehensive characterization and quantification using liquid chromatography-mass spectrometry (LC-MS). The blanched unripe peel extracts exhibited the highest total phenolic content, total tannin content, 2,2-diphenyl-1-picryl hydrazyl (DPPH) antioxidant activity, 2,2-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid (ABTS) radical scavenging activity and ferric ion reducing antioxidant power (FRAP) at 14.0 mg gallic acid equivalent (GAE)/g dry mass (DM), 1.0 mg GAE/g DM, 359.1 µmol Trolox/g DM, 912.2 µmol Trolox/g DM and 802.5 µmol Trolox/g DM, respectively. There was significant (p < 0.05) decrease in PPO and POD activity of all blanched pomegranate peel extracts. The blanched unripe peel extracts had the lowest PPO activity at 0.2 U/g fresh weight (FW), with a 70% PPO inactivation compared to ripe and over ripe harvest, whereas the highest POD inactivation was recorded at 67% in over ripe peel extracts. All blanched peel extracts, irrespective of harvest maturity, had minimum inhibitory concentration (MIC) values at 160 µg/mL against all four bacteria strains tested, which included two Gram-positive bacterial strains (Bacillus subtilis ATCC 6051 and Staphylococcus aureus ATCC 12600) and two Gram-negative bacteria (Escherichia coli 11775 and Klebsiella pneumonia ATCC 13883). A total of 25 metabolites including phenolic acids (4), organic acids (1), flavonoids (4), ellagitannins (13), and other polyphenols (3) in all three pomegranate peel samples were tentatively identified after LC-MS profiling. The blanched unripe peel extracts showed significantly higher punicalin α and ß, ß punicalagin, catechin, epicatechin content at 414 mg/g, and 678 mg/g, 151 mg/g, 229 mg/g, respectively, compared to peel extracts from other harvest maturities. This study provides supportive information for the commercial utilization of pomegranate fruit peel as source of value-added ingredients for the development of novel food, cosmetics, and pharmacological products.

Effects of Enzymatic Pretreatment of Seeds on the Physicochemical Properties, Bioactive Compounds, and Antioxidant Activity of Pomegranate Seed Oil.

Enzymatic pretreatment of seeds is a novel approach that enhances the health benefits of the extracted oil. The study investigated the influence of the enzymatic pretreatment of seeds on the quality of oil from different pomegranate cultivars. The quality of the ultrasound-assisted (and ethanol-extracted) oil was studied, with respect to the refractive index (RI), yellowness index (YI), conjugated dienes (K232), peroxide value (PV) ρ-anisidine value (AV), total oxidation value (TOTOX), total carotenoid content (TCC), total phenolic compounds (TPC), fatty acid composition, phytosterol composition, ferric reducing antioxidant power (FRAP), and 2.2-diphenyl-1-picryl hydrazyl (DPPH) radical scavenging capacity. The seeds of three different pomegranate cultivars ('Wonderful', 'Herskawitz', and 'Acco') were digested with an equal mixture of Pectinex Ultra SPL, Flavourzyme 100 L, and cellulase crude enzymes, at a concentration, pH, temperature, and time of 1.7%, 4.5, 40 °C, and 5 h, respectively. Enzymatic pretreatment of PS increased oil yield, PV, TPC, TCC, and DPPH radical scavenging capacity, but decreased the YI. The levels of K232, AV and TOTOX, fatty acids, phytosterols, RI, and FRAP, were not significantly affected by enzymatic pretreatment of PS. Principal component analysis (PCA) established that oil extracted from the 'Acco' seed after enzymatic pretreatment had higher yield, TPC, TCC, and DPPH radical scavenging capacity. Therefore, enzyme-pretreated 'Acco' pomegranate fruit seed is a source of quality seed oil with excellent antioxidant properties.

Classification Learning of Latent Bruise Damage to Apples Using Shortwave Infrared Hyperspectral Imaging.

Bruise damage is a very commonly occurring defect in apple fruit which facilitates disease occurrence and spread, leads to fruit deterioration and can greatly contribute to postharvest loss. The detection of bruises at their earliest stage of development can be advantageous for screening purposes. An experiment to induce soft bruises in Golden Delicious apples was conducted by applying impact energy at different levels, which allowed to investigate the detectability of bruises at their latent stage. The existence of bruises that were rather invisible to the naked eye and to a digital camera was proven by reconstruction of hyperspectral images of bruised apples, based on effective wavelengths and data dimensionality reduced hyperspectrograms. Machine learning classifiers, namely ensemble subspace discriminant (ESD), k-nearest neighbors (KNN), support vector machine (SVM) and linear discriminant analysis (LDA) were used to build models for detecting bruises at their latent stage, to study the influence of time after bruise occurrence on detection performance and to model quantitative aspects of bruises (severity), spanning from latent to visible bruises. Over all classifiers, detection models had a higher performance than quantitative ones. Given its highest speed in prediction and high classification performance, SVM was rated most recommendable for detection tasks. However, ESD models had the highest classification accuracy in quantitative (>85%) models and were found to be relatively better suited for such a multiple category classification problem than the rest.

The Influence of Internal Packaging (Liners) on Moisture Dynamics and Physical and Physiological Quality of Pomegranate Fruit during Cold Storage.

Weight loss and decay are common physiological disorders during postharvest handling and storage of pomegranates. The study focused on relating the ability of plastic liners as internal packaging to modify both gaseous and moisture atmosphere around the fruit to moisture dynamics and physical and physiological quality of pomegranate fruit (cv. Wonderful) during storage. Fruit were packed with no-liner, non-perforated 'Decco', non-perforated 'Zoe', micro-perforated Xtend®, 2 mm macro-perforated high density polyethylene (HDPE), and 4 mm macro-perforated HDPE plastic liners. After 84 days of storage at 5 °C and 90-95% relative humidity (RH), fruit packed with no-liner lost 15.6 ± 0.3% of initial weight. Non-perforated (Decco and Zoe) liners minimised losses to 0.79 and 0.82% compared to Xtend® micro-perforated (4.17%) and 2 mm HDPE (2.44%) and 4 mm macro-perforated HDPE (4.17%) liners, respectively. Clearly, micro- and macro-perforation of liners minimised moisture condensation, fruit decay, and shrivel severity. Micro-perforated Xtend® and macro-perforated 4 mm HDPE were the best treatments in minimising postharvest losses that are often associated with inadequate environment control inside packaging compared to the use of non-perforated liners.

A Comparative Study of Antimicrobial and Antioxidant Activities of Plant Essential Oils and Extracts as Candidate Ingredients for Edible Coatings to Control Decay in 'Wonderful' Pomegranate.

This study determined the antimicrobial and antioxidant activity of lemongrass (LO), thyme (TO), and oregano (OO) essential oils and ethanolic extracts of pomegranate peel (PPE) and grape pomace (GPE) as candidate ingredients for edible coatings. Antifungal effects against Botrytis cinerea and Penicillium spp. were tested using paper disc and well diffusion methods. Radical scavenging activity (RSA) was evaluated using 2,2-diphenyl-1-picrylhydrazyl and 2,2'-azinobis-3-ethylbenzothiazoline-6-sulfonic acid assays. Gas chromatography-mass spectrometry analysis identified limonene (16.59%), α-citral (27.45%), ß-citral (27.43%), thymol (33.31%), paracymene (43.26%), 1,8-cineole (17.53%), and trans-caryphellene (60.84%) as major compounds of the essential oils. From both paper disc and well diffusion methods, LO recorded the widest zone of inhibition against tested microbes (B. cinerea and Penicillium spp.). The minimum inhibitory concentrations of LO against B. cinerea and Penicillium spp., were 15 µL/mL and 30 µL/mL, respectively. The highest (69.95%) and lowest (1.64%) RSA at 1 mg/mL were recorded for PPE and OO. Application of sodium alginate and chitosan-based coatings formulated with LO (15 or 30 µL/mL) completely inhibited spore germination and reduced the decay severity of 'Wonderful' pomegranate. Lemongrass oil proved to be a potential antifungal agent for edible coatings developed to extend shelf life of 'Wonderful' pomegranate.

Thermo-Mechanical Analysis in the Fresh Fruit Cold Chain: A Review on Recent Advances.

In agro-food research and industry, mathematical models are being used to develop and optimize preharvest and postharvest operations, and their use has grown exponentially over the last decade. Generally, transport phenomena (such as airflow, heat, and mass transfer) during the cooling of horticultural products are complex; therefore, the use of computational modeling techniques is a valid alternative to expensive and difficult experiments because computers continuously become more powerful and less expensive, the software is readily available, and once a model is validated, it is a versatile tool to evaluate the effects of the operating and design parameters involved. In this review, thermo-mechanical modeling studies during postharvest handling are overviewed regarding the experimental, analytical, and computational approaches. The airflow, cooling kinetics, cooling uniformity, and the material and mechanical safety behavior of fresh fruit packaging boxes will be analyzed. Current concerns, challenges, and opportunities are discussed.

Quality and Antioxidant Properties of Cold-Pressed Oil from Blanched and Microwave-Pretreated Pomegranate Seed.

The present research studied the influence of blanching and microwave pretreatment of seeds on the quality of pomegranate seed oil (PSO) extracted by cold pressing. Pomegranate seeds (cv. Acco) were independently blanched (95 ± 2 °C/3 min) and microwave heated (261 W/102 s) before cold pressing. The quality of the extracted oil was evaluated with respect to oxidation indices, refractive index, yellowness index, total carotenoids content, total phenolic content, flavor compounds, fatty acid composition, and 2.2-diphenyl-1-picryl hydrazyl (DPPH) and 2.2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging capacity. Blanching and microwave pretreatments of seeds before pressing enhanced oil yield, total phenolic content, flavor compounds, and DPPH and ABTS radical scavenging capacity. Although the levels of oxidation indices, including the peroxide value, free fatty acids, acid value, ρ-anisidine value, and total oxidation value, also increased, and the oil quality conformed to the requirements of the Codex Alimentarius Commission (CODEX STAN 19-1981) standard for cold-pressed vegetable oils. On the other hand, blanching and microwave heating of seeds decreased the pomegranate seed oil's yellowness index, whilst the refractive index was not significantly (p > 0.05) affected. Even though both blanching and microwave pretreatment of seeds added value to the cold-pressed PSO, the oil extracted from blanched seeds exhibited lower oxidation indices. Regarding fatty acids, microwave pretreatment of seeds before cold pressing significantly increased palmitic acid, oleic acid, and linoleic acid, whilst it decreased the level of punicic acid. On the contrary, blanching of seeds did not significantly affect the fatty acid composition of PSO, indicating that the nutritional quality of the oil was not significantly affected. Therefore, blanching of seeds is an appropriate and valuable step that could be incorporated into the mechanical processing of PSO.

Finite Element Method for Freezing and Thawing Industrial Food Processes.

Freezing is a well-established preservation method used to maintain the freshness of perishable food products during storage, transportation and retail distribution; however, food freezing is a complex process involving simultaneous heat and mass transfer and a progression of physical and chemical changes. This could affect the quality of the frozen product and increase the percentage of drip loss (loss in flavor and sensory properties) during thawing. Numerical modeling can be used to monitor and control quality changes during the freezing and thawing processes. This technique provides accurate predictions and visual information that could greatly improve quality control and be used to develop advanced cold storage and transport technologies. Finite element modeling (FEM) has become a widely applied numerical tool in industrial food applications, particularly in freezing and thawing processes. We review the recent studies on applying FEM in the food industry, emphasizing the freezing and thawing processes. Challenges and problems in these two main parts of the food industry are also discussed. To control ice crystallization and avoid cellular structure damage during freezing, including physicochemical and microbiological changes occurring during thawing, both traditional and novel technologies applied to freezing and thawing need to be optimized. Mere experimental designs cannot elucidate the optimum freezing, frozen storage, and thawing conditions. Moreover, these experimental procedures can be expensive and time-consuming. This review demonstrates that the FEM technique helps solve mass and heat transfer equations for any geometry and boundary conditions. This study offers promising insight into the use of FEM for the accurate prediction of key information pertaining to food processes.