Search Results (708)

Strawberries are highly perishable fruits prone to postharvest losses due to defects, diseases, and uneven ripening. This study proposes a deep learning-based approach for automated quality assessment using the YOLOv8n object detection model. A custom dataset of 5663 annotated strawberry images was compiled, covering eight quality categories, including anthracnose, gray mold, powdery mildew, uneven ripening, and physical defects. Data augmentation techniques, such as rotation and Gaussian blur, were applied to enhance model generalization and robustness. The model was trained over 100 and 200 epochs, and its performance was evaluated using standard metrics: Precision, Recall, and mean Average Precision (mAP). The 200-epoch model achieved the best results, with a mAP50 of 0.79 and an inference time of 1 ms per image, demonstrating suitability for real-time applications. Classes with distinct visual features, such as anthracnose and gray mold, were accurately classified. In contrast, visually similar categories, such as ‘Good Quality’ and ‘Unripe’ strawberries, presented classification challenges. Full article

This study systematically investigates the homogenization-induced Laves phase dissolution kinetics and recrystallization mechanisms in laser powder bed fusion (L-PBF) processed IN718 superalloy. The as-built material exhibits a characteristic fine dendritic microstructure with interdendritic Laves phase segregation and high dislocation density, featuring directional sub-grain boundaries aligned with the build direction. Laves phase dissolution demonstrates dual-stage kinetics: initial rapid dissolution (0–15 min) governed by bulk atomic diffusion, followed by interface reaction-controlled deceleration (15–60 min) after 1 h at 1150 °C. Complete dissolution of the Laves phase is achieved after 3.7 h at 1150 °C. Recrystallization initiates preferentially at serrated grain boundaries through boundary bulging mechanisms, driven by localized orientation gradients and stored energy differentials. Grain growth kinetics obey a fourth-power time dependence, confirming Ostwald ripening-controlled boundary migration via grain boundary diffusion. Such a study is expected to be helpful in understanding the microstructural development of L-PBF-built IN718 under heat treatments. Full article

To advance the development of protein-rich plant-based foods, a novel binder system for vegan sausage alternatives without the requirement of heat application was investigated. This enables long-term ripening of plant-based analogs similar to traditional fermented meat or dairy products, allowing for refined flavor and texture development. This was achieved by using a poorly water-soluble calcium source (calcium carbonate) to introduce calcium ions into a low-ester pectin—gluten matrix susceptible to crosslinking via divalent ions. The gelling reaction of pectin–gluten dispersions with Ca²⁺ ions was time-delayed due to the gradual production of lactic acid during fermentation. Firm, sliceable matrices were formed, in which particulate substances such as texturized proteins and solid vegetable fat could be integrated, hence forming an unheated raw-fermented plant-based salami-type sausage model matrix which remained safe for consumption over 21 days of ripening. Gluten as well as pectin had a significant influence on the functional properties of the matrices, especially water holding capacity (increasing with higher pectin or gluten content), hardness (increasing with higher pectin or gluten content), tensile strength (increasing with higher pectin or gluten content) and cohesiveness (decreasing with higher pectin or gluten content). A combination of three simultaneously occurring effects was observed, modulating the properties of the matrices, namely, (a) an increase in gel strength due to increased pectin concentration forming more brittle gels, (b) an increase in gel strength with increasing gluten content forming more elastic gels and (c) interactions of low-ester pectin with the gluten network, with pectin addition causing increased aggregation of gluten, leading to strengthened networks. Full article

Early crop yield prediction is a major challenge in precision agriculture, and efficient and rapid yield prediction is highly important for sustainable fruit production. The accurate detection of major fruit characteristics, including flowering, green fruiting, and ripening stages, is crucial for early yield estimation. Currently, most crop yield estimation studies based on the YOLO model are only conducted during a single stage of maturity. Combining multi-growth period data for crop analysis is of great significance for crop growth detection and early yield estimation. In this study, a new network model, YOLOv8-RL, was proposed using citrus multigrowth period characteristics as a data source. A citrus yield estimation model was constructed and validated by combining network identification counts with manual field counts. Compared with YOLOv8, the number of parameters of the improved network is reduced by 50.7%, the number of floating-point operations is decreased by 49.4%, and the size of the model is only 3.2 MB. In the test set, the average recognition rate of citrus flowers, green fruits, and orange fruits was 95.6%, the mAP@.5 was 94.6%, the FPS value was 123.1, and the inference time was only 2.3 milliseconds. This provides a reference for the design of lightweight networks and offers the possibility of deployment on embedded devices with limited computational resources. The two estimation models constructed on the basis of the new network had coefficients of determination R² values of 0.91992 and 0.95639, respectively, with a prediction error rate of 6.96% for citrus green fruits and an average error rate of 3.71% for orange fruits. Compared with network counting, the yield estimation model had a low error rate and high accuracy, which provided a theoretical basis and technical support for the early prediction of fruit yield in complex environments. Full article

Effective postharvest cooling of olive fruit is increasingly critical under rising harvest temperatures driven by climate change. This study models passive cooling dynamics using a trait-based, mixed-effects statistical framework. Ten olive groups—representing seven cultivars and different ripening or size stages—were subjected to controlled cooling conditions. Surface temperature was recorded using infrared thermal imaging, and morphological and compositional traits were quantified. Temperature decay was modeled using Newton’s Law of Cooling, extended with a quadratic time term to capture nonlinear trajse thectories. A linear mixed-effects model was fitted to log-transformed, normalized temperature data, incorporating trait-by-time interactions and hierarchical random effects. The results confirmed that fruit weight, specific surface area (SSA), and specific heat capacity (SHC) are key drivers of cooling rate variability, consistent with theoretical expectations, but quantified here using a trait-based statistical model applied to olive fruit. The quadratic model consistently outperformed standard exponential models, revealing dynamic effects of traits on temperature decline. Residual variation at the group level pointed to additional unmeasured structural influences. This study demonstrates that olive fruit cooling behavior can be effectively predicted using interpretable, trait-dependent models. The findings offer a quantitative basis for optimizing postharvest cooling protocols and are particularly relevant for maintaining quality under high-temperature harvest conditions. Full article

With the objective of identifying superior Vernicia montana trees grounded in phenotypic and agronomic traits, this study sought to develop and implement a comprehensive evaluation method which would provide a practical foundation for future clonal breeding initiatives. Using the Vernicia montana propagated from seedling forests grown in the Suxian District of Chenzhou City in southern Hunan Province, we conducted pre-selection, primary selection, and re-selection of Vernicia montana forest stands and took the nine trait indices of single-plant fruiting quantity, single-plant fruit yield, disease and pest resistance, fruit ripening consistency, fruit aggregation, fresh fruit single-fruit weight, fresh fruit seed rate, dry seed kernel rate, and seed kernel oil content rate as the optimal evaluation indexes and carried out cluster analysis and a comprehensive evaluation in order to establish a comprehensive evaluation system for superior Vernicia montana trees. The results demonstrated that a three-stage selection process—consisting of pre-selection, primary selection, and re-selection—was conducted using a comprehensive analytical approach. The pre-selection phase relied primarily on sensory evaluation criteria, including fruit count per plant, tree size, tree morphology, and fruit clustering characteristics. Through this rigorous screening process, 60 elite plants were selected. The primary selection was based on phenotypic traits, including single-plant fruit yield, pest and disease resistance, and uniformity of fruit ripening. From this stage, 36 plants were selected. Twenty plants were then selected for re-selection based on key performance indicators, such as fresh fruit weight, fresh fruit seed yield, dry seed kernel yield, and oil content of the seed kernel. Then the re-selected optimal trees were clustered and analyzed into three classes, with 10 plants in class I, 7 plants in class II, and 3 plants in class III. In class I, the top three superior plants exhibited outstanding performance across key traits: their fresh fruit weight per fruit, fresh fruit seed yield, dry seed yield, and seed kernel oil content reached 41.61 g, 42.80%, 62.42%, and 57.72%, respectively. Compared with other groups, these figures showed significant advantages: 1.17, 1.09, 1.12, and 1.02 times the average values of the 20 reselected superior trees; 1.22, 1.19, 1.20, and 1.08 times those of the 36 primary-selected superior trees; and 1.24, 1.25, 1.26, and 1.19 times those of the 60 pre-selected trees. Fruits counts per plant and the number of fruits produced per plant of the best three plants in class I were 885 and 23.38 kg, respectively, which were 1.13 and 1.18 times higher than the average of 20 re-selected superior trees, 1.25 and 1.30 times higher than the average of 36 first-selected superior trees, and 1.51 and 1.58 times higher than the average of 60 pre-selected superior trees. Class I superior trees, especially the top three genotypes, are suitable for use as mother trees for scion collection in grafting. The findings of this study provide a crucial foundation for developing superior clonal varieties of Vernicia montana through selective breeding. Full article

As consumer preferences tend toward safer, chemical residue-free, and nutritionally rich fruits, preharvest bagging has gained attention as a sustainable method for improving fruit quality and protecting produce from environmental and biological stressors and pesticide residues. This study assessed the impact of preharvest bagging using paper bags with inner aluminum coating on the physicochemical traits, storability, and browning susceptibility after cutting or bruising of ‘Afrata Volou’ quince (Cydonia oblonga Mill.) fruit grown in central Greece. Fruits were either bagged or left unbagged approximately 60 days before harvest, and evaluations were conducted at harvest and after three months of cold storage, plus two days of shelf-life. Fruit bagging reduced the quince’s flesh temperature on the tree crown. Bagging had minor effects on fruit and nutritional quality, except for more yellow skin and higher titratable acidity (TA). Also, at harvest, bagging did not significantly affect fruit flesh browning after cutting or bruising. After three months of storage, unbagged and bagged quince fruit developed more yellow skin color, without significant alterations in most quality characteristics and nutritional value, but increased total tannin content (TTC). After three months of storage, the quince flesh color determined immediately after cutting or bruising was brighter and more yellowish compared to that at harvest, due to continuation of fruit ripening, but it darkened faster with time after cutting or skin removal. Therefore, fruit bagging appears to be a sustainable practice for improving the aesthetic and some chemical quality characteristics of quince, particularly after storage, without negative impacts on other characteristics such as texture and phenolic content. Full article

Petit Manseng is a variety of Vitis vinifera gaining popularity in Virginia, USA because it consistently produces high quality grapes under variable growing conditions. However, its high sugar and acid levels complicate dry wine production. The goal of this study was to characterize Petit Manseng ripening kinetics from veraison to harvest to identify optimal harvest timing for producing dry white wines, using Chardonnay as a comparator because of its popularity in Virginia, well-known ripening kinetics, and ability to produce high quality dry white wines. A total of 74 samples of Petit Manseng and Chardonnay grapes were collected from five commercial sites over 2 years and evaluated for berry weight, pH, titratable acidity (TA), malic acid, total soluble solids (TSS), glucose, and fructose, with ripening kinetics modeled using segmented regressions. Results indicated that harvest timing and grape variety were the primary factors influencing ripening kinetics. In contrast, growing location and vintage had limited impact. In Chardonnay grapes, TA declined from 21 to 7.1 g/L and TSS increased from 6.1 to 19.5 g/L. In Petit Manseng, TA declined from 25 to 10.8 g/L and TSS increased from 8.0 to 23.6 g/L. Acid depletion plateaued ~2 weeks after sugar accumulation plateaued in Petit Manseng grapes, though the plateaus were similar in Chardonnay grapes. Linear discriminant analysis (LDA) completely separated grapes based on pH or TA vs. sugars, but not malic acid vs. sugars, suggesting that tartaric acid is driving acidity differences between cultivars. These data indicate that regardless of when grapes are harvested, winemakers may need to employ targeted acid management strategies with Petit Manseng because of its ripening kinetics. Full article

Banana fruits are harvested and then undergo rapid ripening and senescence, sharply limiting their shelf-life and marketability. Myo-inositol (MI) is an important regulator in ethylene production and reactive oxygen species (ROS) accumulation; however, its involvement in the postharvest ripening process of banana remains to be determined. This study found that postharvest application of MI could efficiently delay the fruit ripening and extend the time in which the luster, color, and hardness were maintained in two cultivars with contrasting storage characteristics, storable ‘Brazil’ and unstorable ‘Fenza No. 1’, when stored at room temperature (23 °C ± 2 °C). Moreover, physiological, metabolic, and gene expression analyses indicated that MI application improved MI metabolism and postponed ethylene biosynthesis and cell wall loosening. The decrease in ethylene production was associated with a reduction in the expression of ACS1 and ACO1 genes. MI treatment decreased the expressions of PL1/2, PG, and EXP1/7/8, which may account for the delay in softening. In addition, the application of MI could alleviate ROS-mediated senescence and cell membrane damage by promoting the activities of SOD, POD, and anti-O₂⁻ and decreasing PPO activity. This study shed light on the function of MI in regulating the postharvest ripening and senescence of bananas and provided an efficient strategy for extending shelf-life and reduce losses. Full article

Redox signaling is central to plant adaptation, influencing metabolic regulation, stress responses, and developmental processes through thiol-based oxidative post-translational modifications (oxiPTMs) of redox-sensitive proteins. These modifications, particularly those involving cysteine (Cys) residues, act as molecular switches that alter protein function, structure, and interactions. Advances in mass spectrometry-based redox proteomics have greatly enhanced the identification and quantification of oxiPTMs, enabling a more refined understanding of redox dynamics in plant cells. In parallel, the emergence of computational modeling, artificial intelligence (AI), and machine learning (ML) has revolutionized the ability to predict redox-sensitive residues and characterize redox-dependent signaling networks. This review provides a comprehensive synthesis of methodological advancements in redox proteomics, including enrichment strategies, quantification techniques, and real-time redox sensing technologies. It also explores the integration of computational tools for predicting S-nitrosation, sulfenylation, S-glutathionylation, persulfidation, and disulfide bond formation, highlighting key models such as CysQuant, BiGRUD-SA, DLF-Sul, and Plant PTM Viewer. Furthermore, the functional significance of redox modifications is examined in plant development, seed germination, fruit ripening, and pathogen responses. By bridging experimental proteomics with AI-driven prediction platforms, this review underscores the future potential of integrated redox systems biology and emphasizes the importance of validating computational predictions, through experimental proteomics, for enhancing crop resilience, metabolic efficiency, and precision agriculture under climate variability. Full article

Biogenic amines (BA) are simple organic bases of low molecular weight, formed during decarboxylation of amino acids. Ripened cheeses provide suitable conditions for the development of bacteria and production of BAs. The aim of the present study was to investigate the presence of eight BAs in ripened cheese samples (n = 125) using a high-performance liquid chromatography with diode array detector (HPLC-DAD). Furthermore, microbiological analyses towards identification of bacteria using matrix-assisted laser desorption ionisation—time of flight mass spectrometry (MALDI-TOF MS) were performed. Cadaverine and putrescine were detected in 28.0% and 20.8% of cheese samples at concentrations ranging from 6.12 to 2871 mg/kg and 5.74 to 441 mg/kg, respectively. High amounts of putrescine and cadaverine in cheeses were associated with the presence of Hafnia alvei. Tyramine was identified in 28.0% of samples in the concentration range of 5.62–646 mg/kg. High concentrations of this amine was found in cheeses containing Enterococcus faecium and Enterococcus faecalis. Histamine content, the only BA restricted in food according to Regulation 2073/2005, was observed above 100 mg/kg in 11.2% of the cheeses. Ripened cheeses available on the local retail market may contain significant levels of biogenic amines and may pose a potential health hazard to consumers. Full article

In food processing, non-destructive and non-invasive characterization is a powerful tool for monitoring processes and controlling quality. Cheeses consist of a large variety of products whose nutritional and sensory properties depend on the source materials, cheesemaking procedures, and biochemical transformations occurring during maturation and storage. In this study, proton magnetic resonance relaxation time correlation maps (2D ¹H-NMR T₁–T₂) are used to investigate the effect of the ripening degree on Pecorino cheese and evaluate its evolution during storage in a refrigerator under vacuum-packaging conditions. NMR relaxometry has allowed for non-invasive monitoring of packaged Pecorino cheese slices, and the results were compared with those obtained with the two widely used techniques, i.e., Differential Scanning Calorimetry (DSC) and Attenuated Total Reflectance Fourier-Transform Infrared Spectroscopy (ATR-FTIR). The analysis of variance and simultaneous component analysis (ASCA), separately applied to 2D ¹H-NMR T₁–T₂ correlation maps, DSC, and ATR-FTIR data, suggests that the results obtained with the NMR approach are consistent with those obtained using the two benchmark techniques. In addition, it can distinguish cheeses stored for different durations (storage time) irrespective of their original moisture content (ripening degree), and vice versa, without opening the vacuum-package, which could compromise the integrity of the samples. Full article

This study aimed to verify, under real operating conditions, the effectiveness of protective lactic acid bacteria (LAB) culture in counteracting the development of late blowing defects in Valtellina Casera PDO cheese and its impact on product sensory characteristics. Thirty-four LAB isolated from Bitto and Valtellina Casera PDO cheeses were screened for anti-Clostridium activity. Lacticaseibacillus casei VC201 was able to inhibit all the indicator strains through organic acid production. Valtellina Casera PDO cheese-making was performed twice in three dairy farms using a commercial autochthonous starter culture with and without the addition of the protective culture VC201. Cheese was ripened both at 8 °C and 12 °C and analyzed after 70 and 180 days for LAB population, proteolysis, and lipolysis evolution as well as sensory impact. Cheeses with the addition of the VC201 strain showed higher contents of rod-shaped LAB throughout the ripening at both temperatures. The protective culture decreased the production of butyric acid at 70 days, especially at 8 °C (−15.4%), while butyric fermentation was occasionally lightly observed at 12 °C. The sensory profile was favorably impacted by the higher relative proportion of short-chain fatty acids (SCFFAs, C2–C8), which was especially pronounced at 8 °C and persisted for 180-day ripening (23.91% vs. 18.84% at 70 days and 23.84 vs. 21.71 at 180 days of ripening). The temperature and time of ripening had a significant effect on the free fatty acid content of the cheese samples in all three classes (SCFFA, MCFFA, and LCFFA). The cheese made with Lcb. casei VC201 was preferred, according to the sensory evaluation, being perceived as less acidic, less bitter, tastier, and with more intense flavor. Protective cultures can represent a practical way to reduce late blowing defects in Valtellina Casera cheese production while maintaining adherence to its PDO regulatory requirements. Full article

During fruit ripening in Capsicum species, substantial amounts of carotenoids accumulate in the pericarp. While the carotenoid biosynthesis pathway in Capsicum species has been extensively investigated from various angles, the transcriptional regulation of genes encoding carotenoid biosynthetic enzymes remains less understood in this non-climacteric horticultural crop compared to tomato, a climacteric fruit. In the present study, we investigated the function of the NAM, ATAF1/2 or CUC2 81 (CaNAC81) transcription factor gene. This gene was selected through RNA-Seq co-expression analysis based on the correlation between expressed transcription factor gene profiles and those of carotenoid structural genes. To determine its role in regulating the expression of biosynthetic-related carotenogenic genes, we performed Virus-Induced Gene Silencing (VIGS) assays in the Serrano-type C. annuum ‘Tampiqueño 74’. Fruits from plants infected with a pTRV2:CaNAC81 construct (silenced fruits) exhibited altered carotenoid pigmentation accumulation, manifested as yellow-orange spots, in contrast to fruits from non-agroinfected controls (NTC) and fruits from plants infected with the empty TRV2 construct (red fruits). Quantitative real-time PCR (qPCR) assays confirmed decreased transcript levels of CaNAC81 in fruits displaying altered pigmentation, along with reduced transcription of the PSY gene, which encodes the carotenoid biosynthetic enzyme phytoene synthase (PSY). High-performance liquid chromatography (HPLC) analysis revealed a distinct carotenoid pigment accumulation pattern in fruits from plants showing silencing symptoms, characterized by low concentrations of capsanthin and zeaxanthin and trace amounts of capsorubin, compared to control plants (NTC). These findings suggest the involvement of CaNAC81 in the regulatory network of the carotenoid biosynthetic pathway in chili pepper fruits. Full article

This study demonstrates that the ripeness of avocado fruits can be analyzed using frequency-dependent electrical conductivity and permittivity through a non-invasive Magnetic Induction Spectroscopy (MIS) method. Utilizing an MIS system for conductivity and permittivity measurements of a large sample set ($N=60$) of avocado fruits across multiple frequencies from 100 kHz to 3 MHz enables clear observation of their dispersion behavior and the evolution of their spectra over ripening time in a completely non-contact manner. For the entire sample batch, the conductivity spectrum exhibits a general upward shift and spectral flattening over ripening time. To further quantify these features, normalized gradient analysis and equivalent circuit modeling were employed, and statistical analysis confirmed the correlations between electrical parameters and ripening stages. The trend characteristics of the normalized gradient parameter $P_y$ provide a basis for defining the three ripening stages within the 22-day period: early pre-ripe stage (0–5 days), ripe stage (5–15 days), and overripe stage (after 15 days). The equivalent circuit model, which is both physically interpretable and fitted to experimental data, revealed that the ripening process of avocado fruits is characterized by a weakening of capacitive structures and an increase in extracellular solution conductivity, suggesting changes in cellular integrity and extracellular composition, respectively. The results also highlight significant inter-sample variability, which is inherent to biological samples. To further investigate individual conductivity variation trends, Gaussian Mixture Model (GMM) clustering and Principal Component Analysis (PCA) was conducted for exploratory sample classification and visualization. Through this approach, the sample set was classified into three categories, each corresponding to distinct conductivity variation patterns. Full article