Search Results (236)

Peaches are a fruit crop with global importance due to their economic value. Fruit quality (e.g., weight, soluble solids content (SSC)) and phenology traits (e.g., maturity date) are essential for generating novel varieties. Nevertheless, modern germplasm’s narrow genetic diversity hampers breeding efforts to enhance these traits. To identify genetic markers helpful for marker-assisted breeding, this work leveraged a diverse panel of 140 peach commercial cultivars and advanced breeding lines phenotyped across three harvest seasons for the maturity date (MD), chlorophyll absorbance (IAD), SSC, and fruit weight (FW). Genotypic data were generated via ddRADseq, identifying 5861 SNPs. A rapid linkage disequilibrium decay (critical r² = 0.308 at 950 kb) was determined, and a population structure analysis revealed two admixed genetic clusters, with phenotypic distributions influenced by seasonal environmental factors. A total of 599 marker–trait associations were detected by using single and multi-year analysis, and for each trait the surrounding genomic regions explored to identify potential candidate genes annotated with functions related to the trait under study, and expressed in peach fruits. This study highlights multiple loci potentially responsible for phenotypic variations in plant phenology and fruit quality, and provides molecular markers to assist peach breeding for fruit quality. Full article

Texture is a critical quality attribute of strawberry fruit, and phytohormones play a pivotal role in fruit softening, which mainly results from cell wall metabolism, which is governed by genes and enzymes. To gain further insights into strawberry (Fragaria × ananassa, Duch. cv.  Akihime ) softening, our study investigated changes across five stages in fruits in their firmness, soluble solids content (SSC), cell microstructure, cell wall materials, activities of cell wall-modifying enzymes, gene expression, endogenous phytohormone levels, and their correlation. During strawberry ripening, firmness decreased, while SSC, intercellular space, and separation of the cell wall from the plasma membrane increased. Meanwhile, the contents of ionic pectin (ISP) and cellulose (CE), pectin methylesterase (PME) activity, FaPME expression, and the levels of zeatin (Z) and strigolactone (SL) decreased, showing a positive correlation with firmness. In contrast, the activities of pectate lyase (PL) and cellulase (Cx), the expression of FaPL and FaCx, and the contents of gibberellin A₄ (GA₄), GA₉, and abscisic acid (ABA) increased during ripening, and these were negatively correlated with firmness. These results suggest that Z and SL are associated with the maintenance of cell wall integrity and firmness, whereas increases in GA₄, GA_9, and ABA are linked to enhanced cell wall disassembly and fruit softening. Full article

This study evaluated the effects of water–fertilizer coupling on the water and fertilizer use efficiency, yield, and quality of fresh common beans (Phaseolus vulgaris L.) in high-latitude and high-altitude regions. For field water-saving, in 2022, six treatments were established, with irrigation rates of 100% FC (W1), 90% FC (W2), 80% FC (W3), 70% FC (W4), 60% FC (W5), and 50% FC (W6). Based on the experiment in 2022, a two-factor experiment (irrigation and fertilizer application rate) was implemented in 2023, and three fertilizer (N−P₂O₅−K₂O) gradients were established: F1 (260−192−255 kg/ha), F2 (195−144−192 kg/ha), and F3 (131−97−127 kg/ha). Based on 2022, three irrigation rates were established at percentages of FC: W7 (100% FC), W8 (80% FC), and W9 (60% FC). Experiments in both years revealed a quadratic relationship (parabola equation) between yield and the rates of both irrigation and fertilization. Excessive fertilization did not consistently enhance yield, and reduced fertilizer application resulted in higher fertilizer partial factor productivity (PFP). Both years of experiments indicated that maintaining soil moisture at 80%~90% field capacity (FC) significantly improved fresh pod yield and water use efficiency (WUE) compared to other treatments. Under the same fertilizer level, reduced irrigation increased key fresh pod quality indicators, such as single-pod weight and soluble sugar content. In contrast, across varying fertilizer rates, these same indicators showed a positive correlation with the amount of fertilizer applied. Vitamin C (VC), soluble protein (SP), soluble solids content (SSC), and nitrate content (NC) reached their highest levels under high fertilizer treatment (N−P₂O₅−K₂O: 260−192−255 kg/ha). Based on the differential comprehensive evaluation models, the study concluded that maintaining soil moisture at 80%~90% FC and applying fertilizer between N−P₂O₅−K₂O: 195−144−192 kg/ha and N−P₂O₅−K₂O: 260−192−255 kg/ha was the optimal strategy. This approach can alleviate the water scarcity pressure in high-latitude and high-altitude regions, and facilitate the selection of common bean management practices that maintain yield while improving quality and PFP, thereby offering theoretical and practical guidance for adapting water–fertilizer regimes to local climatic conditions. Full article

To meet market demand for fresh ‘Dinosaur Egg’ Apricot plum and realize effective quality classification, this study developed a non-destructive quality evaluation method using near-infrared spectroscopy (NIRS) with cross-parameter feature fusion. Spectral data were preprocessed, and key bands were screened via Competitive Adaptive Reweighted Sampling (CARS) and Shuffled Frog Leaping Algorithm (SFLA). Partial Least Squares Regression (PLSR) models for soluble solids content (SSC), moisture content (MC), and fruit firmness (FF) were established. Chemical index features were fused with FF-related preliminary features, and SHapley Additive exPlanations (SHAP) optimized feature contribution. Final models showed high performance: SSC ($R_c^2$ = 0.9354, $R_p^2$ = 0.9302, $RMSE$ = 0.5212° Brix), MC ($R_c^2$ = 0.9367, $R_p^2$ = 0.9314, $RMSE$ = 5.037 × 10⁻⁵), and FF ($R_c^2$ = 0.8151, $R_p^2$ = 0.7986, $RMSE$ = 1.2710 N). This strategy improved the multi-quality detection accuracy, especially for FF, and provides technical support for intelligent fruit grading. Full article

Blackberry (Rubus subg. Eubatus Focke) ranks among the four most commercially valuable berry crops globally, alongside raspberry, strawberry, and blueberry, owing to its high antioxidant content—particularly flavonoids, anthocyanins, and polyphenols. Compared to other berry crops, blackberry cultivation requires lower labor and financial inputs, with plantations remaining productive for 12–15 years. In Russia, total blackberry area is limited (~100 ha), and the Moscow Region is particularly suited for trailing and semi-trailing cultivars with early-to-mid-season ripening. This three-year study (2021–2023) conducted at the Tsitsin Main Botanical Garden (RAS) evaluated ten promising blackberry cultivars to (i) assess interrelationships among phenological, morphological, and fruit quality traits; and (ii) identify optimal market niches for each genotype. Cultivars were grouped by ripening time: early (‘Karaka Black’, ‘Loch Tay’, ‘Natchez’) and medium (‘Columbia Sunrise’, ‘Hall’s Beauty’, ‘Caddo’, ‘Columbia Giant’, ‘Victoria’, ‘Brzezina’). Morphologically, ‘Columbia Giant’, ‘Columbia Star’, ‘Columbia Sunrise’, ‘Hall’s Beauty’, and ‘Loch Tay’ exhibited the most balanced architecture. For fresh-market retail, ‘Hall’s Beauty’ (650.3 gf), ‘Loch Tay’ (632.0 gf), and ‘Victoria’ (882.2 gf) stood out for high fruit firmness, whereas ‘Columbia Giant’ (11.5 g fruit mass, 354.1 gf) is recommended for direct consumer sales due to its large fruit size and acceptable firmness. Key trait associations included flowering duration and drupelet number (r = −0.83); fruiting onset and lateral length (r = 0.75); central leaflet length and fruiting laterals per shoot (r = −0.86); fruit number per lateral and Soluble Solids Content (SSC, r = 0.83); and lateral length (r = 0.84). These findings indicate the importance of proper variety selection for establishing blackberry plantations in the specific climatic conditions of the Moscow Region. Full article

This study addresses the limitations of current non-destructive techniques for assessing tomato quality, such as their high cost, strong dependence on spectroscopic instruments, and difficulty in dynamic monitoring. The study proposes an integrated tomato quality prediction model that combines a Long Short-Term Memory (LSTM)-based environmental predictor, a Gated Recurrent Unit with attention mechanism (GRU-AT) for dynamic maturity prediction, and a Deep Neural Network (DNN)-based quality evaluation module. The LSTM model demonstrated high accuracy in environmental prediction (R² > 0.9559). The GRU-AT model excelled in color ratio prediction (R² > 0.86), and the DNN model achieved R² values exceeding 0.811 for lycopene (LYC), firmness (FI), and soluble solids content (SSC). Experimental results demonstrate that this approach can accurately predict multiple quality parameters using only standard RGB images. In summary, this study provides a low-cost, low-complexity solution enabling real-time, non-destructive monitoring of greenhouse tomato quality, offering a viable pathway for crop quality management in precision agriculture. Full article

Poland, as a leading apple producer in the EU, must maintain high fruit quality during prolonged storage and distribution, which is crucial for exports to distant markets. Therefore, it is essential to clearly identify which factors most strongly affect quality and the magnitude of their effects in order to make informed choices about pre- and postharvest practices, storage technology, and logistics. The objective of this study was to assess the effect of selected factors on the quality of apples of the ‘Gala Schniga^® SchniCo Red(s)’ cultivar after long-term storage. The study analyzed the effects of harvest date (optimal and delayed), three variants of 1-methylcyclopropene application (control-0 µL·L⁻¹ 1-MCP, Harvista™, SmartFresh™, and Harvista™ + SmartFresh™), storage period (5, 7, and 9 months), simulated trading period (0 or 7 days at 20 °C) and storage technology (ULO: 1.2% CO₂: 1.2% O₂; DCA: 0.6% CO₂: 0.6% O₂) in two consecutive seasons (2022/2023 and 2023/2024). Five quality parameters were evaluated: flesh firmness (F), soluble solid content (SSC), titratable acidity (TA), SSC/TA ratio, and the concentration of 1-aminocyclopropane-1-carboxylic acid (ACC). Backward-elimination stepwise regression and partial eta squared (η²) calculations were used to analyze the data to determine the factors with the greatest impact. The post-harvest application of 1-MCP had the strongest effect in terms of maintaining firmness (η² = 70.4%) and acidity (η² = 38.0%) and reducing ACC content (η² = 21.3%). Harvista™ preparation had a weaker or negligible effect on ACC content, but reduced SSC (η² = 22.7%). Harvest date, storage duration, and shelf life significantly influenced all traits, with controlled-atmosphere regime further modulating outcomes. By integrating preharvest maturity with treatment timing and CA storage, we disentangled the relative contributions of harvest timing, treatment, and storage. The results provide actionable inputs for a decision-support tool to help producers maintain target quality—firmness, SSC, TA, SSC/TA, and ACC—through optimized practice, storage technology choice, and logistics. Full article

We developed a model to predict the quality of fresh goji berries during storage by analyzing the correlations of their dielectric properties. The variations in these properties with storage temperature, time, and frequency were systematically characterized to inform the model. Leveraging these relationships, we developed a model to predict quality. The analysis integrated measurements of dielectric properties with assessments of texture and key physicochemical indicators. Results indicate that dielectric parameters exhibit significant frequency dependence. Complex impedance (Z), capacitance (Cp), and resistance (Rp) all decreased sharply with increasing frequency, with the most pronounced change observed in Cp. Conductance, G, and reactance, X, increased with frequency, reaching maximum increases of 360.86% and 87.79%, respectively. Under the specific test frequency of 163,280 Hz, a strong polynomial relationship was observed between the dielectric parameters and storage time, with all fitted models yielding ${\mathit{R}}_{adj}^2$ values above 0.94. The quality factor Q (a dimensionless number for the energy efficiency of a resonant circuit or medium) showed a near-perfect correlation with brittleness, while reactance, X, was correlated with springiness and cohesiveness, with correlation coefficients approaching 0.999 under the optimal test frequency. The constructed ANN model demonstrated high prediction accuracy for hardness, brittleness, elasticity, cohesiveness, chewiness, and soluble solids content (R² > 0.97, MSE < 5%) but performed poorly in predicting adhesiveness, stickiness, and rebound elasticity (R² < 0.9). The constructed LSSVM model showed good prediction performance for some indicators (hardness, springiness, cohesiveness, and SSC) (R² > 0.94), but its prediction accuracy was low for brittleness and chewiness (R² < 0.9). Overall, its performance and generalization ability were inferior to the ANN model. This study shows that ANN models based on dielectric properties establish a technical foundation for the non-destructive, automated monitoring of goji berry storage quality, thereby providing a critical tool for dynamic quality tracking and value assessment within integrated warehouse management systems. Full article

Soluble solids content is the most important attribute related to the quality and price of apples. The objective of this study was to detect the soluble solids content (SSC) in ‘Fuji’ apples using hyperspectral imaging combined with a deep learning algorithm. The hyperspectral images of 570 apple samples were obtained and the whole region of apple sample hyperspectral data was collected and preprocessed. In addition, a method involving multi-attention convolutional neural network (MA-CNN) is proposed, which extracts spectral and spatial features from hyperspectral images by embedding channel attention (CA) and spatial attention (SA) modules in a convolutional neural network. The CA and SA modules help the network adaptively focus on important spectral–spatial features while reducing the interference of redundant information. Additionally, the Bayesian optimization algorithm (BOA) is used for model hyperparameter optimization. A comprehensive evaluation is conducted by comparing the proposed model with CA-CNN models, SA-CNN, and the current mainstream models. Furthermore, the best prediction performances for detecting SSC in apple samples were obtained from the MA-CNN model, with an ${\mathrm{R}}_{\mathrm{p}}^2$ value of 0.9602 and an RMSEP value of 0.0612 °Brix. The results of this study indicated that the MA-CNN algorithm combined with hyperspectral imaging technology can be used as an effective method for rapid detection of apple quality parameters. Full article

Fruit quality and skin color are key determinants of apple marketability. This study investigated the effect of fruit maturity and 1-methylcyclopropene (1-MCP) treatment on quality attributes and chlorophyll (Chl) degradation in ‘Golden Ball’ apples during long-term cold storage. Apples were harvested at two maturity stages—low maturity (LM, starch pattern index [SPI] 6) and high maturity (HM, SPI 8)—based on Cornell’s SPI method, and subsequently treated with 1-MCP (LM+1-MCP and HM+1-MCP) before storage. At harvest, HM fruits exhibited significantly higher soluble solid content (SSC), titratable acidity (TA), red coloration (a*), index of absorbance difference (I_AD), and respiration rate compared to LM fruits, although ethylene production, internal ethylene concentration (IEC), and firmness were not affected by maturity stage. During storage, HM fruits showed a more rapid decline in firmness, SSC, and TA, along with increased IEC, respiration rate, and a* value, and reduced I_AD and Chl contents. Consistently, expression levels of genes associated with ethylene biosynthesis and Chl degradation were also higher in HM fruits. However, application of 1-MCP effectively suppressed ethylene production and respiration, thereby slowing the deterioration of fruit quality and Chl degradation in both maturity groups. Notably, the LM+1-MCP group demonstrated stronger ethylene inhibition and retained higher Chl levels than the HM+1-MCP group. Overall, the findings demonstrate that applying 1-MCP at the LM stage is a superior strategy for maintaining the postharvest quality of the apples. Full article

To address the limitations of single indices in comprehensively evaluating the quality of Korla fragrant pears, this study proposes the firmness–soluble solids ratio (FSR), defined as the ratio of average firmness (FI) to soluble solid content (SSC) for each individual fruit, as a novel index. Using 600 samples from five maturity stages with hyperspectral imaging (950–1650 nm), the dataset was split 4:1 by the SPXY algorithm. The findings demonstrated that FSR’s effectiveness in quantifying the dynamic relationship between FI and SSC during maturation. The developed multiscale convolutional neural network–long short-term memory (MSCNN–LSTM) model achieved high prediction accuracy with determination coefficients of 0.8934 (FI), 0.8731 (SSC), and 0.8610 (FSR), and root mean square errors of 0.9001 N, 0.7976%, and 0.1676, respectively. All residual prediction deviation values exceeded 2.5, confirming model robustness. The MSCNN–LSTM showed superior performance compared to other benchmark models. Furthermore, the integration of prediction models with visualization techniques successfully mapped the spatial distribution of quality indices. For maturity discrimination, hyperspectral-based partial least squares discriminant analysis and linear discriminant analysis models achieved perfect classification accuracy (100%) under five-fold cross-validation across all five maturity stages. This work provides both a theoretical basis and a technical framework for non-destructive evaluation of comprehensive quality and maturity in Korla fragrant pears. Full article

The highbush blueberry (Vaccinium corymbosum L.) is a promising fruit species due to its high nutritional value and health benefits. This study, conducted between 2020 and 2024, monitored the phenological and pomological characteristics of 32 different blueberry cultivars grown in the Czech Republic. The evaluation was carried out according to Czech Republic standardized methodologies, BBCH (Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie) and GRIN (Genetic Resources Information Network), and included parameters such as fruit size, flavor, aroma, firmness, color, and soluble solids content (SSC in °Brix). The correlation between individual traits was assessed, along with their phenotypic stability. The results showed that all cultivars exhibited high pomological values, making them suitable for breeding programs. The cultivars ‘Collins’ and ‘Patriot’ received the highest flavor ratings. Firmness, aroma, and color traits were found to be correlated with consumer preferences. The interannual coefficient of variation (CV) obtained for the evaluated blueberry cultivars differed for both pomological and phenological traits, allowing the identification of genotypes with high stability (CV ≤ 10%) and their potential use in targeted breeding programs and industrial production. The ‘Pink Lemonade’ blueberry cultivar, in particular, combines unique color characteristics with a strong aroma. Overall, this study provides valuable insights for future breeding efforts aimed at improving blueberry quality and cultivar adaptability under different cultivation conditions. Full article

To enhance the economic benefits of the Korla fragrant pear industry and reduce fruit loss rates, this study investigates changes in pear fruit quality during storage under different damage types. An adaptive neuro-fuzzy inference system (ANFIS), tested with eight different membership functions, was used to predict the hardness and soluble solids content (SSC) of pears stored under various damage conditions. The results showed that both hardness and SSC of damaged pears decreased with prolonged storage time. During identical storage periods, more severe damage led to faster declines in hardness and SSC, among which impact loads and combined impact-compression loads caused the most rapid reductions in pear hardness and SSC. The ANFIS model with the gauss2mf membership function achieved optimal prediction accuracy for pear hardness (RMSE = 0.2207, R² = 0.9434); the ANFIS model with the trimf membership function yielded the best prediction for pear SSC (RMSE = 0.2016, R² = 0.9701). This study provides a theoretical basis for optimizing warehouse management and quality control of Korla fragrant pears, and for determining the optimal treatment window during storage. Full article

Blueberries, widely recognized for their antioxidant capacity, have driven rapid growth in China’s blueberry industry owing to their significant health benefits and economic value. However, a comprehensive evaluation for blueberry quality traits and antioxidant capacity remains lacking in China’s domestic research. This study systematically evaluated 26 highbush blueberry cultivars with consistent tree age and cultivation practices, which can better reflect cultivar-dependent trait variation. Key findings revealed Earliblue exhibited the highest soluble solid content (SSC) and the lowest titratable acidity (TA), while Bluechip had the most abundant vitamin C (VC). Glucose and fructose were the main components of soluble sugars in highbush blueberries, accounting for over 97% of the total sugars. Citric acid was the dominant organic acid in nearly all cultivars. Malvidin 3-O-galactoside, delphinidin 3-O-galactoside, delphinidin 3-O-arabinoside, malvidin 3-O-arabinoside and petunidin 3-O-galactoside were the most abundant anthocyanins. The 26 blueberry cultivars were graded into high-, medium- and low-anthocyanin content groups. Correlation analysis divided the 14 anthocyanins into two types: antioxidant-related anthocyanins and other anthocyanins. The five cultivars with the highest comprehensive evaluation scores were Sunrise, Bluegold, Elliott, Amblue and Briteblue. These results may establish empirical selection criteria for the selection and efficient utilization of high-quality blueberry cultivars. Full article

Postharvest deterioration remains a major challenge for blackberries, particularly in warm climates where shelf life is limited. This study evaluated the postharvest performance of three thornless cultivars grown under subtropical conditions: ‘Prime-Ark® Freedom’, ‘Osage’, and ‘Sweet-Ark™ Ponca’ using a two-phase cold storage regime (0 °C for 7 days, then 5 °C for 9 days). Over two seasons (2023–2024), fruit quality was assessed at days 0, 7, 12, and 16, focusing on weight loss, leakiness, red drupelet reversion (RDR), soluble solids content (SSC), titratable acidity (TTA), SSC/TTA ratio, and ascorbic acid. Cultivar responses varied: ‘Prime-Ark^® Freedom’ showed strong storage resilience with minimal weight loss and fewer disorders, although SSC and ascorbic acid levels were lower. ‘Osage’ maintained high SSC, SSC/TTA, and ascorbic acid, favoring shorter storage for fresh markets. ‘Sweet-Ark™ Ponca’ had high SSC/TTA ratios but was prone to leakiness and RDR. Ascorbic acid declined during storage in 2023 but was better preserved in 2024, especially with ‘Prime-Ark^® Freedom’. Our results provide actionable insights for cultivar selection in postharvest strategies that are critical to preserving fruit quality and extending shelf life in blackberries. Full article