Apple Quality Research Articles

Qualitative and quantitative assessment of apple quality using bulk optical properties in combination with machine learning and chemometrics techniques

This study aimed to understand the quantitative relationship between the bulk optical properties (BOP), soluble solids content (SSC), and fruit firmness (FF) of apples, along with the qualitative discrimination of apple cultivar and shelf-life. The absorption coefficient (μa) and reduced scattering coefficient (μs′) of 200 apples from four cultivars during 36-days shelf-life were determined using the single integrating sphere technique in 500-1000 nm. Partial least squares regression (PLSR) and random forest (RF) algorithms were used to establish quantitative prediction models for SSC and FF based on the BOP of apples. The results indicated that the PLSR models based on μɑ and μs′ were optimal for quantitative prediction of SSC (R2p=0.749, RMSEP=0.507) and FF (R2p=0.745, RMSEP=0.571), respectively. RF and linear discriminant analysis (LDA) were used to establish qualitative models for discriminating apple cultivar and shelf-life, demonstrating that the RF model based on μɑ and μɑ+ μs′ had the highest accuracy for the determination of apple cultivar and shelf-life, respectively, with the prediction set reaching 93.2 % and 85.7 %. Overall, RF was better than LDA for qualitative discrimination; however, it was less effective than PLSR for quantitative modeling.

Comparative Analysis of Some Morpho-cultural Characters of Venturia inaequalis (Apple Scab Pathogen) under Kashmir Conditions

Apple (Malus × domestica Borkh.) represents one of the most widely cultivated and economically important temperate fruit crops in the world. However, its cultivation faces significant challenges due to various fungal pathogens, particularly apple scab inflicted by Venturia inaequalis, which has a profound impact on the yield and quality of apple, resulting in substantial economic loss. The pervasive nature of V. inaequalis and its ability to damage crops poses a serious threat to sustainable apple production. In this study, the morpho-cultural characteristics of V. inaequalis were systematically analyzed and compared between the Shopian and Baramullah districts of the Kashmir Valley. Ten isolates from each district were grown on Malt Extract Agar (MEA) and Potato Dextrose Agar (PDA) for comparative analysis. The colonies were characterized by a compact hue ranging from greyish-green to blackish and exhibited a densely velvety texture. Mycelial growth was predominantly aerial, with some isolates displaying partial irregularity in colony margins, while others exhibited greater uniformity. The mean colony radii for potato dextrose agar and malt extract agar media was measured as 23.01 mm and 28.50 mm for the Shopian district, and 28.09 mm and 33.33 mm for the Baramullah district, respectively. The mean conidial spore density was recorded at 27.87 spores/cm² for the Baramullah district and 34.67 spores/cm² for the district Shopian, respectively. This variation could be attributed to several factors, including genetic diversity within the pathogen populations, differences in altitude, climate, and other environmental factors, the selection pressure exerted by fungicide applications, the emergence of novel pathogen races, and phenotypic plasticity driven by the differing agricultural practices and microclimatic conditions in the respective regions.

Effect of Asafoetida Extract Solution on Red Apple Quality with a Focus on the Mechanical Properties of Peduncle, Rate Fruit Drop and Orchard Pest Control

Effect of Asafoetida Extract Solution on Red Apple Quality with a Focus on the Mechanical Properties of Peduncle, Rate Fruit Drop and Orchard Pest Control

Combining Dielectric and Hyperspectral Data for Apple Core Browning Detection

Apple core browning not only affects the nutritional quality of apples, but also poses a health risk to consumers. Therefore, there is an urgent need to develop a fast and reliable non-destructive detection method for apple core browning. To deal with the challenges of the long incubation period, strong infectivity, and difficulty in the prevention and control of apple core browning, a novel non-destructive detection method for apple core browning has been developed through combining hyperspectral imaging and dielectric techniques. To reduce the computational complexity of high-dimensional multi-view data, canonical correlation analysis is employed for feature dimensionality reduction. Then, the two low-dimensional vectors extracted from two different sensors are concatenated into one united feature vector; therefore, the information contained in the hyperspectral and dielectric data is fused to improve the detection accuracy of the non-destructive method. At last, five traditional classifiers, such as k-Nearest Neighbors, a support vector machine with radial basis function kernel and polynomial kernel, Decision Tree, and neural network, are trained on the fused feature vectors to discriminate apple core browning. The experimental results on our own constructed dataset have shown that the sensitivity, specificity, and precision of SVM with RBF kernel based on concatenated 70-dimensional feature vectors extracted via canonical correlation analysis reached 99.98%, 99.70%, and 99.70%, respectively, which achieved better results than other models. This study can provide theoretical assurance and technical support for further development of higher accuracy and lower-cost non-destructive detection devices for apple core browning.

Natural variation in MdNAC5 contributes to fruit firmness and ripening divergence in apple

Abstract Fruit firmness is an important trait for characterizing the quality and value of apple. It is also serves as an indicator of fruit maturity, as it is a complex trait regulated by multiple genes. Re-sequencing techniques can be employed to elucidate variations in such complex fruit traits. Here, the whole genomes of 294 F1 hybrids of ‘Fuji’ and ‘Cripp's Pink’ were re-sequenced, and a high-density bin-map was constructed using 5,014 bin markers with a total map distance of 2,213.23 cM and an average map distance of 0.44 cM. Quantitative trait loci (QTLs) of traits related to fruit were mapped, and an A-T allele variant identified in the coding region of MdNAC5 was found to potentially regulate fruit firmness and ripening. The overexpression of MdNAC5A resulted in higher production of methionine and 1-aminocyclopropanecarboxylic acid compared to MdNAC5T, leading to reduced fruit firmness and accelerated ripening in apples and tomatoes. Furthermore, the activities of MdNAC5A and MdNAC5T were enhanced through their differential binding to the promoter regions of MdACS1 and MdERF3. Spatial variations in MdNAC5A and MdNAC5T caused changes in MdACS1 expression following their interaction with MdERF3. Ultimately, utilizing different MdNAC5 alleles offers a strategy to manipulate fruit firmness in apple breeding.

Practical 1-Methylcyclopropene Technology for Increasing Apple (Malus domestica Borkh) Storability in the Aksu Region.

In recent years, Aksu apple has become popular with consumers because of its unique texture and taste. At present, maintaining quality during storage is the key problem with the apples in the Aksu region. 1-Methylcyclopropene (1-MCP) can delay fruit senescence, so is widely used in fruit preservation. However, many factors affect the preservation effect of 1-MCP. The effects of 1-MCP concentration (0 µL·L-1, 1 µL·L-1, 3 µL·L-1, 5 µL·L-1, and 8 µL·L-1) and postharvest application time (0, 1 and 2 d after harvest) on the quality of stored apple were studied. It was found that 1 µL·L-1 1-MCP was more beneficial in improving the quality of stored apples, reduced the respiration intensity and decay rate, increased the fruit firmness and total soluble solid content, and reduced the relative content of ester volatile aroma components. In addition, 1-MCP treatment applied at different postharvest times also affected the sensory quality and flavor of apples. The effect of 1-MCP treatment immediately after harvest was better.

Strigolactone Preserves Fresh-Cut Apple Quality during Shelf Life

Strigolactone Preserves Fresh-Cut Apple Quality during Shelf Life

UGV‐Based Precision Spraying System for Chemical Apple Blossom Thinning on Trellis Trained Canopies

ABSTRACTBlossom thinning is one of the key steps in apple crop load management that improves the quality of apples, reduces stress on the trees, and avoids the likelihood of biennial bearing. Conventional chemical blossom thinning such as air‐blast spraying can lead to excessive use of chemical thinner to ensure full coverage, which can also cause leaf damage fruit russeting. In addition, a well‐trained operator is required to use these chemical spraying systems. To address these challenges, a UGV‐based precision spraying system was developed for automated and targeted chemical blossom thinning for apples. The system is capable of automatically driving along the tree row in the orchard environment during blooming stage, locating apple flower clusters to be thinned using a real‐time machine vision system, and precisely spraying the chemical thinner to the targeted flower clusters. A set of field tests were conducted to evaluate the performance of the UGV‐based target spraying system by comparing it to a conventional air‐blast sprayer (ABS) and a previous prototype named the cartesian target sprayer (CTS). Tests showed that the flower cluster detection reached a precision of 93.8%. The UGV‐based spraying system used 2.2 L of chemical thinner to finish the chemical thinning for 30 apple trees, followed by the ABS and CTS with 4.2 and 2.4 L usage, respectively. The robotic system also obtained an average fruit set of 2.2 per cluster after thinning, which was comparable to that with the air blast sprayer. The findings indicated that the robotic thinning system demonstrated a 66.7% reduction in chemical usage compared to the ABS and exhibited a 43.0% faster operational pace than the CTS, while attaining a comparable fruit set per cluster. The outcomes of the study provided guidance for developing a full scale robotic chemical thinning system for modern apple orchards.

Effect of organic inputs on yield and quality of custard apple (Annona squamosa L.)

Effect of organic inputs on yield and quality of custard apple (Annona squamosa L.)

Effects of Water and Nitrogen Regulation on Apple Tree Growth, Yield, Quality, and Their Water and Nitrogen Utilization Efficiency.

Apple tree productivity is influenced by the quantity of water and nutrients that are supplied during planting. To enhance resource utilization efficiency and optimize yields, a suitable strategy for supplying water and nitrogen must be established. A field experiment was conducted using a randomized block group design on five-year-old apple trees in Ningxia, with two irrigation lower limit levels (55%FC (W1) and 75%FC (W2)) and four N application levels (0 (N1), 120 (N2), 240 (N3), and 360 (N4) kg·ha-1). Our findings showed that leaf N content increased with a higher irrigation lower limit, but the difference was not statistically significant. However, the leaf N content significantly increased with increasing N application. The growth pattern of new shoots followed logistic curve characteristics, with the maximum new shoot growth rate and time of new shoot growth being delayed under high water and high nitrogen treatments. Apple yield and yield components (weight per fruit and number of fruits per plant) were enhanced under N application compared to no N application. The maximum apple yields were 19,405.3 kg·ha-1 (2022) and 29,607 kg·ha-1 (2023) at the N3 level. A parabolic relationship was observed between apple yield and N application level, with the optimal range of N application being 230-260 kg⸱ha-1. Apple quality indicators were not significantly affected by the irrigation lower limit but were significantly influenced by N application levels. The lower limit of irrigation did not have a significant impact on the quality indicators of the apples. Water and N utilization efficiencies improved with the W2 treatment at the same N application level. A negative relationship was observed between the amount of nitrogen applied and the biased productivity of nitrogen fertilizer. The utilization of nitrogen fertilizer was 127.6 kg·kg-1 (2022) and 200.3 kg·kg-1 (2023) in the W2N2 treatment. The apple yield was sustained, the quality of the fruit improved, and a substantial increase in water productivity was achieved with the W2N3 treatment. The findings of this study can be used as a reference for accurate field irrigation.

Metagenomic and transcriptome insights into the disease resistance mechanisms in fresh-cut apple under pyridoxine treatment

Microbial spoilage poses a significant challenge to fresh-cut apples during storage, impacting quality and consumer health. This study explores pyridoxine’s (vitamin B6; VB6) potential mode of action to mitigate microbial spoilage in fresh-cut apples through physiological, transcriptomic, and metagenomic analysis. VB6 notably reduces microbial spoilage at room temperature by suppressing bacterial genera (Pseudomonas, Curtobacterium, Frigoribacterium) and fungal genera (Alternaria, Penicillium, Aureobasidium, Pseudogymnoascus) proliferation. Spoilage-causing identified biomarkers include species related to Pseudomonas, Curtobacterium, Frigoribacterium, and Penicillium. KEGG analysis suggests correlations of induced disease resistance with tropane alkaloids biosynthesis, plant-pathogen interaction, and phenylpropanoid biosynthesis pathways in fresh-cut apples. Moreover, VB6 treatment enhanced the antioxidant system via maintaining higher total phenolic contents, total flavonoid contents, and ascorbic acid under elevated catalase, superoxide dismutase, and ascorbate peroxidase enzymes activities, induced disease resistance under higher enzymes activities including phenylalanine ammonialyase, chitinase, cinnamate 4-hydroxylase, β-1,3-glucanase, and 4-coumarate: co-enzyme A ligase enzymes activities, maintained elevated VB6 contents, and reduced H2O2 accumulation. Notably, 6 elevated transcription factors involving WRKY, NAC and MYB might regulate disease resistance pathways in fresh-cut apples under VB6 treatment. This research establishes a theoretical and practical foundation for preserving post-processing quality of fresh-cut apples by restraining microbial proliferation through the proposed VB6-induced disease resistance regulatory mechanism.

Efecto de bioestimulantes sobre la calidad del fruto de manzana Golden Glory en Chihuahua, México

The cultivation of apple (Malus domestica (Borkh.) Borkh.) holds significant global importance due to their flavor and nutritional value. In Mexico, Chihuahua leads in production, yet the response of the Golden Glory variety to biostimulants remains unstudied. This study aimed to evaluate the effect of biostimulants on fruit quality in Golden Glory apple. Conducted in Namiquipa, Chihuahua, during the 2023 season, the study employed randomized experimental design with treatments (amino acids, algae, fulvic acids, and a control) spraying weekly from flowering to near harvest. Fruit characteristics were evaluated 90 days post-initial treatment. Amino acids significantly improve fruit weight (27.98 %), diameters (8.41 % polar and 9.28 % equatorial), color (178.8 %), and total soluble solids (TSS;5.72 %), while reducing malic acid content and enhancing TSS/AT ratio by 23.21 %, with no impact firmness. Fruit quality met marketing standards. Seaweed and fulvic acids treatment showed no significant improvement parameters. These results underscore amino acids ‘efficacy in enhancing 'Golden Glory' apples quality. Keywords: amino acids, seaweed, fulvic acids, Malus domestica Borkh

Effect of water chestnut based edible coating on the physicochemical quality and shelf life of apples

Preservation of perishable fruits and vegetables through edible coatings having functional roles, has gained importance now a days. The present study was designed to investigate the effect of water chestnut powder-based edible coatings on the quality and shelf life of apples (Kala kullu). Two treatments, T1 and T2, were developed by utilizing two different concentrations of heated water chestnut powder (2% and 2.5%, respectively). Whereas, 2% guar gum (T0+) was accustomed as positive control, and uncoated apples as negative control (T0−). Before developing emulsions, water chestnut powder was subjected to chemical, functional and structural analysis, after that emulsions developed were used to coat apples, which were investigated for physicochemical and sensory parameters, during 80 days storage at 20 °C. The findings indicated that emulsion capacity, emulsion stability, foaming capacity and viscosity of the coatings was significantly high (p ≤ 0.05) for T2, as compared to T1. During the storage of apples, significant (p ≤ 0.05) decrease in the weight loss and decay percentage was observed in T2. Increased pH and decrease in titratable acidity were also noted in T2. Coated apples (both T2 and T1) maintained the firmness of apples during storage duration, as compared to the uncoated ones. Significantly high (p ≤ 0.05) total phenolic contents and antioxidant capacity was shown by T2 as compared to other treatments, as during storage a comparatively lesser decrease in the values of these parameters was observed for T2. Sensory analysis results showed that T2 was given high scores for color, texture, taste, flavor and overall acceptability, as compared to other treatments. It was noted that T2 showed better outcomes in terms of sensory and physiochemical attributes, thus edible coatings having 2.5% water chestnut powder could be used to increase the shelf life of fruits.Graphical abstract

Paecilomyces variotii extracts promote growth and alleviate nutrient deficiency symptoms in apple

It is essential to find environment-friendly agrochemicals to cope with the problems of nutrient imbalance, fruit quality decline, and physiological disorders during apple fruit production, which is beneficial for improving the quality and yield of apple. A natural extract from Paecilomyces variotii (ZNC), an endophytic fungus, has been used widely to enhance crop performance. However, an understanding of the mechanism underlying ZNC-triggered growth and alleviation of nutrient deficiency-associated symptoms in apples remains elusive. Here, the photosynthesis, leaf growth, and fruit quality were enhanced by adding ZNC. In addition, ZNC relieved nutrient deficiency-related symptoms promoted the differentiation of root morphology and vitality, and reduced the accumulation of osmoprotectants and reactive oxygen species, thereby promoting growth under normal and nutrient-deficient conditions. Finally, genome-wide RNA sequencing reveals the ZNC-regulated mechanisms involved in hormone and metal ion pathways. Our study reveals the role of ZNC in promoting growth and improving the quality of apple, providing a new direction for reducing the use of chemical fertilizers and pesticides.

Impact of pre-harvest application of 1-methylcyclopropene (1-MCP) on fruit quality, physiological disorders and respiration rate of ‘Scilate’ apple

The ethylene inhibitor 1-methylcyclopropene (1-MCP) is widely used in the apple industry as a post-harvest fumigation application to slow down the ripening process and maintain fruit quality during storage. With the development of a sprayable formulation (Harvista™, Agrofresh Inc, USA), it is becoming increasingly common in the apple industry to apply 1-MCP as a pre-harvest spray. This study investigated the impact of pre-harvest 1-MCP applied 1 week prior to harvest as a foliar application at 11.4 L ha−1 in 1000 L water, on the quality and respiration rate of ‘Scilate’ apples grown in the Huon Valley, Southern Tasmania, Australia. Two trials were undertaken, trial 1 examined fruit quality, flesh browning (FB) and fruit softening in 1-MCP treated and untreated fruit while trial 2 compared the respiration rate of 1-MCP treated and untreated fruit. Despite no effect on fresh fruit quality attributes, pre-harvest spray application of 1-MCP influenced post-harvest fruit quality, storability, and respiration rate of apples. Fruit treated with 1-MCP showed higher malic acid concentration (1.2 g L−1 vs 0.9 g L−1) and lower juice pH (4.6 vs 4.9) even after 7.5 months of regular air cold-storage along with a six-fold reduction in fruit softening in comparison to untreated fruit (2% vs 13%). Pre-harvest treatment of 1-MCP reduced respiration rate by 32%, and incidence of CO2 injury by over 40%. The incidence of radial type (senescent related) FB was reduced by 100%. A significant proportion of treated apples still suffered from severe CO2 injury. This study has demonstrated that pre-harvest application of 1-MCP to ‘Scilate’ fruit can be useful in maintaining long-term fruit quality during storage, reducing respiration rate, and lowering the incidence of FB in general. However, the risk of severe CO2 injury remains, especially with larger fruit harvested from trees with lighter crop loads.

The relative importance of postharvest eating quality and sustainability attributes for apple fruit: A case study using new sensory–consumer approaches

Consumer-sensory methods based on check-all-that-apply (CATA) for texture and flavour terms and conceptual descriptors offer alternatives for characterising eating quality. In this study, ‘Red Delicious’, ‘Gala’ and ‘Scilate’ apples (Malus domestica Borkh.), which were of comparable instrumental firmness, and similar in crispness and apple flavour, evoked profoundly different consumer responses. Mean liking scores from 122 consumers were 7.1 (∼like moderately), 5.8 (∼like slightly), and 5.1 (∼neither like nor dislike) for ‘Scilate’, ‘Gala’, and ‘Red Delicious’ respectively, and cluster analysis indicated three consumer-segments: one that preferred ‘Scilate’ over the other cultivars (62 % of consumers), another that liked ‘Scilate’ and ‘Gala’ equally over ‘Red Delicious’ (26 %), and a small third segment that liked ‘Red Delicious’ and ‘Gala’ equally over ‘Scilate’ (12 %). In the associated experimental auction, consumers were provided with $US3, and the mean bids for ‘Scilate’, ‘Gala’, and ‘Red Delicious’ reflected the pattern of consumer liking at $US1.72, $US0.79, and $US0.52, respectively. Correspondence analysis plots of CATA data indicated that ‘Scilate’ was associated with sensory descriptors sweet, fruity, tropical and pear flavours and positive conceptual descriptors including exciting, complex, unique, premium, yummy, intense, and powerful. ‘Gala’ and ‘Red Delicious’ were associated with sensory descriptors including old, mealy, bland, green-grassy and sour-acidic and negative conceptual descriptors dissatisfied, inferior, boring, disappointing, and uninspiring. A best-worst scaling methodology was used to elicit consumers’ priorities regarding the aspects of apple quality and production sustainability. Despite the profound differences in eating quality uncovered in the hedonic and CATA tasks, the statement ‘tastes like the best apple eaten today’ was assessed as being only 23 % as important as the statement ‘grown in a way that is sustainable and does not harm the environment’ in consumer choices. This notable outcome was contradicted in a matching online study changing the eating quality statement ‘tastes like the best apple eaten today’ to ‘Crisp, juicy and sweet’ (the attributes most frequently identified in the sensory CATA). This suggests that trade-offs between eating quality and sustainability are subject to context effects associated with whether taste is an experienced or imagined factor. There is an urgent need to better understand how consumers’ needs for sustainability in the food production system might alter what is acceptable in terms of eating quality.

Characterization of Eurotium cristatum Fermented Thinned Young Apple and Mechanisms Underlying Its Alleviating Impacts on Experimental Colitis.

A hundred million tons of young apples are thinned and discarded in the orchard per year, aiming to increase the yield and quality of apples. We fermented thinned young apples using a potential probiotic fungus, Eurotium cristatum, which notably disrupted the microstructure of raw samples, as characterized by the scanning electron microscope. Fermentation substantially altered the metabolite profiles of samples, which are predicted to alleviate colitis via regulating inflammatory response and response to lipopolysaccharide by using network pharmacology analysis. In vivo, oral gavage of water extracts of E. cristatum fermented young apples (E.YAP) effectively alleviated DSS-induced colitis, restored the histopathology damage, reduced the levels of inflammatory cytokines, and promoted colonic expressions of tight junction proteins. Moreover, E.YAP ameliorated gut dysbacteriosis by increasing abundances of Lactobacillus,Blautia, Muribaculaceae, and Prevotellaceae_UCG-001 while inhibiting Turicibacter, Alistipes, and Desulfovibrio. Importantly, E.YAP increased colonic bile acids, such as CA, TCA, DCA, TUDCA, and LCA, thereby alleviating colitis via PXR/NF-κB signaling. Furthermore, a synbiotic combination with Limosilactobacillus reuteri WX-94, a probiotic strain isolated from feces of healthy individuals with anti-inflammatory properties, augmented anticolitis capacities of E.YAP. Our findings demonstrate that E.YAP could be a novel, potent, food-based anti-inflammatory prebiotic for relieving inflammatory injuries.

Application of Advanced Deep Learning Models for Efficient Apple Defect Detection and Quality Grading in Agricultural Production

In this study, a deep learning-based system for apple defect detection and quality grading was developed, integrating various advanced image-processing technologies and machine learning algorithms to enhance the automation and accuracy of apple quality monitoring. Experimental validation demonstrated the superior performance of the proposed model in handling complex image tasks. In the defect-segmentation experiments, the method achieved a precision of 93%, a recall of 90%, an accuracy of 91% and a mean Intersection over Union (mIoU) of 92%, significantly surpassing traditional deep learning models such as U-Net, SegNet, PSPNet, UNet++, DeepLabv3+ and HRNet. Similarly, in the quality-grading experiments, the method exhibited high efficiency with a precision of 91%, and both recall and accuracy reaching 90%. Additionally, ablation experiments with different loss functions confirmed the significant advantages of the Jump Loss in enhancing model performance, particularly in addressing class imbalance and improving feature learning. These results not only validate the effectiveness and reliability of the system in practical applications but also highlight its potential in automating the detection and grading processes in the apple industry. This integration of advanced technologies provides a new automated solution for quality control of agricultural products like apples, facilitating the modernization of agricultural production.

Apple firmness detection method based on hyperspectral technology

Firmness is a key indicator of apple quality. Building a predictive model for apple firmness based on hyperspectral technology and regression algorithms can achieve rapid, non-destructive, and high-throughput detection of apple firmness. This paper adopts an Adaptive Window Length Savitzky-Golay Smoothing (AWL-SG smoothing) algorithm based on the Savitzky-Golay Smoothing (SG smoothing) algorithm, which can adaptively adjust the window length according to the change rate of spectral data at different wavelengths. SG smoothing, AWL-SG smoothing, Standard Normal Variate (SNV), and Multiplicative Scatter Correction (MSC) algorithms were used to preprocess the original spectral data, and Partial Least Squares (PLS), Ridge Regression (Ridge), and Kernel Ridge Regression (Kernel Ridge) predictive models were constructed to analyze the impact of different preprocessing methods on model prediction accuracy. The prediction models established with spectral data preprocessed by SG smoothing and AWL-SG smoothing algorithms showed significant improvement in predictive performance on the basis of the original spectral data, among which the AWL-SG smoothing algorithm performed the best. The Ridge model established with spectra data preprocessed by AWL-SG smoothing achieved an R2 of 0.8914 in the test set. Successive Projection Algorithm (SPA), Principal Component Analysis (PCA), and Independent Component Analysis (ICA) dimensionality reduction algorithms were used to reduce the dimensions of the full-band spectral data preprocessed by SG smoothing and AWL-SG smoothing algorithms, and Ridge and Kernel Ridge prediction models were constructed. The results showed that both SPA and PCA algorithms could improve the predictive performance of the models, with the PCA performing the best. The combination of AWL-SG + PCA + Ridge achieved the best predictive effect, with an R2 of 0.9146 in the test set.

Действие органоминерального комплекса «Белый Жемчуг» на качество и выход товарных плодов яблони после длительного хранения

Biological fertilizers improve fruit quality; for instance, organomineral, or activated mixes are known to increase consumer qualities of apples. This article describes the effect of a new activated complex (non-root treatment) on the yield, chemical composition, and physiological disorders, e.g., scald and brown spot, of commercial apples after long-term storage. The research featured the natural activated complex of the Beliy Zhemchug (White Pearl) brand. The apple trees were divided into two groups: 1 – untreated control trees; 2 – trees that underwent a non-root treatment with the activated complex (1% solution of its Antifreeze variant + 1% solution of the Drip Ca + Mg variant). The trees belonged to the Sinap Orlovskiy cultivar, which is highly susceptible to brown spot and scald, both in the orchard and during long-term storage. The apples were studied for chemical composition and consumer qualities after long-term storage in a CV114-S refrigerator at +2°C and a relative humidity of 85–90%. The non-root treatment of apple trees with the Beliy Zhemchug activated complex had no significant effect on the content of soluble solids, total sugars, titrated acids, and ascorbic acid in ripe apples. Weather conditions affected the chemical composition 30 days before harvesting. The non-root treatment increased the yield of commercial apples by 1.62 times after long-time storage. The scald, brown spot, and moniliosis damage decreased by 1.9, 2.6, and 1.9 times, respectively. The activated fertilizers of the Beliy Zhemchug brand proved highly efficient as additional techniques in common apple cultivation and could be recommended to improve the quality and yield of commercial fruits after long-term storage.