High-quality Apple Research Articles

Lactic acid bacteria sequential fermentation improves viable counts and quality of fermented apple juice via generating two logarithmic phases

This study investigated the impact of lactic acid bacteria (LAB) sequential fermentation on viable counts and apple juice quality. The optimal fermentation conditions were obtained by a step-by-step optimization process, including pH 4.5, temperature 37 °C, the second inoculation time 16 h, total fermentation time 40 h and fermentation sequence (first 21,805 + 21,828, second 20,241). Under the optimal conditions, sequential fermentation allowed LAB to experience two logarithmic phases, increasing viable counts to 1.38 × 108 CFU/mL, exceeding simultaneous fermentation for 24 h and 40 h by 4.10 × 107 CFU/mL and 5.40 × 107 CFU/mL, respectively. This process enhanced sugar utilization, yielding more lactic acid and polyphenols. Furthermore, sequential fermentation improved DPPH (71.71 %) and ABTS (84.79 %) scavenging rates, and enriched volatile compounds, particularly beta-Damascenone, potentially contributing to floral and richer apple flavor. Sequential fermentation also achieved optimal sensory acceptability. This study proposes a novel strategy for high-density LAB fermentation to produce high-quality apple juice.

The physicochemical components, amino acids, organic acids, phenolic compounds and antioxidant capacity of apple ciders: According to geographical origin and altitude of Fuji apple

This study aimed to analyze the physicochemical parameters, amino acids, organic acids, total phenols, total flavonoids and antioxidant capacity of apple ciders fermented with Fuji apple from different regions. The results showed that there are differences in the composition and quality characteristics of ciders fermented with Fuji apple from different regions. The apple ciders fermented with Fuji apple from 11 different producing areas were divided into three categories by cluster heat map analysis. The samples belonging to category I are from Zhaotong. Category II comprises samples from Changli, Weihai, Xingcheng, and Qingyang, while category III includes samples from Liangshan, Yuncheng, Luochuan, Aksu, Jinzhong, and Lingbao. The altitude of the apple production area has an impact on the quality of the apples, consequently affecting the distinctive characteristics of the final apple cider. This research aims to provide a theoretical basis for the development and production of high-quality apple ciders.

Genome‑Wide Identification and Expression Analysis of SPX Domain-Containing Gene Subfamily in Response to Phosphorus-Solubilizing Bacteria in Apple (Malus domestica)

Phosphate is one of the major elements that significantly affects fruit yield and quality. The aim of the study was to determine whether using phosphorus-solubilizing bacteria could produce high-quality apple nursery trees. Five different treatments were tested on a “Granny Smith” apple cultivar that was grafted onto an M.9 rootstock. These were 100% P, 50% P, 50% P + Bacillus megatarum (plant growth promoting rhizobacteria, PGPR), 0%P, and 0%P + PGPR. The study also identified the SPX gene family, which is essential for plant growth and development and responds to phosphorus (P) stress. A total of 72 SPX genes were identified in different plant species based on structural and phylogenetic analysis. The apple genome contains seven different SPX genes distributed on five of the 17 chromosomes. Gene structure and motif analysis showed that SPX genes show a relatively conserved exon/intron arrangement and motif composition in five different species: apple, strawberry, peach, apricot, and grape. Protein–protein network analysis showed that SPX proteins are closely related to proteins involved in P metabolism in apple. The digital expression profiles of MdSPX genes among 47 apple tissues were characterized to provide insight into their potential functions. RT-qPCR revealed that the expression level of all MdSPXs was significantly downregulated in 50% P + PGPR treatments, indicating that 50% P combined with PGPR is effectively taken up by the plant, saving it from Pi starvation. These results not only confirm the key role of MdSPXs in Pi homeostasis and the Pi signaling pathway but also clarify the importance of Pi-solubilizing bacteria in plant nutrition.

Research Progress of Rapid Non-Destructive Detection Technology in the Field of Apple Mold Heart Disease.

Apples are rich in vitamins and dietary fiber and are one of the essential fruits in people's daily diet. China has always been a big apple consumer, and with the improvement of people's life quality, nutrition, and health requirements, the demand for high-quality apples has increased year by year. Apple mold heart disease is one of the main diseases affecting apple quality. However, this disease cannot be easily detected from the surface, so it is difficult to detect mold heart disease. Therefore, this paper focuses on the analysis of seven non-destructive detection technologies, including near infrared spectroscopy technology, hyperspectral technology, Raman spectroscopy technology, electronic nose technology, acoustic technology, electrical technology, and magnetic technology, summarizes their application status in the detection of apple mold heart disease, and then analyzes their advantages and disadvantages. Combined with the current rapid development of artificial intelligence (AI) technology, this paper proposes the future development trends of using non-destructive technologies to detect apple mold heart disease. It is expected to provide basic theory and application references for the intelligent detection of apple mold heart disease.

FEATURES PRODUCTIVITY FORMATION OF RED-FLESH APPLE VARIETIES

In the changing conditions of Transcarpathia, red-soft varieties provide high productivity and are less affected by diseases, which will provide a biologically clean technology for their cultivation. Most apples of red pulp varieties at first glance do not differ from the total weight of the fruit. Era apples do not have an intense skin color, but an intense color of the pulp. Fruits of Siren, Odysio, Baia Marissa red with different intensity of placement of lentils and rusting with white edging. Assessing the structure of the flower, it should be noted that almost each has additional pistils and highly developed anthers, which promotes self-pollination. All varieties are characterized by dark pink flowers with very abundant flowering. Rings are formed not only on short biennial branches, but also annual, which should be taken into account when pruning and normalization of flowering. Among the studied varieties, the Baia Marisa variety is the tastiest and with an intense color. It has a red flesh color due to the presence of a special pigment "anthocyanin", which destroys harmful bacteria in the human body and strengthens the immune system. The amount of anthocyanins is 2 times higher than in ordinary apples. Therefore, we offer it for widespread implementation in the production of dietary food. Assessing the economic and biological indicators, it is established that the load on the trees of the third and fourth year of fruiting is quite high with the formation of high quality apples in spite of the critical conditions of 2020. The average number of fruits per tree was up to 60 apples weighing from 188 to 203 g, which provided a high yield of Baia Marisa 33.7 t/ ha in 2019 and the lowest in 2020 30.5 t / ha. The lowest yield in 2019 was characterized by the Odisio variety, which yielded only 29.8 t / ha against 31.2 t / ha in 2020. Measuring biometric indicators, the required height of trees in the fourth year of vegetation was established. The height of the trees of the studied varieties was about 300 cm, except for the variety Sirena, whose trees reached an average of no more than 285 cm in 2019 and an increase in height by 20-25 cm in 2020. The diameter of the trunk is the best in the variety Sirena (232 mm) with the best growth during the year. In terms of the number of annual shoots, the Era variety is in the lead (58 pieces) and the average length of annual growth is 61 cm in two years of comparative evaluation. In difficult climatic conditions, new varieties with red crumbs stood out, the yield of which averaged over the above period 30t / ha of high quality fruit, which provided a selling price of 45-64 UAH. The level of profitability from the cultivation of these varieties was 167 256%. Efficiency indicators depended on the form of product delivery, sales and time of maximum sales. Such products are designed for sale in gift packaging with juices during the Christmas holidays, sale to restaurants for culinary decoration of meat and desserts. Keywords: apple tree, red pulp varieties, productivity, economically valuable traits, economic efficiency

Analysis of Carotenoids and Gene Expression in Apple Germplasm Resources Reveals the Role of MdCRTISO and MdLCYE in the Accumulation of Carotenoids.

Carotenoids play an important role in the coloring and nutritional value of apple (Malus spp.) fruits. Here, six carotenoids, including lutein, zeaxanthin, β-carotene, β-cryptoxanthin, violaxanthin, and neoxanthin, were detected in 105 fruits of apple germplasm resources, which showed a skewed distribution in both the peel and pulp. There were more carotenoids in the peel than in the pulp, and lutein and β-carotene were the primary carotenoids that were present. The expression levels of most carotenoid pathway genes in germplasm fruits during fruit development were higher in the fruits that had an abundance of carotenoids. A linear relationship analysis showed that the expression levels of MdCRTISO and MdLCYE were highly correlated with the content of carotenoids. The leaves accumulated the greatest number of carotenoids, while the roots had the lowest amount. MdCRTISO and MdLCYE were highly expressed in the fruits compared to other tissues. Transgenic calli and transiently transformed fruits confirmed that MdCRTISO and MdLCYE affected the biosynthesis of carotenoids owing to their effects on the expression of other genes for enzymes in the carotenoid pathway. Our findings will extend the understanding of carotenoid biosynthesis in apple and excavate apple germplasm resources with rich carotenoids to breed high-quality apples.

Can synergies in agriculture through an integration of solar energy reduce the cost of agrivoltaics? An economic analysis in apple farming

Agrivoltaics is a relatively new concept of agriculture and photovoltaic power generation on the same area. While an increased land use efficiency and potential synergies between agriculture and power generation speak in favor of agrivoltaics, higher investment cost compared to ground-mounted photovoltaics represents a challenge for a broader market launch in most countries.This work analyses the economic performance of agrivoltaics in apple farming focusing on potential synergies and adverse effects regarding investment requirements and operational cost of the farming system. The analysis is based on literature, expert interviews, and data of three pilot projects in Germany. The results show that average investment cost from the farming system could be reduced by 26% mainly due to partially replacing the hail protection structure. Annual operating costs of the farming system reduce by up to 9% through lower cost for land and maintenance works. However, annual revenues also decrease by about 9% due to an expected reduction in high quality apple yield. Overall, the cost of apple production decreases by about 5%. Regarding the total cost of agrivoltaics, though, the potential contribution from cost savings in the farming sector to reduce the cost of electricity only amounts to <1%. The expected Land Equivalent Ratio of the analyzed agrivoltaic system amounts to 1.54.The results indicate that agrivoltaics in orcharding is only economically feasible if the regulatory framework provides sufficiently high feed-in tariffs or comparable support payments. The work also shows that the theoretical potential of agrivoltaics in apple farming in Germany amounts to 23.8 GWp which could contribute to 13% of the PV development required to meet Germany's climate goals by 2030 [1].

Fast Screening Test of Apple Juice and Surface Water for Patulin Recognition and Quantification

Since a high concentration of patulin causes cytotoxicity, a new approach to the determination of patulin plays an important role in the research and development of new control technologies. The main objective of the paper is to provide a fast screening method for obtaining clean water and high-quality apple juice. Square-wave voltammetry method using a modified Mn (OAP) Cl screen-printed carbon electrode was used for the fast screening test of apple juice and surface water for patulin recognition and quantification. A number of experimental parameters, such as scan rate, type of buffer solution, and pH, were studied and optimized. Thus, a linear concentration dependence was determined in the range 1.00 × 10–12 to 1.00 × 10–8 mol L–1, while the quantification limit was 1.00 × 10–12 mol L–1 and the detection limit was 3.33 × 10–13 mol L–1. High reliability was achieved at the assay of patulin in water and apple juice samples, with a recovery rate of 96.27–99.88%, relative standard deviation (RSD), and a bias value of less than 5.00%. Based on the remarkable outcomes, it can be inferred that the sensor holds promise as a robust instrument for point-of-care detection in the times ahead.

Non-Destructive Hyperspectral Imaging and Machine Learning-Based Predictive Models for Physicochemical Quality Attributes of Apples during Storage as Affected by Codling Moth Infestation

The demand for high-quality apples remains strong throughout the year, as they are one of the top three most popular fruits globally. However, the apple industry faces challenges in monitoring and managing postharvest losses due to invasive pests during long-term storage. In this study, the effect of codling moth (CM) (Cydia pomonella [Linnaeus, 1758]), one of the most detrimental pests of apples, on the quality of the fruit was investigated under different storage conditions. Specifically, Gala apples were evaluated for their qualities such as firmness, pH, moisture content (MC), and soluble solids content (SSC). Near-infrared hyperspectral imaging (HSI) was implemented to build machine learning models for predicting the quality attributes of this apple during a 20-week storage using partial least squares regression (PLSR) and support vector regression (SVR) methods. Data were pre-processed using Savitzky–Golay smoothing filter and standard normal variate (SNV) followed by removing outliers by Monte Carlo sampling method. Functional analysis of variance (FANOVA) was used to interpret the variance in the spectra with respect to the infestation effect. FANOVA results showed that the effects of infestation on the near infrared (NIR) spectra were significant at p &lt; 0.05. Initial results showed that the quality prediction models for the apples during cold storage at three different temperatures (0 °C, 4 °C, and 10 °C) were very high with a maximum correlation coefficient of prediction (Rp) of 0.92 for SSC, 0.95 for firmness, 0.97 for pH, and 0.91 for MC. Furthermore, the competitive adaptive reweighted sampling (CARS) method was employed to extract effective wavelengths to develop multispectral models for fast real-time prediction of the quality characteristics of apples. Model analysis showed that the multispectral models had better performance than the corresponding full wavelengths HSI models. The results of this study can help in developing non-destructive monitoring and evaluation systems for apple quality under different storage conditions.

Analyzing the Quality Parameters of Apples by Spectroscopy from Vis/NIR to NIR Region: A Comprehensive Review.

Spectroscopic methods deliver a valuable non-destructive analytical tool that provides simultaneous qualitative and quantitative characterization of various samples. Apples belong to the world's most consumed crops and with the current challenges of climate change and human impacts on the environment, maintaining high-quality apple production has become critical. This review comprehensively analyzes the application of spectroscopy in near-infrared (NIR) and visible (Vis) regions, which not only show particular potential in evaluating the quality parameters of apples but also in optimizing their production and supply routines. This includes the assessment of the external and internal characteristics such as color, size, shape, surface defects, soluble solids content (SSC), total titratable acidity (TA), firmness, starch pattern index (SPI), total dry matter concentration (DM), and nutritional value. The review also summarizes various techniques and approaches used in Vis/NIR studies of apples, such as authenticity, origin, identification, adulteration, and quality control. Optical sensors and associated methods offer a wide suite of solutions readily addressing the main needs of the industry in practical routines as well, e.g., efficient sorting and grading of apples based on sweetness and other quality parameters, facilitating quality control throughout the production and supply chain. This review also evaluates ongoing development trends in the application of handheld and portable instruments operating in the Vis/NIR and NIR spectral regions for apple quality control. The use of these technologies can enhance apple crop quality, maintain competitiveness, and meet the demands of consumers, making them a crucial topic in the apple industry. The focal point of this review is placed on the literature published in the last five years, with the exceptions of seminal works that have played a critical role in shaping the field or representative studies that highlight the progress made in specific areas.

Effects of acidified apple juice before fermentation on ethyl carbamate and volatile components of apple distillate

In order to eliminate ethyl carbamate (EC) content in apple distillate, Fuji apple juice was acidified to pH 3.0 by sulfuric acid (ST), malic acid (MT), lactic acid (LT), or citric acid (CT). The acidified juice was inoculated with yeast, fermented at room temperature, and distilled by double distillation. Acid treatment by ST (3.23 μg/L), MT (3.20 μg/L), LT (2.93 μg/L), and CT (3.57 μg/L) significantly eliminated EC from apple distillate. Combined with the EC content and sensory evaluation, it was suggested that the high-quality apple distillate could be obtained with lower EC if apple juice was treated with ST or MT before fermentation.

Transcriptomic and metabolomic analysis reveals a protein module involved in preharvest apple peel browning.

Peel browning is a natural phenomenon that adversely affects the appearance of fruits. Research on the regulation of browning in apples (Malus × domestica Borkh.) has mainly focused on postharvest storage, while studies at the preharvest stage are relatively rare. Apple is an economically important horticultural crop prone to peel browning during growth, especially when the fruits are bagged (dark conditions). The present study's integrated transcriptomics and metabolomics analysis revealed that preharvest apple peel browning was primarily due to changes in phenolics and flavonoids. The detailed analysis identified MdLAC7's (laccase 7) role in the preharvest apple peel browning process. Transient injection, overexpression, and CRISPR/Cas9 knockout of the MdLAC7 gene in apple fruit and calli identified vallinic acid, anthocyanidin, tannic acid, sinapic acid, and catechinic acid as its catalytic substrates. In addition, yeast one-hybrid assay, electrophoretic mobility shift assay, luciferase reporter assay, and ChIP-PCR analysis revealed that MdWRKY31 binds to the promoter of MdLAC7 and positively regulates its activity to promote peel browning of bagged fruits (dark conditions). Interestingly, upon light exposure, the light-responsive transcription factor MdHY5 (ELONGATED HYPOCOTYL 5) bound to the promoter of MdWRKY31 and inhibited the gene's expression, thereby indirectly inhibiting the function of MdLAC7. Subsequent analysis showed that MdHY5 binds to the MdLAC7 promoter at the G-box1/2 site and directly inhibits its expression in vivo. Thus, the study revealed the MdLAC7-mediated mechanism regulating preharvest apple peel browning and demonstrated the role of light in inhibiting MdLAC7 activity and subsequently reducing peel browning. These results provide theoretical guidance for producing high-quality apple fruits.

Comparative assessment of environmental impacts, mitigation potentials, and economic benefits of rain-fed and irrigated apple production systems on China's Loess Plateau

Although the repaid development of China's apple industry heavily depends on excessive fertilizer-water-pesticide (FWP) inputs, little information is available that systematically evaluates environmental impacts, mitigation potential, and economical benefits of apple production systems in China. In this study, life cycle assessment (LCA) was conducted to elucidate environmental risks and mitigation potentials of rain-fed and irrigated apple production systems on China's Loess Plateau based on survey data from 847 farmers, and economic benefits were analyzed simultaneously. Results showed that irrigated orchards caused more severe environmental risks associated with energy depletion (ED), global warming potential (GWP) and acidification potential (AP) than those in rain-fed orchards, whereas an opposite was true for eutrophication potential (EP), human toxicity potential (HTP), aquatic toxicity potential (ATP) and soil toxicity potential (STP). ED and GWP occurred primarily in the agricultural material stage, while AP, EP, HTP, ATP, and STP occurred mostly in the orchard management stage. Optimized FWP management can markedly mitigate environmental impacts in both irrigated and rain-fed orchard systems. Synthetic fertilizer, because of production and field-associated emissions, was the greatest contributor to environmental impacts of an apple production system. An environmental pollution index (EPI) that integrated environmental categories was highest in conventional irrigated orchards (0.946), followed by conventional rainfed orchards (0.857), and optimized irrigated orchards (0.459), and the lowest EPI was in optimized rainfed orchards (0.389). Economic analysis revealed that the benefits of rainfed orchards were higher than those of irrigated orchards because of higher apple prices and lower labor costs. Optimized FWP management sharply decreased input costs, thereby substantially increasing net income in irrigated and rain-fed apple orchards. Overall, severe environmental risk and large mitigation potential co-exist in rain-fed and irrigated apple orchards on China's Loess Plateau. Integrated soil-crop-market management potentially exhibited considerable environmental and economic advantages, thereby efficiently developing high-quality apple production.

A Machine Learning Approach to Identify Optimal Cultivation Practices for Sustainable apple Production in Precision Agriculture in Morocco

Precision agriculture techniques have been increasingly adopted worldwide to optimize cultivation practices and achieve sustainable crop production. In this study, we developed a Machine Learning approach to identify optimal cultivation practices for sustainable apple production in precision agriculture in the Msemrir town Morocco. We collected a dataset of cultivation practices and apple yield and size data from 10 farms in the town and used correlation-based feature selection and three Machine Learning algorithms (Linear Regression, Decision Tree, and Random Forest) to develop predictive models. The results showed that irrigation, fertilization, and pruning are the most important cultivation practices for apple production in the region, and the Random Forest model performed the best in predicting apple yield and size based on the selected practices. The use of Machine Learning techniques can help farmers optimize cultivation practices and achieve sustainable apple production by reducing inputs such as water and fertilizer and minimizing environmental impact. Moreover, the use of precision agriculture techniques can help farmers meet consumer demand for sustainable and high-quality apple products.

Advance in application of rapid non-destructive testing technology in the detection of apple mold heart disease

Apples are rich in vitamins and dietary fiber, and are one of the essential fruits and vegetables in People’s Daily diet. China is a big apple consumer, and with the improvement of people’s pursuit of quality of life and the improvement of nutrition and health requirements, the demand for high-quality apples has increased year by year. Apple mold heart disease is one of the main diseases affecting apple quality, this disease can not be identified from the outside, so the detection is very difficult, and spectral technology, electromagnetic technology and other non-destructive testing technology has accurate, efficient, convenient, non-destructive advantages, can greatly reduce the difficulty of detection of mold heart disease. This paper mainly analyzed the application of non-destructive testing technology in the detection of apple mold heart disease, combined with the current rapid development of AI technology to discuss the future development direction of each technology in the field of apple mold heart disease rapid detection.

Выращивание саженцев яблони сибирской в Чурапчинском улусе РС(Я)

The article presents the first experimental data on the cultivation of the Siberian apple tree in the conditions of the alas of Yakutia on the example of the school district of the MBOU "Ozhulunskaya secondary school". Long-term results of research (2017-2022) confirmed the plasticity of this crop in terms of the biological trait of winter hardiness. So, during the cold winter of 2021, the sum of the minimum temperatures is minus 5554.7 ° С. In January, the minimum temperature reached minus 54 °C. The provision of moisture during the growing season was at the hydrothermal coefficient (hereinafter HTC) an average of 0.62 over 5 years. In the course of the research, the landing site was chosen open, well warmed by the sun. The soil scheme of the planting pit for the apple tree was established to a depth of 50 cm. The growth and development of the Siberian apple tree was recorded. The main phenological phases of apple tree development under alas conditions against the background without irrigation were determined. Accounting for the height of the Siberian apple tree showed that the maximum growth of the main trunk falls on the age of 5, which is 53 cm of growth. At the same time, the height of the apple tree reached 123 cm. By the age of 6, the growth reaches 37 cm and the height of the apple tree is 169 cm. It was planned to establish a fruit and berry garden in the alas permafrost zone. To increase the durability of a tree, its winter hardiness should be increased. An important factor is agricultural technology, but the basis of longevity is the right choice of the location of the apple tree itself, then the rootstock, the base of the tree. The winter hardiness of the Siberian apple tree in the conditions of the alas of the Churapchinsky district showed a satisfactory assessment after the first overwintering of 2 seedlings, one remained with excellent winter hardiness in the next 4 years of research. In the future, the selected seedling without shelter can serve as forms of adapted material for landscaping gardens and parks, obtaining high-quality apple fruits. Keywords: SEEDLINGS, SIBERIAN APPLE TREE, WINTER HARDINESS, ALAS, GROWTH AND DEVELOPMENT OF SIBERIAN APPLE TREE

Real-Time Grading of Defect Apples Using Semantic Segmentation Combination with a Pruned YOLO V4 Network.

At present, the apple grading system usually conveys apples by a belt or rollers. This usually leads to low hardness or expensive fruits being bruised, resulting in economic losses. In order to realize real-time detection and classification of high-quality apples, separate fruit trays were designed to convey apples and used to prevent apples from being bruised during image acquisition. A semantic segmentation method based on the BiSeNet V2 deep learning network was proposed to segment the defective parts of defective apples. BiSeNet V2 for apple defect detection obtained a slightly better result in MPA with a value of 99.66%, which was 0.14 and 0.19 percentage points higher than DAnet and Unet, respectively. A model pruning method was used to optimize the structure of the YOLO V4 network. The detection accuracy of defect regions in apple images was further improved by the pruned YOLO V4 network. Then, a surface mapping method between the defect area in apple images and the actual defect area was proposed to accurately calculate the defect area. Finally, apples on separate fruit trays were sorted according to the number and area of defects in the apple images. The experimental results showed that the average accuracy of apple classification was 92.42%, and the F1 score was 94.31. In commercial separate fruit tray grading and sorting machines, it has great application potential.

Water, energy, and carbon integrated footprint analysis from the environmental-economic perspective for apple production in China

The ecosystem currently suffers from water-, energy-, and food-scarcity as well as climate change caused by population growth and industrialization progress. To analyze these four challenges, the integrated consideration from environmental and economic perspectives are highly needed. This study constructed an environmental–economic coupled water, energy, and carbon integrated footprint (WECF) assessment method to evaluate apple production in China. The overall environmental WECF of apple production in 2019 on human health, ecosystem quality, and resource depletion categories were 3.0 × 104 disability adjusted life years, 323 annual species loss, and $ 5.6 × 109 respectively. The overall cost of apple production in China in 2019 was $ 1.6 × 1010, including 95.3% of internal costs and 4.7% of external costs. Additionally, ∼ $ 5.6 × 109 of net profits in China were observed. The environmental WECF was dominated by fertilizer production process and irrigation, whereas the internal costs of labor and fertilizer and external costs of human health were the major contributors to economic impacts. In addition, approximately 3.8 × 106 disability adjusted life years in health life were avoided due to the nutrition intake from apples in 2019. Results suggest that the current apple planting layout in China for high-quality apple production is suitable for an environmental and economic win–win situation despite the existing water scarcity situation. However, compared with Europe, the global standing of China's apple production in terms of WECF is still at a low point because of the backward irrigation facilities and technologies, high fertilizer consumption rate, and low apple production yield per unit area. Therefore, adopting suitable water-saving irrigation technologies following local conditions, exploring driven forces on the water- and fertilizer-saving technologies, and increasing apple yield per area is highly recommended.

Apple appearance quality classification method based on double branch feature fusion network

This paper carried out a classification study on the quality of different types of apples. In order to achieve a high-precision classification of high-quality apples in various dimensions, shorten the classification time, improve efficiency, and make it feasible for practical applications. This paper proposes an automatic recognition and classification model OB-Net (for apple appearance quality) based on a dual-branch structure. The model consists of two branches, an O branch and a B branch. The O branch extracts the shape and contour features of the apple surface defect by decomposing the feature map into high and low frequencies. The B branch extracts the shape size and texture characteristics of the apple surface defect by fusing channel attention and spatial attention mechanisms; this is done to further increase the feature distance between different types of defects. Experimental results show that the classification accuracy rates of rot, insect bites, russeting, scratches, and intact apples are 95.65%, 98.17%, 94.62%, 92.02% and 97.67%, respectively; the overall classification and recognition accuracy rate reaches 95.64%. Finally, the three aspects of the feature map, heat map and category probability statistics map extracted from the OB-Net network model prove the validity of the network model in the classification of apple appearance quality.

Effect of Sustainable Preharvest and Postharvest Techniques on Quality and Storability of High-Acidity ‘Reinette du Canada’ Apple

Consumers are more disposed towards paying price premiums for sustainable food products. This fact is especially important for products with a PDO (Protected Designation of Origin) label, such as the high-acidity apple cultivar ‘Reinette du Canada’. However, ‘Reinette du Canada’ apple fruit is affected by two of the main post-harvest disorders in apple cultivars, bitter pit and senescent breakdown. As a means to achieve sustainable production of this high-quality apple cultivar, the effect of a sustainable preharvest technique, summer pruning, in combination with a zero-residue postharvest treatment allowed in organic farming on calcium-related disorders and quality in global terms in this PDO-labelled apple cultivar was assessed during storage. The combination of the two sustainable practices was an effective tool in diminishing senescent breakdown from 43% to 17% and to decrease bitter pit incidence by up to 21% (from 36% to 15%) throughout storage, especially in fruit with high susceptibility to this disorder during storage. Moreover, the overall acceptability was kept high (values of more than 3 on a 5-point scale) when applying this environment-friendly sustainable horticulture practice, which will not only reduce the synthetic pesticide input in the apple agroecosystem, but also contribute to producing fruit with zero residues.