Apple Cultivation Research Articles

Development of a 3D point cloud reconstruction-based apple canopy liquid sedimentation model

China leads the world in apple production, contributing to over half of the global total. Annually, extensive pesticide use is employed in apple cultivation, but the uncertain quantities of pesticide deposition and indiscriminate application have resulted in significant pesticide loss and residue. This poses a considerable potential risk to human health. This paper focuses on ground-based plant protection and stratifies the canopy horizontally, using 3D point cloud reconstruction technology and tree deposition experiments to explore the relationship between canopy leaf area index and pesticide deposition. By calculating the droplet penetration coefficient based on the amount of solution deposited at various canopy layers, a functional model linking leaf area index and droplet penetration coefficient has been established, with a correlation coefficient (R2) of 0.92. Based on this model, and by integrating the canopy volume with the amount of solution deposited on the outermost layer of the canopy, the total solution deposition on the entire tree can be estimated. According to the deposition model, there is a negative correlation between the amount of solution deposited on the canopy and the leaf area index of the canopy. Moreover, the experiments have shown that when the spray vehicle travels at a speed of 1.5 m/s, the maximum amount of solution is deposited while still ensuring an effective deposition rate. The establishment of the deposition estimation model allows for the visualization of canopy solution deposition and can guide fruit farmers in determining the appropriate frequency of spraying based on the severity of pest and disease infestations.

Evaluation of Morphological Characteristics in Some Apple Varieties (Malus Pumila Mill.) from Northeastern Algeria

Abstract The current investigation is centered on the characterization of specific apple cultivars in the Garza region, within the Teniet El Abed municipality, situated 55 km east of Batna (NE-Algeria). Utilizing descriptors outlined by UPOV 2015 pertaining to apples, the study focuses on morphological parameters of leaves, fruits, and terminal shoots across three varieties: Golden Delicious, Royal Gala, and Starkrimson. Additionally, soil analysis was conducted to ascertain its suitability for apple cultivation. The examination revealed limited morphological diversity among the investigated apple cultivars, with some descriptors, particularly those related to fruit traits, showing insignificant differences between cultivar types. Overall, the studied varieties - Golden Delicious, Royal Gala, and Starkrimson - exhibit distinct physiological and morphological characteristics. Variations in size, shape, skin color, flesh attributes, as well as sugar and acid content, contribute to the uniqueness of each variety. Whether one prefers sweet or tart apples, or favors larger or smaller fruits, there exists an apple variety to cater to individual tastes. Our findings complement molecular analyses and underscore the need for further exploration of apple germplasm, alongside sustained conservation efforts.

Optimizing deficit drip irrigation to improve yield,quality, and water productivity of apple in Loess Plateau of China

ContextDeficit drip irrigation is an advanced agricultural technology widely promoted and applied around the world to maintain/increase yield and quality while simultaneously minimizing water consumption. However, there is still a lack of comprehensive research on the effects of deficit drip irrigation at different stages on apple yield, water productivity, and quality. ObjectiveThe aim was to investigate the effects of deficit drip irrigation treatments (DDITs) on apple yield, quality, and water productivity (WP), and optimize the deficit drip irrigation strategy for apples in the Loess Plateau of China. Methodsa two-year field experiment was conducted with 17 irrigation treatments, including a control treatment (CK, full irrigation (FI)) and four DDITs (D15%, D30%, D45%, D60%) during the bud burst to leafing stage (I), flowering to fruit set stage (II), fruit expansion stage (III), and fruit maturation stage (IV). The optimal irrigation management was determined using the fuzzy Borda combined model, which was based on four different single evaluation models of the TOPSIS method, principal component analysis (PCA), grey correlation analysis (GCA), and membership function analysis (MFA). ResultsThe DDITs at stage IV decreased midday leaf water potential (Ψs) by 2.57–20.00% compared with CK, and the difference of Ψs between IV-D30%, IV-D45%, IV-D60%, and CK were significant in two years (P<0.05). DDITs at stages I, II, and IV improved fruit weight (FW), fruit shape index (FSI), and fruit firmness (FN), but did not significantly affect fruit water content (FWC). The DDITs at stages III and IV significantly enhanced total soluble solids (TSS), soluble sugars (SS), and vitamin C (Vc) in 2021 and 2022, but a notable decrease in titratable acidity (TA) was observed. ConclusionsDDITs at stage IV exhibited the highest comprehensive benefit of apple, followed by DDITs at stages I and II, and DDITs at stage III had the lowest values. The DDITs of D15%, D30%, CK, and D15% at stages I, II, III, and IV were identified as the optimal irrigation strategy to improve apple yield, quality, and WP. ImplicationsOur findings can guide the development of appropriate irrigation strategies for apple cultivation in Loess Plateau of China, promoting efficient and sustainable apple production.

Severe nitrogen leaching and marked decline of nitrogen cycle-related genes during the cultivation of apple orchard on barren mountain

Limited available lands have led to the widespread practice of establishing orchards on barren mountains to expand apple cultivation in China. However, improper nitrogen (N) management strategies in intensive orchards escalate costs and also contribute to environmental contamination. A long-term field experiment was conducted in a representative apple-producing area in Shandong Province, China, to assess the environmental risks associated with newly established orchards. This research utilized lysimeters and soil metagenomic sequencing to investigate N leaching loss and the functional microbial profiles associated with the N cycle during apple cultivation on barren mountains. Five treatments were implemented: no inorganic N fertilizer, traditional farmer's fertilization, drip irrigation with a water-soluble fertilizer, resin-coated urea, and grass interplanting. Among treatments involving inorganic N, the total N leaching rate ranged from 16.5% to 30.7% of the total N fertilizer input. Notably, in treatments with equivalent N fertilizer applications, the water-soluble fertilizer treatment exhibited the highest N leaching loss rate -(20.2–29.0%), while the grass interplanting and resin-coated urea treatments showed significantly lower rates of N leaching loss (17.0–24.9% and 15.2–24.5%, respectively). The abundance of N cycle-related genes experienced a marked decline (17.1–18.8%) during the cultivation of orchards on barren mountains. The water-soluble fertilizer treatment displayed the highest potential for nitrification, contributing to elevated N leaching. Both resin-coated urea and traditional farmer's fertilization treatments exhibited the highest abundance of genes associated with N2O emission risk to the atmosphere. However, the grass interplanting treatment, while effectively reducing N leaching, also triggered the most pronounced soil acidification. Spearman correlation analysis revealed that the decline in pH, coupled with an increase in soil NO3--N concentration and electrical conductivity (EC), were the primary factors contributing to the reduction in the abundance of key N cycle functions. In summary, excessive use of inorganic N fertilizer in orchard environments led to increased N leaching, altered soil physicochemical properties, and significant impacts on N cycle-related genes. The elevated ionic strength in soils might be responsible for both the high N leaching loss and the decrease in N cycle function abundance. In intensive orchard cultivation, each N fertilization strategy mentioned above comes with its environmental drawbacks. Further investigation is warranted to achieve a balance between productivity and environmental protection.

Functional identification of CCR1 gene in apple (Malus halliana) demonstrates that it enhances saline-alkali stress tolerance

BackgroundLignin is a complex aromatic polymer that plays an important biological role in maintaining plant structure and defending plants against biotic and abiotic stresses. Cinnamoyl-CoA reductase (CCR) is a key enzyme involved in the lignin synthesis-specific pathway and regulates lignin biosynthesis and accumulation.MethodsBased on transcriptome data, MhCCR1, which was significantly induced by saline-alkali stress, was cloned from Malus halliana. The physicochemical properties, evolutionary relationships and cis-acting elements were analyzed. We obtained transgenic materials by heterologous transformation of MhCCR1 into Arabidopsis thaliana and tobacco, as well as homologous transformation into apple callus, and characterized their saline-alkali stress resistance by a series of physiological and biochemical experiments. And yeast two-hybridization technique was applied to screen and validate the interacting proteins.ResultsWe found that overexpression of MhCCR1 enhanced the tolerance of A. thaliana, tobacco and apple calli under saline-alkali stress, and caused a variety of physiological and biochemical changes. As compared to the wild type, the transgenic plants showed better growth, higher lignin, chlorophyll and proline contents, lower conductivity and MDA content, and significant increase in antioxidant enzyme activities (SOD, POD, CAT) in the transgenic lines under stress condition. In addition, expression of saline-alkali stress-related genes in overexpressed A. thaliana were also higher than in WT, including the antioxidant genes, the Na+ transporter genes, and the H+-ATPase genes, while expression of the K+ transporter genes displayed opposite changes. Meanwhile, the expression levels of genes related to lignin synthesis, AtPAL1, AtCOMT, AtC4H, At4CL1, and AtCCOAOMT, were also significantly up-regulated. At last, the Y2H experiment confirmed the interaction between MhCCR1 and MhMYB4, MhMYB1R1, MhHXK, and MhbZIP23 proteins.ConclusionsThese results suggest that MhCCR1 may play a positive regulatory role in saline-alkali tolerance of transgenic lines by regulating the lignin content, osmoregulatory substances, chlorophyll content, antioxidant enzyme activities, and genes related to saline-alkali stress, thus providing excellent resistance genes for the stress-responsive regulatory network of apples, and providing a theoretical basis for the cultivation of saline and alkali-resistant apple varieties.Graphical

Apple Growth and Yield in Replant Soils Supplemented by Organic Soil Additives

Repeated apple cultivation in the same area leads to apple replant disease (ARD), which can probably be reduced by the use of organic supplements and selected rootstock/variety combinations. Soils at two conventionally and one organically farmed site in north-eastern Germany were tested for ARD in pot trials. In subsequent field trials, the effects of champost, microbially carbonised compost, and coniferous wood shavings piled up like a dam (‘Müncheberger Damm’ (M)-dam) and of rootstock/variety combinations were tested. On the organic site, only leonardite and champost were tested. The pot trials indicated for all sites that the soil is affected by ARD. After five years, the growth increase in trunks in the M-dam was 20–40% higher than in controls and other treatments, depending on the site. On one site, the yield over four years was a 15.7% increase for M-dam and also for champost compared to controls, on the other site, it was 11.7% and 3.0%, respectively. The M.9 rootstock with the Gala variety had a higher, but insignificant, yield compared to G.11/Gala by 6.7 or 2.6%, depending on the site. No difference in trunk growth or yield with Topaz was observed at the organic farmed site. Further research on M-dam and champost is supported, as both are promising in terms of yield.

The Economic Potential of Agrivoltaic Systems in Apple Cultivation—A Hungarian Case Study

Agrivoltaic systems (AVS) allow the simultaneous use of land—as a limited resource—for crop production and electricity generation. This paper introduces the development prospects of AVS in Hungary with insights into international trends. The most important part is a complex economic analysis and a unit cost analysis of a 38 MWp capacity AVS, considering the most typical basic data in electricity and apple production. The applied risk analysis is based on a Monte Carlo simulation, the distribution function, and probabilities. To introduce the economic facet of the competitiveness of AVS, a comparative analysis was carried out between AVS, ground-mounted photovoltaic (GM-PV) systems, and conventional apple production systems (ConAPS). In the most probable scenario, the AVS was financially attractive (NPV = 70 million EUR under 30 years). Our correlation analysis shows that feed-in tariff (FIT) price and the role of financing are considered the dominant economic factors. A favorable FIT price enhances the profitability of AVS; however, it makes GM-PV systems more profitable compared to AVS, so it negatively affects the competitiveness of AVS systems. AVS operations result in a more balanced unit cost of apples and of electricity compared to the independent operation of GM-PV systems and of ConAPS; in addition, it allows for land saving and more intensive land use.

Expansion of apple cultivation increases the abundance of codling moth (Cydia pomonella) in agricultural landscapes of China.

Agricultural land-use change is an important driver of pest population dynamics, and can alter source-sink dynamics and the concentration-dilution effects of the landscape. Understanding the effects of land use on pests at both landscape and regional levels is essential for the development of sustainable pest management strategies given the large changes occurring in cropping systems in China. At the landscape level, we investigated the impacts of landscape composition and edge density on pheromone trap catch of codling moth (Cydia pomonella) in apple orchards, in Aksu, Xinjiang, China. At the regional scale, we conducted a meta-analysis using data from studies performed across the Aksu area in recent decades, to assess the relationship between trends in codling moth abundance and the area of apple cultivation. Both extensive planting of apple and large areas of annual crops in the landscape increased the abundance of codling moth, whereas the presence of secondary host plants (peach, pear, walnut, plum, and apricot) had a negative effect. Seminatural habitats and landscape edge density did not significantly affect codling moth abundance. The responses of different generations of codling moth to landscape factors were varied. At the regional level, codling moth occurrence was positively correlated with the expansion of apple production areas. Expansion of apple cultivation increases the abundance of codling moth in agricultural landscapes. We recommend decreasing the area devoted to monocultures of apple when designing agricultural landscapes and increasing plantings of secondary host crops to dilute and reduce the abundance of codling moth. © 2024 Society of Chemical Industry.

Exploration of Pathogenic Microbes and Antagonistic Agents in Apple Production Centers in Malang Regency

The apple farming group is one of the built of Department of Plant Pests and Diseases, Agricultural Faculty, Brawijaya University. In 2019, this departmen received a request from apple farmers in Madiredo Village, Pujon District to held an assistance programs of apple cultivation and environmentally pest control. This is related with the increasing of fruit rot and other diseases which is caused a decrease of apple production especially in Malang Regency. In general, apple farmers still rely on disease control using chemical fungicides which can have a negative impact on the environment and create resistance to pathogenic fungi. Therefore, this research was carried out to explore and study the potential of biological agents in apple production centers in Malang Regency, specifically in Poncokusumo, Pujon, and Batu District on conventional fields and mixed fields. This research was held observationally through fields surveys and farmer interviews, took soil samples and disease samples then then isolating, identifying and testing for antagonism at laboratory. Based on interviews and observation of symptomology, two dominant diseases were found, namely fruit rot disease (Gloeosporium sp.) and marsonina leaf spot disease (Marssonina coronaria). The results of exploration of the rhizospheric apple plants obtained isolates on conventional fields in Kec. Pujon has the highest abundance of fungal colonies compared to other regions. Based on the results of the antagonism test for pathogenic fungi and biological agents, it was found that the isolate codes KH.C, KK.A, JK.B, JK.J, and BK.B had the highest percentage of inhibition or the most effective in controlling the pathogen Gloeosporium sp. So in the next, the species can be identified molecularly.

A Comprehensive Farm Efficiency Analysis of Apple Growers in Newley Merged District South Waziristan

In the apple-producing land of South Waziristan’s three tehsils, Wana, Bermal, and Tiarza, this research paper is designed to analyze farmers' efficiencies, e.g., production, allocative and technical dimensions. Through a Data Envelopment Analysis (DEA) framework, the study evaluates the performance trajectories of 304 apple growers. A multistage sampling technique was used for the farmer’s interview. To the researcher’s knowledge, there is no detailed efficiency analysis of South Waziristan’s apple growers in existing literature, so there is a need to investigate the factors affecting efficiencies in the targeted area. The researcher is therefore encouraged to conduct a study of the farm efficiency of apple growers in South Waziristan. Apple growers' efficiencies were categorized as technical, allocative, and economic efficiency using the DEA approach. Results of the study show that there were tremendous inefficiencies of apple growers, which need to be reduced. This study sheds light on optimal resource allocation, productivity dynamics, and efficiency frontiers within apple cultivation in South Waziristan. The research offers an understanding of agricultural practices, resource utilization patterns, and efficiency benchmarks. The empirical insights derived from this comprehensive analysis facilitate informed decision-making among farmers and provide policymakers, agricultural stakeholders, and development practitioners with actionable recommendations to enhance agricultural productivity, sustainability, and socio-economic well-being in the region. Through empirical evidence and contextual relevance, this paper contributes significantly to the evolving discourse on agricultural efficiency analysis and underscores the imperative of tailored interventions for optimizing apple cultivation practices in South Waziristan.

An overview of the red-fleshed apple: History and its importance for horticulturists, gardeners, nurserymen, and consumers

The present review summarizes the information on the botany, breeding, genetic features, cultivation, and nutraceutical values of red-fleshed apples. Malus sieversii var. niedzwetzkyana or Niedzwetzky’s apple became widely known after the publication of Georg Dieck in the last XIX century. It is characterized by anthocyanin coloration of all organs. Another source of red flesh is the ancient variety ‘Surprise’, which differs from the Niedzwetzky’s apple by a mutation in another gene. These two mutated genes, MYB10 and MYB110a, are located on chromosomes 9 and 17, respectively. Their expression correlated with the anthocyanin accumulation. In type 1 red-fleshed apples, which belong to the Niedzwetzky’s apple progeny, the transcription factor MYB10 confers extensive anthocyanin accumulation in fruit flesh and skin, flowers, leaves, and stems. In type 2 red-fleshed apples, the ‘Surprise’ progeny, only the flesh is red, determined by the transcription factor MYB110а. A new combination Malus domestica f. niedzwetzkyana comb. nov. has been proposed for orchard apples, originated from Niedzwetzky’s apple. The apple cultivars which are progeny of Niedzwetzky’s apple and ‘Surprise’ apple can be placed to Malus Niedzwetzkyana Group and Malus Surprise Group, respectively. All red-fleshed cultivars of orchard apple can be grouped together into Malus domestica Red Flesh Group. Many dozens of new ornamental apple trees have been developed for of European and North American conditions, including the most famous red-flowered centennial apple varieties such ‘Aldenhamensis’, ‘Lemoinei’, ‘Makamik’, and ‘Oekonomierat Echtermeyer’. Rootstocks ‘MB’, ‘PB9’, ‘54-118’, ‘62-396’ and others have become popular in nurseries for the propagation of dwarf and semi-dwarf apple trees thanks to their red leaves, which are useful when removing scion shoots from budded plants. In the F3-F4 and next generation, the new high-quality red-fleshed cultivars have been developed by crossing both Niedzwetzky’s apple and ‘Surprise’ apple with the best orchard apple varieties. Marker-assisted breeding shows great promise for accelerating the development of new red-fleshed cultivars with outstanding traits. The use of the Redlove®, Red Moon®, Kissabel®, and Lucy™ apples brands will ensure the red-fleshed apples’ best path to the consumer as well as the fruit quality and production volume of these novelties. Increasing the consumption of red-fleshed apples is essential for a healthy diet.

Development Prospects of Apple Farming in India

The cultivation of apples in India has observed significant growth and transformation over the years, becoming a crucial component of the country's horticultural landscape. This review provides a comprehensive analysis of the current state of apple production in India, highlighting key factors influencing its cultivation, challenges faced by growers, and the economic impact on the agricultural sector. The review begins by exploring the historical evolution of apple cultivation in India, tracing its origins and the introduction of different apple varieties. It examines the geographical distribution of apple orchards across the country, emphasizing the diverse agro-climatic zones that contribute to the cultivation of this temperate fruit.

An apple a day keeps the doctor away? - a review of health benefits of apples

Introduction and purpose: Apples are a widely consumed fruit globally and are known to be a great source of nutrition. Studies have shown that apples contain high levels of antioxidants, dietary fiber, and vitamins that contribute to numerous health benefits. This paper aims to provide a comprehensive review of the impact of apples on human health. State of knowledge: The paper reviews the current literature on the health benefits of apples, focusing on their impact on various health conditions such as cancer, cardiovascular diseases, diabetes, and obesity. Additionally, it examines the role of apples in improving intestinal, immune, and cognitive function. The paper also discusses the potential mechanisms by which apples exert their health benefits, such as high levels of flavonoids, polyphenols, and dietary fiber. Summary: In conclusion, the vast body of evidence reviewed in this paper supports the notion that consuming apples regularly can contribute to better health outcomes. They may help reduce the risk of chronic diseases, such as cancer, cardiovascular diseases, and diabetes, as well as promote healthy gut microbiota and immune function. Despite the controversy surrounding the use of pesticides in apple cultivation, the benefits of consuming apples outweigh the risks. Therefore, it is highly recommended to include apples as part of a balanced and nutritious diet to promote optimal health and wellbeing. As the saying goes, "An apple a day keeps the doctor away".

Unlocking heirloom diversity: a pathway to bridging global challenges in modern apple cultivation

Reports indicate that climate changes will result in the extinction of a significant percentage of plant species even though many of these species contributed to crucial genetic traits that led to the development of domestic crops. In the past, the diversified range of plant species, varieties, and agricultural practices allowed agriculture production and local food systems to tolerate moderate climate variability. Today, industrial farming relies on very limited genetic diversity for commercial production. Narrowing the genetic base leads to higher susceptibility to environmental changes and diseases.Heirloom cultivars survived climate variations and extreme conditions but were abandoned in favor of a handful of commercial cultivars that dominate the food industry and fit the standards of the global food system. From a climate change perspective, it would be important to conserve heirloom cultivars to preserve biodiversity and make greater genetic diversity available to farming, which will lead to resilience and adaptation.

Identification of S-RNase genotype and analysis of its origin and evolutionary patterns in Malus plants

Identification of the S genotype of Malus plants will greatly promote the discovery of new genes, the cultivation and production of apple, the breeding of new varieties, and the origin and evolution of self-incompatibility in Malus plants. In this experiment, 88 Malus germplasm resources, such as Aihuahong, Xishuhaitang, and Reguanzi, were used as materials. Seven gene-specific primer combinations were used in the genotype identification. PCR amplification using leaf DNA produced a single S-RNase gene fragment in all materials. The results revealed that 70 of the identified materials obtained a complete S-RNase genotype, while only one S-RNase gene was found in 18 of them. Through homology comparison and analysis, 13 S-RNase genotypes were obtained: S1S2 (Aihuahong, etc.), S1S28 (Xixian Haitang, etc.), S1S51 (Hebei Pingdinghaitang), S1S3 (Xiangyangcun Daguo, etc.), S2S3 (Zhaiyehaitang, etc.), S3S51 (Xishan 1), S3S28 (Huangselihaerde, etc.), S2S28 (Honghaitang, etc.), S4S28 (Bo 11), S7S28 (Jiuquan Shaguo), S10Se (Dongchengguan 13), S10S21 (Dongxiangjiao) and SeS51 (Xiongyue Haitang). Simultaneously, the frequency of the S gene in the tested materials was analyzed. The findings revealed that different S genes had varying frequencies in Malus resources, as well as varying frequencies between intraspecific and interspecific. S3 had the highest frequency of 68.18%, followed by S1 (42.04%). In addition, the phylogenetic tree and origin evolution analysis revealed that the S gene differentiation was completed prior to the formation of various apple species, that cultivated species also evolved new S genes, and that the S50 gene is the oldest S allele in Malus plants. The S1, S29, and S33 genes in apple-cultivated species, on the other hand, may have originated in M. sieversii, M. hupehensis, and M. kansuensis, respectively. In addition to M. sieversii, M. kansuensis and M. sikkimensis may have also played a role in the origin and evolution of some Chinese apples.

Characterization of Bacillus amyloliquefaciens BA-4 and its biocontrol potential against Fusarium-related apple replant disease.

Apple replant disease (ARD), caused by Fusarium pathogens, is a formidable threat to the renewal of apple varieties in China, necessitating the development of effective and sustainable control strategies. In this study, the bacterial strain BA-4 was isolated from the rhizosphere soil of healthy apple trees in a replanted orchard, demonstrating a broad-spectrum antifungal activity against five crucial apple fungal pathogens. Based on its morphology, physiological and biochemical traits, utilization of carbon sources, and Gram stain, strain BA-4 was tentatively identified as Bacillus amyloliquefaciens. Phylogenetic analysis using 16S rDNA and gyrB genes conclusively identified BA-4 as B. amyloliquefaciens. In-depth investigations into B. amyloliquefaciens BA-4 revealed that the strain possesses the capacity to could secrete cell wall degrading enzymes (protease and cellulase), produce molecules analogous to indole-3-acetic acid (IAA) and siderophores, and solubilize phosphorus and potassium. The diverse attributes observed in B. amyloliquefaciens BA-4 underscore its potential as a versatile microorganism with multifaceted benefits for both plant well-being and soil fertility. The extracellular metabolites produced by BA-4 displayed a robust inhibitory effect on Fusarium hyphal growth and spore germination, inducing irregular swelling, atrophy, and abnormal branching of fungal hyphae. In greenhouse experiments, BA-4 markedly reduced the disease index of Fusarium-related ARD, exhibiting protective and therapeutic efficiencies exceeding 80% and 50%, respectively. Moreover, BA-4 demonstrated plant-promoting abilities on both bean and Malus robusta Rehd. (MR) seedlings, leading to increased plant height and primary root length. Field experiments further validated the biocontrol effectiveness of BA-4, demonstrating its ability to mitigate ARD symptoms in MR seedlings with a notable 33.34% reduction in mortality rate and improved biomass. Additionally, BA-4 demonstrates robust and stable colonization capabilities in apple rhizosphere soil, particularly within the 10-20 cm soil layer, which indicates that it has long-term effectiveness potential in field conditions. Overall, B. amyloliquefaciens BA-4 emerges as a promising biocontrol agent with broad-spectrum antagonistic capabilities, positive effects on plant growth, and strong colonization abilities for the sustainable management of ARD in apple cultivation.

夹持-拉断式苹果采摘机器人设计与实验

For the standardized apple orchards in China, which are mainly dwarfed and densely planted, firstly, according to the spatial distribution characteristics of fruits within the tree canopy, a clamping-pull-off apple picking robot was developed by analyzing the parameters of apple cultivation and picking methods, in order to replace the manual harvesting operation. Then, the D-H method was used to establish the kinematic Equations of the apple-picking robot, the forward and inverse kinematic calculations were carried out, and the Monte Carlo method was used to analyze the workspace of the robot. Through the robot picking task planning and the simulation of the trajectory of the robotic arm, the scheme of the robot's picking strategy was given, and MATLAB software was applied to simulate the motion trajectory as well as to verify the feasibility of the trajectory planning scheme and the picking strategy. Finally, an apple-picking test bed was set up, the corresponding picking control system program was designed, and 45 apples were selected for picking tests. The results showed that during the robot's picking process, the average time for picking each fruit was 7.59 seconds, the fruit recognition success rate was 86.67%, and the picking damage rate was 5.13%.

Efficiency analysis of apple and grape producers

In recent years, the world has experienced unforeseen events that have greatly affected the population and the economy. It is important to analyze how the agricultural sector has responded to these events and assess its effectiveness as its performance is always vital, in peaceful periods but even more during the highly uncertain period we have been facing these last years. In Hungary, the most significant fruit production is the cultivation of apples. The specificity of apples, compared to other fruits, is that they can be stored and consumed in their original form all year round. Over the years, however, the final use of apple production has changed, as today most of it is intended for industrial processing in Hungary. The grapes are also consumed as a fruit during a short period of the year. However, a minimal proportion of the grapes are consumed freshly, and most of it is used instead to make the products of the winery. Overall, the country's apple and grape fields have been steadily decreasing over the years. The yield is fluctuating for both apples and grapes, however, the grape yield has been steadily decreasing over the past 5 years. How do these two sectors operate in 2021, one year after the start of Covid-19? This research aims to provide a comprehensive picture of the apple and grape growing sector and then to specifically analyze the financial efficiency of Hungarian small and medium-sized enterprises operating in those two sectors in 2021.

Estimation of Apple Leaf Nitrogen Concentration Using Hyperspectral Imaging-Based Wavelength Selection and Machine Learning

In apple cultivation, the total nitrogen content is an important indicator of plant growth, fruit quality, and yield. Timely monitoring of growth becomes imperative, since an imbalance, either in deficiency or excess nitrogen, can result in physiological disorders, adversely impacting both the quantity and quality of fruit. Leaf nitrogen content can be determined using simple chlorophyll meters or destructive testing; however, these methods are time-consuming. However, by employing spectral imaging technology, it is possible to swiftly predict leaf nitrogen content. This study estimated the total nitrogen content in apple trees via hyperspectral imaging and machine learning-based regression analysis (partial least-squares regression (PLSR), support vector regression (SVR), and eXtreme gradient boosting regression (XGBoost). Additionally, to reduce computational costs and improve reproducibility, spectral binning was divided into three stages (4, 8, and 16 bins), and models were compared with a 2-binning estimation model. The analysis focused on green, red, red edge, and near-infrared (NIR) spectra, with 5–10 selected wavelengths, and the SVR-based prediction model showed a similar or greater performance to that of the full spectrum. At 4- and 8-binning, the selected wavelengths were similar to those at 2-binning, maintaining similar prediction model performance. However, at 16 bp, the performance of the prediction model decreased owing to spectral data loss, leading to a significant reduction in wavelengths for nitrogen content estimation. These results can support informed nitrogen fertilization decisions, enabling precise, real-time monitoring of nitrogen content for enhanced plant growth, fruit quality, and yield in apple trees. Additionally, the selected wavelengths can be considered in the development of new types of multispectral sensors.

A System for Identifying Deficiency Elements in Apple Leaf Disease Based on Deep Learning

Background: Plant diseases and pests were natural disasters that seriously threaten agricultural production. Leaf diseases posed a significant threat to the overall productivity and quality of apple orchards. Currently, the diagnosis of plant diseases in apple orchards mainly relied on manual labor, which was both time-consuming and costly. It took a considerable amount of time to train an expert capable of accurately identifying apple diseases and pests, and different crop diseases vary. However, with the use of AI technology, training could be completed in just a few hours to a day, transforming computers into experts in disease and pest identification. Although China became a major apple cultivation nation, the development data from 2021 revealed that traditional advantageous production areas were undergoing dynamic adjustments due to optimization of industrial structure, leading to a decrease in cultivated land. Conversely, the demand for apples in the Chinese market continued to rise, even as the country's population structure gradually trended towards an aging population. This situation underscored the urgent need to replace the laborious and high-cost task of identifying apple foliar diseases in the cultivation process with intelligent agricultural technological solutions. Taking into account the aforementioned factors of the natural environment and socio-cultural considerations and addressing the issue of reduced apple yields due to the high impact of foliar diseases, we initiated study on disease prevention and control during the cultivation process. Methods: To overcome the objective impact of environmental factors, the system extracted images and performed operations such as enhancement and segmentation. Subsequently, a convolutional neural network was employed to process the enhanced images, extracting features such as color, shape, and texture of apple foliar lesions, which were then summarized into histograms using mathematical methods. These histograms served as the primary reference for distinguishing various diseases. Python was chosen as the programming language for the system, and the recognition system was operated by integrating frontend technologies, backend database design, and other relevant techniques. Results: Based on a substantial number of experimental results, the apple leaf disease and nutrient deficiency recognition system could accurately and with extremely high precision identifying major diseases commonly occurring in apple plants, including apple scab, leaf spot disease, rust disease, gray mold disease, and brown spot disease. Moreover, the system was capable of proposing remedies tailored to the specific pain points of each disease. It not only detected apple leaf diseases but also performs nutrient deficiency detection. This holds significant importance in enhancing both the yield and quality of apples. Conclusion: For the commonly occurring foliar diseases in cultivation, the system exhibited the capability to autonomously recognize and provide decision feedback. In contrast to the less efficient and more costly traditional approach of consulting experts, the more accessible apple foliar disease recognition system was poised to replace it as a primary tool for prevention and control assistance. This system will serve as a guiding companion, safeguarding the robust growth of apple plants.