Orchard Planting Research Articles

A systematic analysis of scan matching techniques for localization in dense orchards

In recent years, different methods have been studied to determine machinery position within a grove, as an alternative for complementing GNSS (global navigation satellite system) information in cases where GNSS signal is occluded. Such a situation can be observed when agricultural machinery travels under dense foliage or on the slopes of mountains. Scan matching techniques arise as a possible solution for localizing the machinery, complementing the absence of the GNSS signal when necessary. However, since key points are difficult to obtain in heterogeneous, unstructured and non-rigid environments (such as orchard plants), the performance of scan matching techniques often decreases in agricultural environments. This paper suggests dividing the point clouds into horizontal and vertical segments to improve the performance of scan-matching methods in orchards. It also examines the best way for registered frames to overlap. We validate the analysis with extensive experimentation in a Fuji apple orchard. The results show that the cumulative localization error in scan matching techniques can be notoriously decreased with selective parts of the orchard, by up to 60%. The experimentation performed herein suggests that the proposed methodology can complement the GNSS navigation in a middle-long path.

Optimizing Orchard Planting Efficiency with a GIS-Integrated Autonomous Soil-Drilling Robot

A typical orchard’s mechanical operation consists of three or four stages: lining and digging for plantation, moving the seedling from nurseries to the farm, moving the seedling to the planting hole, and planting the seedling in the hole. However, the digging of the planting hole is the most time-consuming operation. In fruit orchards, the use of robots is increasingly becoming more prevalent to increase operational efficiency. They offer practical and effective services to both industry and people, whether they are assigned to plant trees, reduce the use of chemical fertilizers, or carry heavy loads to relieve staff. Robots can operate for extended periods of time and can be highly adept at repetitive tasks like planting many trees. The present study aims to identify the locations for planting trees in orchards using geographic information systems (GISs), to develop an autonomous drilling machine and use the developed robot to open planting holes. There is no comparable study on autonomous hole planting in the literature in this regard. The agricultural mobile robot is a four=wheeled nonholonomic robot with differential steering and forwarding capability to stable target positions. The designed mobile robot can be used in fully autonomous, partially autonomous, or fully manual modes. The drilling system, which is a y-axis shifter driven by a DC motor with a reducer includes an auger with a 2.1 HP gasoline engine. SOLIDWORKS 2020 software was used for designing and drawing the mobile robot and drilling system. The Microsoft Visual Basic.NET programming language was used to create the robot navigation system and drilling mechanism software. The cross-track error (XTE), which determines the distances between the actual and desired holes positions, was utilized to analyze the steering accuracy of the mobile robot to the drilling spots. Consequently, the average of the arithmetic means was determined to be 4.35 cm, and the standard deviation was 1.73 cm. This figure indicates that the suggested system is effective for drilling plant holes in orchards.

Agritourism and Socioeconomic Potentials of Orchards

This study explores the potential of developing agritourism through orchard management in the Ilaro Yewa Land region of southwestern Nigeria. Utilizing site-to-site observations and semi-structured questionnaires, the research investigates ten selected orchard plantations, focusing on five to ten prevalent fruit tree species within each plantation. Data was collected from 45 staff members involved in various aspects of the orchards. The findings indicate significant potential for orchards to stimulate agritourism, contributing positively to the local economy. Among the respondents, 97.8% agreed that orchards positively impact tourism, while only 2.2% disagreed. The study suggests that integrating agritourism with orchard management can provide additional income for local farmers, create educational opportunities for visitors, and promote sustainable agricultural practices. This approach supports cultural, economic, and environmental sustainability in the Ilaro Yewa Land region. The research concludes that agritourism, centered around orchard management, is viable and beneficial for enhancing the economic welfare of the local community and maintaining the ecological health of the region.

Spatiotemporal changes of orchards in the ancient canal of the Yellow River using Landsat data

As an important part of the Yellow River Basin, the ancient canal of the Yellow River plays a great role in promoting ecological protection and high-quality development in the Yellow River Basin. There is a need to explore the distribution of the available resources to optimally manage and utilize them more effectively. By analyzing multi-temporal characteristic of the remote sensing images, the spatial temporal distribution characteristics of orchards in the ancient canal of Yellow River were investigated. Time series of orchards were derived from the Landsat images over a nearly 30-year period at approximately 5-year intervals since 1990. And the spatial distribution characteristics were qualified basing on the spatial overlay analysis methods. The results show that from 1990 to 2020, the orchard area in the ancient canal of the Yellow River increased rapidly in the early, then slowed down after 2000; the area of orchards in 2020 was about 1268.30 km2. Dangshan County, Feng County and Xiao County were the major areas planting orchards; 86.84 % of the orchards distributed in flat terrain with an elevation of 21–60 m, 88.50 % distributing on a slope of less than 4° and 91.12 % of the orchards distributed within the distance of more than 280 km from the coastline; Moran's I index of orchard planting density was greater than 0 for all four spatial scales and was increasing when downscaling, which showed significant spatial positive correlation. These findings provide helpful information for the research in promoting ecological protection and high-quality development of the ancient canal of the Yellow River Basin.

Using a rainfall simulator thrust type to evaluate the efficacy of insecticides in a apple orchard

A rainfall simulator thrust type was evaluated as a novel tool for studying the efficacy of insecticides against pests in apple orchards, compared to traditional laboratory methods. The simulator was installed and calibrated to simulate rainfalls of 50 mm h-1 on a 7-year-old apple orchard. The results of Grapholita molesta (Lepidoptera: Tortricidae) control in the field differed from those obtained in laboratory. The control efficacy in the orchard was lower than that obtained in laboratory tests. Control percentages varied throughout the simulated rains, with increases at the beginning of rainfall followed by decreases. The use of the push-type rainfall simulator provides advantages to research experiments, as it allows for evaluations under field conditions at different developmental stages of plants in orchards under different management practices, with results closer to field reality than those currently generated by laboratory tests.

Flora of Bulandshahr District

The paper gives an account of the vegetation of the district of Bulandshahr in Central Uttar Pradesh. Edaphic, climatic, biotic and other factors determining the floristic composition of the district have been discussed in the paper. Aquatic and cultivated plants, avenue trees and orchard plants have been mentioned. A list of 376 species has been appended to give an idea of the flora of the District. Cuscuta capitata Roxb. and Clinopodium umbrosum (M. Bieb.) Koch have been reported for the first time from the U. P. plains.

Xylem Hydraulic Conductance Role in Kiwifruit Decline Syndrome Occurrence

Kiwifruit decline syndrome (KiDS) has affected kiwifruit orchards for more than ten years in the Mediterranean area, severely compromising productivity and causing extensive uprooting. The affected plants go through an irreversible and fast wilting process. The problem has not been solved yet, and a single cause has not been identified. In this work, we carried out a survey on ten five-year-old healthy kiwifruit cv. Hayward plants cultivated in an area strongly affected by KiDS and characterised by a rising temperature and vapor pressure deficit (VPD). Five plants were located in a KiDS-affected orchard. Our goal was to assess the hydraulic conductance of asymptomatic plants in a KiDS-affected area where rising climate change stress is underway. Our hypothesis was that a rising temperature and VPD could impair xylem functionality, leading the plants to develop strategies of tolerance, such as vessel narrowing, or stress symptoms, such as cavitation or implosion, inducing a higher risk of KiDS onset. Hydraulic conductance was investigated using a physiological and morphological approach to detect trunk sap flow, trunk growth and daily diameter variations, leaf gas exchanges and temperature, stem water potential, and the root xylem vessel diameter and vulnerability to cavitation. A strong xylem vessel narrowing was observed in all plants, with the highest frequency in the 30–45 µm diameter class, which is an indicator of long-term adaptation to a rising VPD. In some plants, cavitation and implosion were also observed, which are indicative of a short-term stress response; this behaviour was detected in the plants in the KiDS-affected orchard, where a high leaf temperature (>39 °C), low stomatal conductance (<0.20 mol H2O m−2 s−1) and transpiration (<3 mmol H2O m−2 s−1), low stem water potential (<−1 MPa), high vulnerability to cavitation (3.7 μm mm−2), low trunk sap flow and high daily stem diameter variation confirmed the water stress status. The concurrence of climate stress and agronomic management in predisposing conditions favourable to KiDS onset are discussed, evidencing the role of soil preparation, propagation material and previous crop.

Acarofauna (Acari) associada a pomares de maçã (Malus domestica) e vegetação espontânea como reservatório de ácaros predadores

Abstract The aim of this study was to recognize the mite fauna associated with apple orchards in southern Brazil and present a dichotomous key of the species sampled and those already reported in apple trees in southern Brazil. The studies were carried out in the 2020/2021 harvest in seven apple orchards of the Eva, Fuji and Gala cultivars located in the municipalities of Muitos Capões, Antônio Prado (Rio Grande do Sul state) and São Joaquim (Santa Catarina state). The orchards were divided into quadrants and sampling was carried out monthly. In each orchard, 40 plants were sampled, with three leaves of each plant collected in apical, median and basal regions of a median branch. In addition, monthly five species of spontaneous plants per orchard were sampled. A total of 8,425 mites were found, with the greatest abundance in Antônio Prado (50%), followed by Muitos Capões (35.5%) and São Joaquim (14.5%). The specimens found belong to 29 families, 64 genera and 99 species, in addition to mites of the order Oribatida. The greatest diversity was found in spontaneous vegetation (59 species), being 19 exclusives to apple trees and 21 species common to apple trees and spontaneous vegetation. Phytoseiidae was the family that presented the greatest richness, with 16 species, of which seven were common in apple trees and spontaneous plants. The most abundant species was Aculus schlechtendali Nalepa (Eriophyidae) (39.5%), followed by Panonychus ulmi (Koch) (Tetranychidae) (14.6%), Polyphagotarsonemus latus (Banks) (Tarsonemidae) (9.4%) and Neoseiulus californicus (McGregor) (Phytoseiidae) (7.4%). These results suggest that the mite fauna present in apple orchards in different landscapes and management are distinct, with a greater diversity of phytoseiid mites present in organic areas. Therefore, to maintain a greater diversity of predatory mites in these orchards, organic management seems to be the most appropriate. Furthermore, the high acarine diversity found in spontaneous vegetation demonstrates the importance of maintaining these plants in orchards that serve as refuges and reservoirs, favoring the permanence of natural enemies in these environments.

Multiscale Inversion of Leaf Area Index in Citrus Tree by Merging UAV LiDAR with Multispectral Remote Sensing Data

The LAI (leaf area index) is an important parameter describing the canopy structure of citrus trees and characterizing plant photosynthesis, as well as providing an important basis for selecting parameters for orchard plant protection operations. By fusing LiDAR data with multispectral data, it can make up for the lack of rich spatial features of multispectral data, thus obtaining higher LAI inversion accuracy. This study proposed a multiscale LAI inversion method for citrus orchard based on the fusion of point cloud data and multispectral data. By comparing various machine learning algorithms, the mapping relationship between the characteristic parameters in multispectral data and point cloud data and citrus LAI was established, and we established the inversion model based on this, by removing redundant features through redundancy analysis. The experiment results showed that the BP neural network performs the best at both the community scale and the individual scale. After removing redundant features, the R2, RMSE, and MAE of the BP neural network at the community scale and individual scale were 0.896, 0.112, 0.086, and 0.794, 0.408, 0.328, respectively. By adding the three-dimensional gap fraction feature to the two-dimensional vegetation index features, the R2 at community scale and individual scale increased by 4.43% and 7.29%, respectively. The conclusion of this study suggests that the fusion of point cloud and multispectral data exhibits superior accuracy in multiscale citrus LAI inversion compared to relying solely on a single data source. This study proposes a fast and efficient multiscale LAI inversion method for citrus, which provides a new idea for the orchard precise management and the precision of plant protection operation.

Aesthetic and ecological characteristics of Prunus Taxa in landscape design: A Study in eastern and southeastern provinces of Türkiye

Plants play a crucial role in landscape design and are at the heart of landscape design. Climate change's purposeful plant choices could improve landscape design. In this study, it is tackeled using some native Subgen Amygdalus taxa in the landscape to make the natural environment flexible against global climate change, as some species are indispensable elements of plant breeders and gardens, which have adapted to the arid habitat and Türkiye is among the gene centers. The research was carried out in rural areas, afforestation areas and gardens in the provinces of Adıyaman, Hakkâri, Malatya, Şanlıurfa and Van and detected taxa were recorded on form through on-site observation, photographing and collected in accordance with the herbarium technique later to identify according to Browicz (1972) and Yazbek (2010). After field studies, the aesthetic and ecological characteristics of each of Subgenus Amygdalus were evaluated based on plant design. In the course of study fields, it was determined that P. dulcis, P. orientalis and P. arabica are used in afforestation and erosion control areas, P. dulcis in almond orchard plant, P. arabica, P. orientalis and P. spinosisima are used as hedge plants, and some taxa are used as rootstock and and they grow in different ecological areas with outstanding visual effect. In this study, it is aimed to determine Subgen Amygdalus growing naturally in study area, their aesthectic and ecologic features and the roles they can undertake in the landscape against climate crisis and to be introduced.

Anti-Drift Technology Progress of Plant Protection Applied to Orchards: A Review

In orchard plant protection application, an anti-drift strategy can effectively reduce drift in the non-target area, reduce spray drift in the environment, and avoid spray leakage and overspraying. To clarify the future development direction of orchard plant protection mechanization technology, this review introduces the development status of an anti-drift spray nozzle and the impact of different types of spray nozzles on the potential of drift, and then, it analyzes the research progress on air-assisted spraying, recycling spraying, profiling spraying, target variable spraying technologies, and plant protection UAVs. It also provides a general analysis of the above spraying technologies on the amount of drift and the impact of pesticide deposition. Finally, combined with the characteristics of orchard plant protection, the paper presents the research and development of anti-drift nozzles, pesticide adjuvant, air-assisted spraying technology, electrostatic, recycling spraying technology, profiling and target variable spraying technology, and plant protection UAVs. The review provides a reference for the development of an anti-drift strategy for orchard plant protection production.

Integration of RS/GIS in Assessing the National Great Green Wall Woodlots/Orchards in Katagum LGA, Bauchi State, Nigeria

The study is based on the premise that climate change and desertification have strong connection in the ecosystem. Because desertification affects climate change through the loss of fertile soil and corresponding vegetation, it also has important repercussions for the global climate system. Through the Great Green Wall (GGW) tree planting project initiatives, a lot has been achieved elsewhere hence this study. In Nigeria, the programme was introduced in Bauchi State (northern Nigeria) as one of the 11 front line states where desertification is observed. The study was conducted under the hypothetical assumption that the planting of Woodlots and Orchards can help checkmate and control the seeming desertification in the Katagum Local Government Area of Bauchi State, Nigeria. Six woodlots and Orchards were identified and mapped using the Google Earth image visualization platform and the spatial extent of change were determined in hectare (Ha) using the digitizing tool in the software. Except Dugunde (which reduced from 2,499.65 to 2,265.96 Ha), the rest increased within the period under review. Dagoro increased from 371.45 Ha to 372.91 Ha, followed by Dangazau (324.02 to 328.05 Ha), Gambaki (1,154.04 to 1.167.07 Ha), Dugunde 2 (469.42 to 537.74 Ha), and Dugunde 3 (719.58 to 749.61). The Orchard and Woodlots’ growth is understandable because of continuous watering and tending of the vegetation over the years. From sampled questionnaires, the study further reveals that the Woodlots and Orchards are very effective mechanism in controlling desertification in the Northern State. The study shows that the locals are satisfied with the project and are ready to support the programme because it provided employment for them, and also helps to preserve the environment and tree species. The satisfaction with the use of woodlots and orchards

Different management strategies for non-cropping plants in pear orchards and their impact on biological control

Different management strategies for non-cropping plants in pear orchards and their impact on biological control

Inter-comparison of the Penman-Monteith type model in modeling the evapotranspiration and its components in an orchard plantation of Southwest China

Crop evapotranspiration (ET) along with its components (canopy transpiration (T) and soil evaporation (E)) estimates are crucial for agroecosystem hydrological process research and developing agricultural water-saving strategies. An inter-comparison of the Penman-Monteith type model, including Penman-Monteith (PM), Shuttleworth-Wallace (S-W), Two-Patch (T-P) and topography- and vegetation-based surface energy partitioning algorithm (TVET), Clumping (CL) and developed Two patch-Two layer (T-T) model was conducted to estimate ET and its components in a kiwifruit orchard. Results showed that all models can well capture the pattern of eddy covariance-based hourly ET (ETEC), with a slope of 0.82–1.10, R2 of 0.78–0.83, and RMSE of 0.039–0.049 mm 0.5 h–1, and yield relatively reliable estimates validated by sap flow-based hourly T, with a slope of 0.93–1.16, R2 of 0.72–0.79, and RMSE 0.017–0.026 mm 0.5 h–1. All the P-M type models agreed well with the daily ETEC, with a slope of 0.88–1.21, R2 of 0.82–0.86, and RMSE of 0.55–0.88 mm d–1, respectively. S-W overestimated actual ET due to overestimation in both T and E, T-P and TVET models overestimated T but underestimated actual E as they ignored the soil contribution under the canopy. T-T model outperformed other models in daily ET, T, and E estimates, with R2 of 0.86, 0.73 and 0.73, and RMSE of 0.56, 0.39 and 0.46 mm d–1, respectively. The output ET and T of the different P-M type models were most sensitive to canopy resistance (rsc), while E is most sensitive to aerodynamic resistance between substrate and crop canopy. Net radiation was the most crucial meteorological factor affecting ET, T and E, as it directly participated in the energy balance calculation. The output T was sensitive to air temperature since it affected rsc, while E was relatively sensitive to soil water content since it greatly changed soil surface resistance.

Application of living mulch in rows of the apple trees on several rootstocks – long-term evaluation

The long-term influence of several living mulches on apple tree growth, nutrient status, yield, and fruit quality concerning the year of cover crop sowing in tree rows was evaluated in the Lower Silesia region in the southwestern part of Poland. The estimation was conducted in six apple tree ‘Ligol’ populations differentiated by the rootstock: M.26, M.9, P 60, P 2, P 16, and P 22. In experiment no. 1, one-year-old nursery stock was planted, and perennial living mulches were sown: colonial bent grass (Agrostis vulgaris With.) and white clover (Trifolium repens L.) in the same year and blue fescue (Festuca ovina L.) in the following year. In experiment no. 2, which involved two-year-old stock, the sowing of blue fescue was delayed until the second, third, fourth, and fifth years following orchard planting. The presence of the cover crop significantly affected young tree growth when one-year-old trees were planted. The sowing of the living mulch in the first or the second year after tree planting led to a significant reduction in the cumulative yield obtained from the young trees. The living mulch improved the red coloration of the fruit skin in the young orchard, but it caused a reduction in the mean fruit weight and size. However, it also contributed to decreased nitrogen concentration in the leaves of the apple trees, and the tree tolerance to living mulch increased as the orchard aged. A choice of semidwarf rootstock, postponed sowing of cover crop, and high-quality nursery stock were recognized as the most important factors for fostering apple tree tolerance to living mulches in tree rows.

Ex-Ante Co-Benefit of Orchard Cropping as Climate Resilient Agriculture Practice in Drought Prone Area, Jalna District, Maharashtra, India

A Project on Climate Resilient Agriculture (PoCRA) in drought prone regions of Maharashtra is intending to increase farm productivity and income of small land holding farmers. Horticulture plantation activity under project is one of climate resilient agriculture practice supported by PoCRA. About 93 farm plots of horticulture plantation and its co-benefits in Jalna district of Maharashtra have studied. A biomass estimation method was used for the measure of carbon sequestration. This method is essentially requiring plant density, height and girth diameter. It has observed that larger the plant biomass highest will be the carbon sequestered. Also, the number of plants per hectare has impact on biomass accounting. As per the observations, study shows highest to lowest carbon sequestration in plants in following order Pomegranate > Sweet lime > Mango > Guava > Custard apple i.e., respectively 66.38, 65.11, 33.24, 25.68 and 14.9 Kg of carbon sequestered per plant per year. This study primarily focuses on potential of carbon sequestration of horticulture plantation and ex-ante co-benefits in conservation of soil, water, nutrient. From the (PoCRA project) data it has observed that about 2215 ha of land is under fruit crop plantation (till September 2021) sequestering about 52,473.35 tons of CO2 per year. Also, it is expected that soil is conserve directly at these 2215 ha of orchard plantation plots, and 50% area covering drip irrigation conserve the water and nutrient, figured through farmer’s application on portal i.e., for both drip irrigation and plantation. Therefore, it is benefitting farmers economically and sequestering carbon and conserving environment as co-benefit.

Visualization of Lidar-Based 3D Droplet Distribution Detection for Air-Assisted Spraying

Air-assisted spraying is a commonly used spraying method for orchard plant protection operations. However, its spraying parameters have complex effects on droplet distribution. The lack of large-scale 3D droplet density distribution measurement methods of equipment has limited the optimization of spraying parameters. Therefore, there is a need to develop a method that can quickly obtain 3D droplet distribution. In this study, a 2D LiDAR was used to quickly scan moving droplets in the air, and a test method that can obtain the visualization of 3D droplet distribution was constructed by using the traveling mode of the machine perpendicular to the scanning plane. The 3D droplet distribution at different positions of the nozzle installed in the air-assisted system was tested at different fan rotation speeds, and the methods for signal processing, point cloud noise reduction, and point cloud division for 2D LiDAR were developed. The results showed that the LiDAR-based method for detecting 3D droplet distribution is feasible, fast, and environmentally friendly.

ASFL-YOLOX: an adaptive spatial feature fusion and lightweight detection method for insect pests of the Papilionidae family.

Insect pests from the family Papilionidae (IPPs) are a seasonal threat to citrus orchards, causing damage to young leaves, affecting canopy formation and fruiting. Existing pest detection models used by orchard plant protection equipment lack a balance between inference speed and accuracy. To address this issue, we propose an adaptive spatial feature fusion and lightweight detection model for IPPs, called ASFL-YOLOX. Our model includes several optimizations, such as the use of the Tanh-Softplus activation function, integration of the efficient channel attention mechanism, adoption of the adaptive spatial feature fusion module, and implementation of the soft Dlou non-maximum suppression algorithm. We also propose a structured pruning curation technique to eliminate unnecessary connections and network parameters. Experimental results demonstrate that ASFL-YOLOX outperforms previous models in terms of inference speed and accuracy. Our model shows an increase in inference speed by 29 FPS compared to YOLOv7-x, a higher mAP of approximately 10% than YOLOv7-tiny, and a faster inference frame rate on embedded platforms compared to SSD300 and Faster R-CNN. We compressed the model parameters of ASFL-YOLOX by 88.97%, reducing the number of floating point operations per second from 141.90G to 30.87G while achieving an mAP higher than 95%. Our model can accurately and quickly detect fruit tree pest stress in unstructured orchards and is suitable for transplantation to embedded systems. This can provide technical support for pest identification and localization systems for orchard plant protection equipment.

Intercropping of aromatic plants in truffle orchards: short-term effect on extraradical truffle mycelium and aromatic plant growth

Intercropping of aromatic plants in truffle orchards: short-term effect on extraradical truffle mycelium and aromatic plant growth

Design and Test of an Automatic Navigation Fruit-Picking Platform

With the development in agricultural mechanization and information technology, orchard agricultural machinery is also constantly pursuing the goal of intelligence and efficiency. Fruit picking is the most labor-intensive part of the orchard harvesting process. In order to resolve the problems of high labor intensity, low picking efficiency, and labor shortage when harvesting dwarf high-density orchards, an automatic navigation fruit-picking platform with voice control was developed in the present study. First, the platform utilized a voice-controlled high-level extendable working platform and a fruit-box-lifting device to adapt to varying orchard planting row spacing and enable convenient fruit box loading and unloading. Second, an automatic navigation system, which employed China’s Beidou navigation satellite system to acquire positional data and the Stanley algorithm for path-tracking control, was implemented. Third, the fruit-picking platform with automatic navigation system was fabricated and assembled, its outer wheel steering was measured to have a maximum angle of 30.3° and an average minimum turning radius of 4.5 m, meeting the turning radius requirements under orchard conditions. Finally, automatic navigation tests of the developed platform were performed in the orchard conditions. The results indicated that the platform could maintain a straight-line path with a maximum lateral deviation of 101.5 mm and a maximum absolute average deviation of 44.1 mm at 0.4 m/s. Under the U-shaped paths, the measured maximum lateral deviation was 148.6 mm and the maximum absolute average deviation was 57.2 mm. The navigation accuracy was sufficient to meet the requirements for the harvesting platform’s routine operation in the orchards.