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Highlights A LiDAR-guided automatic airflow control system for precision sprayers was developed. Three models were built to measure the amount of airflow required for apple trees. The study confirmed that adjusting the fan inlet could control airflow penetration into tree canopies. Results suggest that the system can reduce spray drift and off-target losses. Abstract. The airflow discharged from orchard airblast sprayers is a primary component for successfully carrying spray droplets to the target trees. Because of the variation in orchard tree canopies, control of the airflow to minimize off-target loss during spray application is essential. An automatic airflow control system for precision sprayers was developed to maximize spray droplet coverage on targets and minimize off-target loss while considering the tree canopy densities. The primary component of the system was an iris damper, which was designed as a retrofit attachment on the fan inlet of a three-point airblast intelligent sprayer. A 3D light detection and ranging (LiDAR) sensor was installed at the top of the sprayer to acquire the tree canopy data. A motor was employed to control the damper opening with a micro-controller. To develop the models required for automatic airflow control, field experiments were conducted at three canopy density orchards with different cultivars (GoldRush, Gala, and Fuji). A total of 15 trees (five trees from each cultivar) were randomly selected, and five different damper openings (openings 1, 2, 3, 4, and 5) were tested for each tree. Opening 1 represented the same air inlet as a traditional precision airblast sprayer, while openings 2, 3, 4, and 5 were the sequentially reduced air inlets of the sprayer. A canopy density measurement algorithm was scripted to measure the canopy point density of individual trees. Three models were built to show relationships between (1) tree canopy point densities and airflows; (2) canopy densities and damper openings; and (3) damper opening and motor steps. The combination of the two models (2 & 3) was used to assess the amount of airflow required for a specific canopy density. Field validations for medium and high-density trees showed that the system achieved adequate spray penetration at the top, middle, bottom, back-left, and back-right positions of the tree sections and reduced off-target loss at the ground and edge of next row sections using openings 4 and 2, respectively. However, the mechanical motion of the damper required 3 s to move from minimum to maximum opening, so the average canopy density was recommended to control the airflow. The overall results suggested that the automatic airflow control system could reduce spray drift and off-target losses and improve spray application efficiency in orchards. Keywords: Automation, Canopy sensing, Fan inlet, Precision spraying, Variable rate application.

Digital intervention tools against problematic smartphone usage help users control their consumption on smartphones, for example, by setting a time limit on an app. However, today's social media apps offer a mix of quasiessential and addictive features in an app (e.g., Instagram has following feeds, recommended feeds, stories, and direct messaging features), which makes it hard to apply a uniform logic for all uses of an app without a nuanced understanding of feature-level usage behaviors. We study when and why people regret using different features of social media apps on smartphones. We examine regretful feature uses in four smartphone social media apps (Facebook, Instagram, YouTube, and KakaoTalk) by utilizing feature usage logs, ESM surveys on regretful use collected for a week, and retrospective interviews from 29 Android users. In determining whether a feature use is regretful, users considered different types of rewards they obtained from using a certain feature (i.e., social, informational, personal interests, and entertainment) as well as alternative rewards they could have gained had they not used the smartphone (e.g., productivity). Depending on the types of rewards and the way rewards are presented to users, probabilities to regret vary across features of the same app. We highlight three patterns of features with different characteristics that lead to regretful use. First, "following"-based features (e.g., Facebook's News Feed and Instagram's Following Posts and Stories) induce habitual checking and quickly deplete rewards from app use. Second, recommendation-based features situated close to actively used features (e.g., Instagram's Suggested Posts adjacent to Search) cause habitual feature tour and sidetracking from the original intention of app use. Third, recommendation-based features with bite-sized contents (e.g., Facebook's Watch Videos) induce using "just a bit more," making people fall into prolonged use. We discuss implications of our findings for how social media apps and intervention tools can be designed to reduce regretful use and how feature-level usage information can strengthen self-reflection and behavior changes.

HighlightsA robotic mushroom picking mechanism was developed, including positioning, picking, and stipe trimming.The picking end-effector was designed based on a bending motion around the stipe-substrate joint.The overall success rate of the developed picking mechanism reached 91.4%.Acting time and air pressure for the suction cup were studied in mushroom bruise level tests.Abstract. Button mushroom (Agaricus bisporus) harvesting mainly relies on costly manpower, which is time-consuming and labor-intensive. Robotic harvesting is an alternative method to address this challenge. In this study, a robotic mushroom picking mechanism was designed, including a picking end-effector based on a bending motion, a four degree-of-freedom (DoF) positioning end-effector for moving the picking end-effector, a mushroom stipe trimming end-effector, and an electro-pneumatic control system. A laboratory-scale prototype was fabricated to validate the performance of the mechanism. Bruise tests on the mushroom caps were also conducted to analyze the influence of air pressure and acting time of the suction cup on bruise level. The test results showed that the picking end-effector was successfully positioned to the target locations. The success rate of the picking end-effector was 90% at first pick and increased to 94.2% after second pick. The main reason for the failures was inclined growing condition of those mushrooms, resulting in difficulties in engaging the mushroom cap with the suction cup facing straight downward. The trimming end-effector achieved a success rate of 97% overall. The bruise tests indicated that the air pressure was the main factor affecting the bruise level, compared to the suction cup acting time, and an optimized suction cup may help to alleviate the bruise damage. The laboratory test results indicated that the developed picking mechanism has potential to be implemented in automatic mushroom harvesting. Keywords: Bruise test, End-effector, Mushroom, Robotic harvesting.

HighlightsA branch accessibility simulation was performed for robotic pruning of apple trees.A virtual tree environment was established using a kinematic manipulator model and an obstacle model.Rapidly-exploring random tree (RRT) was combined with smoothing and optimization for improved path planning.Effects on RRT path planning of the approach angle of the end-effector and cutter orientation at the target were studied.Abstract. Robotic pruning is a potential solution to reduce orchard labor and associated costs. Collision-free path planning of the manipulator is essential for successful robotic pruning. This simulation study investigated the collision-free branch accessibility of a six rotational (6R) degrees of freedom (DoF) robotic manipulator with a shear cutter end-effector. A virtual environment with a simplified tall spindle tree canopy was established in MATLAB. An obstacle-avoidance algorithm, rapidly-exploring random tree (RRT), was implemented for establishing collision-free paths to reach the target pruning points. In addition, path smoothing and optimization algorithms were used to reduce the path length and calculate the optimized path. Two series of simulations were conducted: (1) performance and comparison of the RRT algorithm with and without smoothing and optimization, and (2) performance of collision-free path planning considering different approach poses of the end-effector relative to the target branch. The simulations showed that the RRT algorithm successfully avoided obstacles and allowed the manipulator to reach the target point with 23 s average path finding time. The RRT path length was reduced by about 28% with smoothing and by 25% with optimization. The RRT smoothing algorithm generated the shortest path lengths but required about 1 to 3 s of additional computation time. The lowest coefficient of variation and standard deviation values were found for the optimization method, which confirmed the repeatability of the method. Considering the different end-effector approach poses, the simulations suggested that successfully finding a collision-free path was possible for branches with no existing path using the ideal (perpendicular cutter) approach pose. This study provides a foundation for future work on the development of robotic pruning systems. Keywords: Agricultural robotics, Collision-free path, Manipulator, Path planning, Robotic pruning, Virtual tree environment.

HighlightsAn end-effector with two degrees of freedom (2R) was developed for pruning apple trees.A rational 2×2 relationship (R2 = 0.93) was found for ‘Fuji’ apple tree branch diameter and cutting force.Simulation showed that the cutter can be aligned in a wide range of orientations in a spherical workspace.The developed end-effector was able to cut branches up to 12 mm in diameter.Abstract. Robotics and automation technologies are now used extensively in agriculture, while production operations for tree fruit crops still largely depend on manual labor. Manual pruning is a labor-intensive and costly task in apple production. Robotic pruning is a potential solution, but it involves several challenges due to the unstructured work environment. This study focused on designing an end-effector prototype for pruning considering the maneuvering, spatial, mechanical, and horticultural requirements. Branch cutting force was measured with a thin force sensor to provide guidelines for the end-effector design. The test results indicated the relationship between the force required to cut different diameter branches with an R2 value of 0.93. The end-effector was developed using two rotary motors, a pneumatic cylinder, and a pair of bypass shear blades. A three-directional linear manipulator system and a control system were built for moving the end-effector to targeted locations. A mathematical model was developed for simulation of the workspace utilization and reachable points of the end-effector. The simulation results indicated that the end-effector can be aligned in a wide range of orientations of the cutter. Field tests were conducted for validation of the simulation results and performance assessment of the end-effector. The results indicated that the end-effector with the current parameter settings successfully cut branches up to 12 mm in diameter and was able to cut branches in a wide range of possible orientations in a given 3D space. The robotic end-effector developed in this study is a core component of an automated pruning system for fruit trees. In future work, an integrated manipulator system will be developed for branch accessibility with collision-free trajectories. Keywords: Malus × domestica (Borkh.), Pruning end-effector, Reachable-points simulation, Tree pruning.

HighlightsThermal conductivity significantly decreased (p < 0.05), particularly in the last two weeks of the growing season.Thermal conductivity values were significantly different (p < 0.05) between the measurement locations.Thermal conductivity had a moderate correlation (0.35 < |r| < 0.67) with maturity indices.Abstract. ±±W m·K-1±±2-1 Keywords: Apple maturity, DNHP, Harvest time, Malus × domestica (Borkh.), Thermal conductivity, Thermal properties.

Amphibian biodiversity is declining globally, with over 40% of species being considered threatened to become extinct. Crucial to the success of conservation initiatives are a comprehensive understanding of life history and reproductive ecology of target species. Here we provide an overview of the Pseudacris genus, including breeding behaviour, reproduction, development, survival and longevity. We present an updated distribution map of the 18 species found throughout North America. We also summarize the conservation status at the national and subnational (state, provincial, and territorial) levels, in Canada, USA, and Mexico, to evaluate the relationship between life history traits and extinction risk. Results show a high degree of consistency in the life history traits of Pseudacris species considering their relative diversity and wide distribution in North America. However, data are lacking for several species, particularly in the Fat Frog and West Coast clades, causing some uncertainties and discrepancies in the literature. We also found that the most threatened populations of chorus frog were located in the east coast of the USA, potentially as a result of increased levels of anthropogenic disturbance. We suggest that the similarities in life history traits among chorus frog species provides an opportunity for collaboration and united efforts for the conservation of the genus. Supplementary Information The online version contains supplementary material available at 10.1186/s12983-021-00425-w.

Monitoring of fruit size development has important implications for apple orchard management decision making such as scheduling for fruitlet chemical thinning and allocating resources for harvest. The current method for tracking fruit size development is by tagging a sample of fruits and using calipers or sizing rings to make measurements, which can be labor-intensive and time-consuming. In this study, a stereo vision system was developed which sized fruits on a tree and kept track of their growth during the season by matching fruit in images across time. Neural network models including Faster R-CNN and Mask R-CNN were used for fruit detection and on-tree fruit sizing. Camera pose estimation using feature matching of apples was used for tracking individual fruit growth. The best performance on fruit matching for the ‘Golden Delicious‘ variety during the growing season in an apple orchard was observed in September and October; 74% of all detected fruits which were fully visible were matched between the two months. Fruitlets averaging 25 mm in diameter also had a matching accuracy of 73% during two imaging trials performed on the same day for the month of June.

Precision irrigation with sensors has proven to be effective for water saving in crop production. Internet of things (IoT) system is necessary for monitoring real-time data from sensors and automating irrigation systems. Long-range wide-area network (LoRaWAN) is low-cost and easy to be implemented in IoT systems that can be used for precision crop irrigation. In this study, an IoT-based precision irrigation system with LoRaWAN technology was developed and evaluated as a precision management tool on fresh-market tomato production in an open field. Four irrigation scheduling treatments were designed and tested, including ET (ETc), MP60 (Watermark 200SS-5 soil matric potential sensors, -60 kPa), MP40 (-40 kPa), and GesCoN (decision support system). The treatments were arranged based on a randomized complete block design (RCBD) with four replications. System feasibility, yield, and irrigation water use efficiency (iWUE) were evaluated during the experiment. The results indicated that treatment MP60 and GesCoN had a marketable yield 15.2% and 22.1% higher than ET, respectively. MP40 had a marketable yield 12.5% lower than ET. GesCoN had a significantly higher yield than ET and MP40. However, MP60 did not produce significantly different results from GesCoN and ET but had higher yield than MP40. MP40 received relatively low water via irrigation because of unproper installation and positioning of the soil moisture sensors, which caused a higher incidence of blossom end-rot and thus lower marketable yield. Nevertheless, the LoRaWAN-based IoT system worked well in terms of power consumption, communication, sensors reading and valve control. It can be potentially implemented for precision and automatic irrigation operation in vegetable fields.

Various cucurbitacins have been isolated, and their structures have been elucidated. Owing to their economic potential and importance as active pharmacological compounds, their cytotoxicity in various cancer cells has been assessed. Here, we mined several candidate genes with potential involvement in cucurbitacin biosynthesis in watermelon (Citrullus lanatus) and performed in vitro enzymatic assays and instrumental analyses using various substrates to identify cucurbitacin functions and products. Enzymatic activities of two acetyltransferases (ACTs) and one UDP-glucosyltransferase (UGT) against cucurbitacins were confirmed, resulting in the synthesis of novel cucurbitacins in vivo and/or in vitro to our knowledge. As ACTs and UGT are involved in the dynamic conversion of cucurbitacins by catalyzing acetylation and glucosylation at moieties in the cucurbitacins skeleton, these findings improve our knowledge on how these genes contribute to the diversity of cucurbitacins., Kim et al. use RNAseq of two watermelons to select candidate genes coding for enzymes that catalyze modifications of cucurbitacins. They characterise four of the 16 candidate enzymes (3 different acetyltransferases and one UDP-glucosyltransferase) by HPLC, LC-MS, NMR, and in vitro enzymatic assay. They further show with in vivo assay in Drosophila, that acetylation of cucurbitacin increases neuronal activity in insects.

International audience; Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is an autoimmune disorder which affects small-and, to a lesser degree, medium-sized vessels. ANCA-associated vasculitis encompasses three disease phenotypes: granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), and eosinophilic granulomatosis with polyangiitis (EGPA). This classification is largely based on clinical presentations and has several limitations. Recent research provided evidence that genetic background, risk of relapse, prognosis, and co-morbidities are more closely related to the ANCA serotype, proteinase 3 (PR3)-ANCA and myeloperoxidase (MPO)-ANCA, compared to the disease phenotypes GPA or MPA. This finding has been extended to the investigation of biomarkers predicting disease activity, which again more closely relate to the ANCA serotype. Discoveries related to the immunopathogenesis translated into clinical practice as targeted therapies are on the rise. This review will summarize the current understanding of the immunopathogenesis of ANCA-associated vasculitis and the interplay between ANCA serotype and proposed disease biomarkers and illustrate how the extending knowledge of the immunopathogenesis will likely translate into development of a personalized medicine approach in the management of ANCA-associated vasculitis.