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An orchard sprayer prototype running a variable-rate algorithm to adapt the spray volume to the canopy characteristics (dimensions, shape and leaf density) in real-time was designed and implemented. The developed machine was able to modify the application rate by using an algorithm based on the tree row volume, in combination with a newly coefficient defined as Density Factor (Df). Variations in the canopy characteristics along the row crop were electronically measured using six ultrasonic sensors (three per sprayer side). These differences in foliage structure were used to adjust the flow rate of the nozzles by merging the ultrasonic sensors data and the forward speed information received from the on-board GNSS. A set of motor-valves was used to regulate the final amount of sprayed liquid. Laboratory and field tests using artificial canopy were arranged to calibrate and select the optimal ultrasonic sensor configuration (width beam and signal pre-processing method) that best described the physical canopy properties. Results indicated that the sensor setup with a medium beam width offered the most appropriate characterization of trees in terms of width and Df. The experimental sprayer was also able to calculate the application rate automatically depending on changes on target trees. In general, the motor valves demonstrated adequate capability to supply and control the required liquid pressure at all times, mainly when spraying in a range between 4.0 and 14.0 MPa. Further work is required on the equipment, such as designing field efficiency tests for the sprayer or refining the accuracy of Df.

Site-specific management of crops represents an important improvement in terms of efficiency and efficacy of the different labours, and its implementation has experienced a large development in the last decades, especially for field crops. The particular case of the spray application process for what are called “specialty crops” (vineyard, orchard fruits, citrus, olive trees, etc.) represents one of the most controversial and influential actions directly related with economical, technical, and environmental aspects. This study was conducted with the main objective to find possible correlations between data obtained from remote sensing technology and the actual canopy characteristics. The potential correlation will be the starting point to develop a variable rate application technology based on prescription maps previously developed. An unmanned aerial vehicle (UAV) equipped with a multispectral camera was used to obtain data to build a canopy vigour map of an entire parcel. By applying the specific software DOSAVIÑA®, the canopy map was then transformed into a practical prescription map, which was uploaded into the dedicated software embedded in the sprayer. Adding to this information precise georeferenced placement of the sprayer, the system was able to modify the working parameters (pressure) in real time in order to follow the prescription map. The results indicate that site-specific management for spray application in vineyards result in a 45% reduction of application rate when compared with conventional spray application. This fact leads to a equivalent reduction of the amount of pesticide when concentration is maintained constant, showing once more that new technologies can help to achieve the goal of the European legislative network of safe use of pesticides.

Biochar can potentially increase crop production in saline soils. However, the appropriate amount of biochar that should be applied to benefit from resource preservation and increase both grain yield (GY) and quality is not clear. A pot experiment was conducted to evaluate the effects of biochar applied at various rates (i.e., 0, 5, 10, 20, 30, 40 and 50 t/ha) on the nitrogen use efficiency (NUE), GY and amino acid (AA) contents of wheat plants in saline soils. The results showed that the application of 5–20 t/ha biochar increased wheat NUE by 5.2–37.9% and thus increased wheat GY by 2.9–19.4%. However, excessive biochar applications (more than 30 t/ha) had negative effects on both the NUE and GY of wheat. Biochar had little influence on leaf soil and plant analyzer development (SPAD) values, the harvest index or yield components. The AAs were significantly affected by biochar, depending on the application rate. Among the application rates, 5–30 t/ha biochar resulted in relatively higher (by 5.2–19.1%) total AA contents. Similar trends were observed for each of the 17 essential AAs. In conclusion, the positive effects of biochar occurred when it was applied at appropriate rates, but the effects were negative when biochar was overused.

Canopy characteristics are crucial for accurately and safely determining the pesticide quantity and volume of water used for spray applications in vineyards. The inevitably high degree of intraplot variability makes it difficult to develop a global solution for the optimal volume application rate. Here, the design procedure of, and the results obtained from, a variable rate application (VRA) sprayer are presented. Prescription maps were generated after detailed canopy characterization, using a multispectral camera embedded on an unmanned aerial vehicle, throughout the entire growing season in Torrelavit (Barcelona) in four vineyard plots of Chardonnay (2.35 ha), Merlot (2.97 ha), and Cabernet Sauvignonn (4.67 ha). The maps were obtained by merging multispectral images with information provided by DOSAVIÑA®, a decision support system, to determine the optimal volume rate. They were then uploaded to the VRA prototype, obtaining actual variable application maps after the application processes were complete. The prototype had an adequate spray distribution quality, with coverage values in the range of 20–40% and exhibited similar results in terms of biological efficacy on powdery mildew compared to conventional (and constant) application volumes. The VRA results demonstrated an accurate and reasonable pesticide distribution, with potential for reduced disease damage even in cases with reduced amounts of plant protection products and water.

Since literature is not unanimous about profitability of variable rate application (VRA), a systematic analysis is essential to determine when, where and how to increase the production profits. This paper examines the relationship between the within-field spatial variability of soil fertility and profitability of variable rate fertilisation (VRF) and VR seeding (VRS). Within-field spatial variability was determined using high resolution data of key soil attributes, subjected to a modified Cambardella Index (CI). Profitability was determined as the net revenue over the VRA input, which is an adjusted form of the contribution margin. Results showed that the contribution margin of VRAs ranged from 847 to 6624 EUR per ha. Variations in the adjusted contribution margin were positively correlated with the adjusted Cambardella index, confirming the assumption that VRA is more profitable in fields with a higher spatial variability. Findings are interpreted in a production-theoretical framework, which discussed whether, when and under which circumstances, the observed potential for profit will effectively lead to profitability increases.

Variable rate application (VRA) is a crucial tool in precision agriculture, utilizing platforms such as Google Earth Engine (GEE) to access vast satellite image datasets and employ machine learning (ML) techniques for data processing. This research investigates the feasibility of implementing supervised ML models (random forest (RF), the support vector machine (SVM), gradient boosting trees (GBT), classification and regression trees (CART)) and unsupervised k-means clustering in GEE to generate accurate management zones (MZs). By leveraging Sentinel-2 satellite imagery and yielding monitor data, these models calculate vegetation indices to monitor crop health and reveal hidden patterns. The achieved classification accuracy values (0.67 to 0.99) highlight the potential of GEE and ML models for creating precise MZs, enabling subsequent VRA implementation. This leads to enhanced farm profitability, improved natural resource efficiency, and reduced environmental impact.

Agriculture is one of the economic sectors that affects climate change contributing to greenhouse gas emissions directly and indirectly. There is a trend of agricultural greenhouse gas emissions reduction, but any practice in this direction should not affect negatively farm productivity and economics because this would limit its implementation, due to the high global food and feed demand and the competitive environment in this sector. Precision agriculture practices using high-tech equipment has the ability to reduce agricultural inputs by site-specific applications, as it better target inputs to spatial and temporal needs of the fields, which can result in lower greenhouse gas emissions. Precision agriculture can also have a positive impact on farm productivity and economics as it provides higher or equal yields with lower production cost than conventional practices. In this work, the precision agriculture technologies that have the potential to mitigate greenhouse gas emissions are presented providing a short description of the technology and the impacts that have been reported in literature on greenhouse gases reduction and the associated impacts on farm productivity and economics. The technologies presented span between all agricultural practices, including variable rate sowing/planting, fertilizing, spraying, weeding and irrigation.

PurposeIt is unclear whether a higher biochar (BC) application rate enhances rice (Oryza sativa L.) yield and reduces CH4 emissions. This study investigated changes in rice yield and CH4 emissions with varying BC application rates.MethodsData on rice yield and CH4 emission from paddies amended with or without BC were collected from the literature, and the biochar effects were analyzed using the data set.ResultsAcross the biochar application rate from 2 to 48 t ha-1, the rice yield increased (by 10.8%) while the area-scaled (by 14.4%) and yield-scaled CH4 emission (by 22.2%) decreased. However, the correlation of BC application rates with rice yield and CH4 mitigation was not significant, implying that a higher BC application rate did not enhance rice yield and CH4 reduction. Interestingly, for a data set showing increased rice yield and decreased CH4 emission by BC, the magnitude of change in the rice yield and CH4 mitigation per unit weight of BC (1 t ha-1) decreased with an increase in the BC application rate. These results suggest that BC effects on rice yield and CH4 mitigation are not additive, probably because of the decreases in the inherent capacity of unit weight of BC to enhance rice yield and reduce CH4 emission, which might be caused by the adverse effects of toxic compounds contained in BC, losses of BC, and a higher degree of nutrient immobilization by BC.ConclusionsAnnual BC application at a low rate (e.g., 2 t ha-1) rather than a luxury application may be an effective and economical strategy for long-term rice yield enhancement and CH4 mitigation using BC.

Purpose Fine root decomposition plays an essential role in the nutrient cycle and energy transfer in terrestrial ecosystems, and changes in decomposition induced by nitrogen (N) deposition have become a global concern. However, patterns of fine root decomposition with N application are still scattered, and the dominant factors regulating decomposition are still controversial. Here, we aimed to explore general patterns and key drivers of decomposition in temperate forests with N application. Methods From 20 studies, we synthesized 123 records of fine root decomposition in temperate forests where N was applied. We explored the overall effect of decomposition with N application and the variation in decomposition among N application rates, N forms, fertilization condition of root growth and decomposition (FF, from fertilized to fertilized conditions, and UFF, from unfertilized to fertilized conditions), tree functional types and soil depth. The dominant factors of decomposition were identified using regression. Results Our results showed that N application decreased fine root decomposition. Specifically, decomposition decreased at the application rate of 100–150 kg N ha ‒1  yr ‒1 , under NH 4 NO 3 application, in broadleaf trees and in deep layers, attributable to the inhibited microbial enzyme activity. Decomposition decreased in FF, likely resulting from home-field advantage (HFA) effects. Multiple regressions showed that initial lignin content was the most important factor determining decomposition. Conclusion Our results suggested that inhibited microbial enzymes were associated with decreased decomposition under N application in temperate forests. Additionally, our results confirmed the importance of initial root traits, such as lignin, in regulating decomposition.

The priority problem in intensive viticulture is reducing pesticides, and fertilizers, and improving water-use efficiency. This is driven by global and EU regulatory efforts. This review, systematically examines 92 papers, focusing on progress in satellite solutions over time, and (pre)processing improvements of spatio-temporal and spectral resolution. The importance of the integration of satellites with ground truth data is highlighted. The results provide precise on-field adaptation strategies through the generation of prescription maps and variable rate application. This enhances sustainability and efficiency in vineyard management and reduces the environmental footprint of vineyard techniques. The effectiveness of different vegetation indices in capturing spatial and temporal variations in vine health, water content, chlorophyll levels, and overall vigor is discussed. The challenges in the use of satellite data in viticulture are addressed. Advanced satellite technologies provide detailed vineyard monitoring, offering insights into spatio-temporal variability, soil moisture, and vine health. These are crucial for optimizing water-use efficiency and targeted management practices. By integrating satellite data with ground-based measurements, viticulturists can enhance precision viticulture, reduce reliance on chemical interventions, and improve overall vineyard sustainability and productivity.