Coffee production and marketing is one of the main global commercial activities, but crop yields depend on several factors, among which plant health. The objective of this study was to evaluate the efficiency of spray droplet deposition in coffee crops grown in a mountain region, associated to the efficacy of the control of fungal diseases. The application efficiency, using an unmanned aerial vehicle (UAV), and the efficacy of the products applied were tested. Water-sensitive paper tags were used to analyze the application efficiency; agronomic efficiency, vegetative vigor, yield, and physiological parameters were used to determine the fungicide efficacy. Droplet coverage in the upper canopy layer using a pneumatic sprayer (28.70%) was 4.11-fold higher than that found in the same layer for application using a UAV (6.98%) at the rate of 15 L ha⁻¹. The highest droplet depositions by using a UAV were found for the rate of 15 L ha⁻¹: 1.60, 1.04, and 0.43 µL cm⁻² in the upper, middle, and lower layers, respectively; the deposition in the upper layer with application using a pneumatic sprayer was 42.67 µL cm⁻², and therefore, a 26.7-fold higher deposition. The results denote that the control of fungal diseases through fungicide applications using a UAV is efficient for mountain coffee crops.

Adjuvants alter the physical–chemical properties of pesticide formulations, influencing either the droplet size or drift phenomenon. Selecting the appropriate adjuvant and understanding its characteristics can contribute to the efficiency of Plant Protection Product (PPP) application. This reduces drift losses and promotes better deposition on the crop. The objective of this study was to evaluate the effects of four commercial adjuvants based on mineral oil (Agefix and Assist), vegetable oil (Aureo), and polymer (BREAK-THRU) on the physical–chemical properties (surface tension, contact angle, volumetric mass, electrical conductivity, and pH), droplet size, and drift, using pure water as the control treatment (no adjuvant). Surface tension and contact angle were measured with a DSA30 droplet shape analyzer, while droplet size measurements were determined through a laser diffraction particle analyzer (Malvern Spraytec), using a single flat fan spray nozzle (AXI 110 03) operating at 0.3 MPa. Drift reduction potential was evaluated inside a wind tunnel with an air speed of 2 m s−1. All adjuvants reduced surface tension and contact angle compared to water. volumetric median diameter (VMD) increased for Aureo, Assist, and Agefix, generating coarse, medium, and medium droplets, respectively, while BREAK-THRU formed fine droplets, similar to those generated by water. Aureo had the greatest reduction in Relative Span Factor (RSF), with a reduction of 30.3%. Overall, Aureo, Assist, and Agefix adjuvants significantly reduced the percentage of droplets 500 µm. Drift reduction potential was achieved for all adjuvants, with Aureo showing the highest reduction of 59.35%. The study confirms that selecting the appropriate adjuvant can improve PPP application and promote environmental sustainability in agricultural practices.

Weather conditions and sprayer operating parameters influence spray quality. Unmanned aerial vehicles are considered a modern, useful, and very efficient technological tool in the application of pesticides, as they carry out punctual spraying, and reduce environmental and public health problems. The objective of this study was to characterize the spraying quality carried out with an unmanned aerial vehicle as a function of flight height and target position in a coffee plantation in a mountainous region. Three flight heights (2.5, 3.0, and 4.0 m) were used, and the targets were placed at the top and bottom of the plant. For each plant, six water sensitive papers were placed on top of the plant and six were placed at the bottom. CIR 1.5 software was applied to determine the coverage percentage, drop density, volume median diameter, volumetric diameter corresponding to 10 and 90%, numerical median diameter, and relative amplitude. The results showed that the flight height only influenced the parameters of the volumetric diameter corresponding to 10% of the volume, numerical median diameter, and coverage percentage. The target position on the canopy influenced all the evaluated spraying parameters. In mountainous coffee plantations, the spraying system using unmanned aerial vehicle spraying is more efficient for the lower part of the plant.

Spray droplet diameters play a key role in the field of liquid plant protection product (PPP) application technology. However, the availability of various measurement techniques, each with its unique operating principles for evaluating droplet size spectra, can lead to different interpretations of spray characteristics. Therefore, in this study, four measurement techniques—Liquid Immersion (LI), Laser Diffraction (LD), Phase Doppler Particle Analysis (PDPA), and Shadowgraphy (SG)—were utilized to evaluate the droplet size distribution of agricultural spray nozzles. Additionally, PDPA and SG were used to assess the average velocity of spray droplets. Experiments were conducted in three different laboratories with the main aim of comparing results obtained with various types of equipment utilized under ordinary practical conditions. Spraying tests were carried out using three flat fan nozzles and an air-induction flat fan nozzle. As a general trend, the lowest values for droplet diameters were measured using the Laser Diffraction technique, followed by Shadowgraphy. The PDPA technique provided the highest values for mean diameters (D₁₀, D₂₀, and D₃₀) and the numeric median diameter (Dn_0.5), whereas the Liquid Immersion method yielded the highest values for the Sauter mean diameter (D₃₂) and volumetric diameters (Dv_0.1, Dv_0.5, and Dv_0.9). Importantly, all measurement techniques were able to discriminate the four nozzles based on their Dv_0.5 diameter. Average droplet velocities showed a similar pattern across the four nozzles with the PDPA and the SG measurement techniques. The differences in diameter values observed with the four measurement techniques underline the necessity of always including reference nozzles in spray quality assessments to base classifications on relative rather than absolute values.

The use of unmanned aerial vehicles (UAVs) in the agricultural and forestry sectors has constantly evolved due to its great versatility and applicability in the field. In this sense, this study provided a statistical overview of studies on the use of UAVs in agricultural and forestry through a bibliometric and scientometric analysis. For that, a research was carried out on the Scopus platform using the terms UAV, UAS, drone, and RPA, together with “agricult*” or “forest* or livestock”. Only manuscripts published in English and from January 2000 to December 2020 were selected. The VOSviewer software was used for the analyses. The USA and China were responsible for more than 38% of the publications worldwide. Furthermore, about 50% of the countries in the world showed some scientific record of the use of UAVs in agricultural and forestry studies. The term UAS was more used until 2016, while UAV was more mentioned between 2017 and 2018. Conversely, drone was more endorsed from 2019. The constant increase in scientific production reported in the research and the evolution of the co-occurrence of keywords corroborated two ideas: i) the use of UAVs is still undergoing transformations and is directly related to the advancement of technology included in these equipments; and ii) studies are still not enough to explore all the applicability of the UAVs in agriculture, livestock and forestry.

In this study, we evaluated the spatial variability in droplet deposition in herbicide applications using a remotely piloted aircraft (RPA) in pasture areas. The investigation was conducted in a square grid (50.0 m × 50.0 m), with 121 sampling points, at two operational flight heights (3.0 and 4.0 m). Droplet deposition was quantified using the fluorescent dye rhodamine B, and the droplet spectrum was characterised using water-sensitive paper tags. Geostatistical analysis was implemented to characterise spatial dependence, complemented by multivariate statistical analysis. Droplet deposition ranged from 1.01 to 9.02 and 1.10–6.10 μL cm⁻² at 3.0 and 4.0 m flight heights, respectively, with the coefficients of variation between 19.72 and 23.06% for droplet spectrum parameters. All droplet spectrum parameters exhibited a moderate to strong spatial dependence (relative nugget effect ≤75%) and a predominance of adjustment to the exponential model, with spatial dependence indices ranging from 12.55 to 47.49% between the two flight heights. Significant positive correlations were observed between droplet deposition and droplet spectrum parameters (r = 0.60–0.79 at 3.0 m; r = 0.37–0.66 at 4.0 m), with the correlation magnitude decreasing as the operational flight height increased. Cross-validation indices demonstrated acceptable accuracy in spatial prediction, with a mean estimation error ranging from −0.030 to 0.044 and a root mean square error ranging from 0.81 to 2.25 across parameters and flight heights. Principal component analysis explained 99.14 and 85.72% of the total variation at 3.0 and 4.0 m flight heights, respectively. The methodological integration of geostatistics and multivariate statistics provides a comprehensive understanding of the spatial variability in droplet deposition, with relevant implications for the optimisation of phytosanitary applications performed using RPAs.