Variable Fertilizer Application Research Articles

Impact of Variable Device Structural Changes on Particle Deposition Distribution in Multi-Rotor UAV

The aim of this study was to investigate the effect of structural changes in variable fertilizer application devices on the distribution of particle deposition in UAVs. With the rapid development of drone technology, particularly in particulate spreading, drones have demonstrated significant potential due to their efficiency and precision. This paper evaluates the impact of different variable adjustment modes of the device on particulate deposition distribution through drone spreading experiments and particulate deposition data analysis. In this study, device structure change is the main variable factor, and flight altitude, flight speed and ambient wind speed are single quantitative factors. Experiments were conducted by varying the structure of the device to test the detailed deposition distribution of the device under group a, b, and c structures. Experimental results indicate that by choosing different variable combinations, the spreading device can achieve various fertilizer deposition states to meet regional needs. Among all 27 variable groups, the fertilizer particle deposition data for group b1b2b3 is relatively uniform, with three-quarters of particulate deposition values being 3 g/m2 and the maximum value being 4 g/m2. However, even with a relatively uniform distribution of fertilizer particles, the coefficient of variation for group b1b2b3 remains high (36.5%), with a range of 4.5% to 41%. Under different group adjustments, the particle distribution shows the smallest variability range in group b1b2b3, with a range of 15.71–26.44% and a variability difference of 10.73%. The particle distribution shows the largest variability range in group a1a2b3, with a range of 0.78–35.06% and a variability difference of 34.28%. These research conclusions provide important guidance for the study and practice of drone spreading systems.

Spatial Chlorophyll Estimation from Rice Field using Drone-derived Spectral Indices

Background: Precision farming has significantly advanced the agricultural sector by enabling real-time canopy monitoring and crop condition evaluation, thus facilitating precise management strategies to enhance yields. This study investigated the use of drone-derived vegetation indices (VIs) for assessing spatial variability in crop conditions, offering a more cost effective and practical alternative to satellite data. Methods: The field experiment was conducted during the Kuruvai season (July - November 2023) on a short-duration rice variety CO 55. Several vegetation indices viz., BGI, CI, EVI, GNDVI, MCARI, MSAVI, NDRE and NDVI were calculated to predict chlorophyll content and correlated with the measured SPAD values. Result: The results showed that indices like MCARI, GNDVI, and NDVI had strong positive correlations with SPAD values, with MCARI exhibiting the highest correlation (R = 0.914) and an R² value of 0.836. The findings underscore the effectiveness of using drone-derived indices for precise chlorophyll estimation, which is crucial for variable rate fertilizer application in precision agriculture.

Impact of Agricultural Activities on Climate Change: A Review of Greenhouse Gas Emission Patterns in Field Crop Systems.

This review paper synthesizes the current understanding of greenhouse gas (GHG) emissions from field cropping systems. It examines the key factors influencing GHG emissions, including crop type, management practices, and soil conditions. The review highlights the variability in GHG emissions across different cropping systems. Conventional tillage systems generally emit higher levels of carbon dioxide (CO2) and nitrous oxide (N2O) than no-till or reduced tillage systems. Crop rotation, cover cropping, and residue management can significantly reduce GHG emissions by improving soil carbon sequestration and reducing nitrogen fertilizer requirements. The paper also discusses the challenges and opportunities for mitigating GHG emissions in field cropping systems. Precision agriculture techniques, such as variable rate application of fertilizers and water, can optimize crop production while minimizing environmental impacts. Agroforestry systems, which integrate trees and crops, offer the potential for carbon sequestration and reducing N2O emissions. This review provides insights into the latest research on GHG emissions from field cropping systems and identifies areas for further study. It emphasizes the importance of adopting sustainable management practices to reduce GHG emissions and enhance the environmental sustainability of agricultural systems.

Rapid detection of fertilizer information based on Raman spectroscopy and machine learning

The rapid detection of fertilizer nutrient information is a crucial element in enabling intelligent and precise variable fertilizer application. However, traditional detection methods possess limitations, such as the difficulty in quantifying multiple components and cross-contamination. In this study, a rapid detection method was proposed, leveraging Raman spectroscopy combined with machine learning, to identify five types of fertilizers: K2SO4, (CO(NH2)2, KH2PO4, KNO3, and N:P:K (15-15-15), along with their concentrations. Qualitative and quantitative models of fertilizers were constructed using three machine learning algorithms combined with five spectral preprocessing methods. Two variable selection methods were used to optimize the quantitative model. The results showed that the classification accuracy of the five fertilizer solutions obtained by random forest (RF) was 100 %. Moreover, in terms of regression, partial least squares regression (PLSR) outperformed extreme learning machine (ELM) and least squares support vector machine (LSSVM), yielding prediction Rp2 within the range of 0.9843–0.9990 and a root mean square error in the range of 0.0486–0.1691. In addition, this study evaluated the impact of different water types (deionized water, well water, and industrial transition water) on the detection of fertilizer information via Raman spectroscopy. The results showed that while different water types did not notably affect the identification of fertilizer nutrients, they did exert a pronounced effect on the quantification of concentrations. This study highlights the efficacy of combining Raman spectroscopy with machine learning in detecting fertilizer nutrients and their concentration information effectively.

Revolutionizing Agriculture: Innovative Techniques, Applications, and Future Prospects in Precision Farming

Precision agriculture (PA) represents a transformative approach to farming, employing advanced technologies to enhance productivity, efficiency, and sustainability. This review article provides an in depth analysis of the latest innovations in PA techniques, their diverse applications, and future directions. Precision agriculture is revolutionizing the agricultural landscape by integrating sophisticated tools such as GPS, remote sensing, Internet of Things (IoT), and big data analytics. These technologies enable farmers to monitor and manage variability in crop production meticulously, optimize the use of inputs, and enhance overall farm management practices. The key innovations in PA include the development and application of Geographic Information Systems (GIS) and Global Positioning Systems (GPS), which facilitate accurate mapping and variable rate technology (VRT) for site specific input management. Remote sensing technologies, encompassing both satellite imagery and UAVs (unmanned aerial vehicles), provide critical insights into crop health, soil conditions, and weather patterns, allowing for proactive and informed decision making. The integration of IoT in agriculture involves deploying sensors and connected devices to monitor soil moisture, temperature, and other environmental parameters in real time. This integration supports precision irrigation, climate monitoring, and efficient resource utilization. Big data analytics further enhances PA by processing vast amounts of data to generate actionable insights, enabling predictive analytics and decision support systems (DSS) that aid in optimizing farming operations. The article explores the applications of these advanced techniques in crop management, resource use optimization, and environmental stewardship. Examples include variable rate application of fertilizers, precision irrigation systems, and automated machinery such as drones and robotic harvesters. These innovations lead to significant improvements in crop yields, resource efficiency, and sustainability. Moreover, the review addresses the challenges associated with the adoption and implementation of PA technologies. These challenges include data management complexities, high initial costs, limited accessibility, and the need for technical expertise. The article discusses potential solutions such as cloud computing, machine learning algorithms, government subsidies, collaborative models, and comprehensive training programs to mitigate these barriers, the review highlights the integration of advanced technologies like artificial intelligence (AI), blockchain, and enhanced connectivity through 5G networks as pivotal developments that will further revolutionize precision agriculture. AI and machine learning will enhance predictive modeling and automated decision making, while blockchain will ensure transparency and traceability in supply chains. Enhanced connectivity will facilitate real time monitoring and collaborative platforms, driving efficiency and innovation in farming practices.

基于土壤养分检测的变量施肥系统的设计与试验

In order to solve the problems of low correlation between variable fertilizer application system and soil nutrient content detection and insufficient real-time performance, a variable fertilizer application system based on real-time soil nutrient content detection was developed. This paper describes the structure, working principle and design of key components of the soil information acquisition and fertilizer application system. It includes the simulation and analysis of fertilizer application using the discrete element method and the selection of curved blade fertilizer application discs. The system uses STM32F429IGT6 microcontroller and ROS higher-level computer for decision making. The device detects soil nutrients in real time, adjusts the fertilizer motor speed accordingly, and runs autonomously along the planned path. The decision coefficient R^2 between the fertilizer application rate and the speed of the fertilizer application wheel is not less than 0.97, and the relative error between the actual fertilizer application rate and the theoretical fertilizer application rate is up to 5.91%, with the maximum value of the coefficient of variation (CV) of 10.18%. The indoor bench test shows that the relative error between the actual fertilizer application rate and the target fertilizer application rate within a single operating grid is up to 6.2%, with the maximum value of CV being 6.64%. The field test in the orchard showed that the maximum relative error between the actual fertilizer application and the target fertilizer application in a single operation grid was 6.3%, and the maximum value of CV was 12.34%, and the fertilizer application was completed in the operation grid, which demonstrated that the device was able to realize real-time and accurate variable fertilizer application according to the soil nutrient information.

Design and Development of Variable Rate Metering System for Fertilizer Application

A variable rate fertilizer metering mechanism was designed by changing the speed of the feed shaft for use in variable rate fertilizer applicator. A micro-controller unit programmed with a Pulse Width Modulation (PWM) motor driver was used to run the feed shaft for varying speeds. Two types of fluted rollers (straight and helical flute) were used with varying number of flutes having same volume for each fluted roller. No significant difference in discharge rate between helical and straight fluted roller was observed with varying number of flutes (6, 8, 10, and 12). However the discharge rate of SSP fertilizer was significantly higher than that for DAP. Also, significant difference was observed in applied torque and power requirement for straight and helical flute.

Estimation of Sensor-based site specific variable rate fertilizer application for maize (Zea mays L.) crop

Optical spectrometry sensors in crops offer a remarkable technological breakthrough in the field of variable-rate nitrogen fertilization. A field study was conducted during rainy (kharif) season of 2021 at the research farm of the Agricultural Engineering College and Research Institute Tamil Nadu Agricultural University Coimbatore to estimate maize crop nitrogen (N), Normalized Difference Vegetation Index (NDVI) value and chlorophyll content in hybrid maize COH (M) 8. Fertilizers were administered to the plots following the recommendations (250:75:75 kg NPK ha-1) given under Soil Test Crop Response, with a goal yield of 9t ha-1 predicted based on the initial soil available N, P, and K values. The experimental findings revealed a significant impact of nitrogen rate (P<0.001) on the percentage of nitrogen content in the leaves (% N leaf content). Additionally, there was a decrease in maize leaf chlorophyll content index over time, with ranges of 32.96 to 50.57, 28.78 to 41.78, 24.81 to 35.86, 22.12 to 28.54, and 14.34 to 20.56. On the contrary, the NDVI experienced an increase throughout the season, with ranges of 0.32 to 0.49, 0.30 to 0.55, 0.28 to 0.66, 0.46 to 0.88, and 0.56 to 0.84. The study will help foster sustainability within modern intensive farming practices by emphasizing the importance of reducing environmental pollution caused by applying Sensor-based site-specific nitrogen fertilizer for maize crop.

Understanding farmer views of precision agriculture profitability in the U.S. Midwest

Precision Agriculture (PA) technologies are well known to be useful in addressing field heterogeneities and enabling informed site-specific management decisions. While profitability is the foremost factor considered by farmers when making PA adoption decisions, information in this regard is lacking from the farmers' perspective. This paper analyzed 1119 farmer responses from a 2021 survey conducted in four states along the western margins of the U.S. Midwest. Our findings show that while most (around 60%) non-adopters indicate that they are unaware of PA profit change, adopters are likely to rate a major profit increase. About two thirds of adopters rated at least a 5% increase in profitability towards variable rate (VR) fertilizer application (72%), VR seed application (68%), and automatic section control (66%). We modeled farmers' profit change subsequent to PA adoptions. Our regression results demonstrate that the profits from PA usage increase over time and that use of conservation practices likely influences PA profitability in a positive way. As soil quality and weather factors also affect profit ratings, it would be beneficial to compare and demonstrate profitability potential of various PA technologies on a regional basis and tailor the promotion efforts to farmers most likely to benefit from them.

Potential of existing strategies to reduce net anthropogenic inputs of phosphorus to land in the United States

Improving phosphorus (P) management is important for both ecosystem protection and avoiding mineable P scarcity. In order to inform the development of impactful solutions to both of these issues, we assessed the potential of several specific management strategies to reduce demand for new mined P in fertilizers and supplements for livestock, thereby reducing net P inputs to land. The strategies assessed were variable rate fertilizer (VRF) application, improvements to P digestibility for livestock, efficient utilization of manure and wastewater treatment (WWT) P, and elimination of avoidable domestic food waste. The potential of these strategies to reduce net anthropogenic P inputs was assessed at the county level for the coterminous US using the commodity-specific net anthropogenic P and nitrogen inputs (CSNAPNI) model. The largest contributions toward eliminating NAPI in the US can come from efficient manure utilization either at national (30%–50% NAPI reduction) or county-level (21%–30% NAPI reduction). However, widespread adoption of VRF (10%–41% NAPI reduction), and all other strategies considered (5% or greater NAPI reductions each) could make significant contributions. In combinations of strategies that included VRF or P digestibility improvements, negative feedbacks occurred. VRF reduced demand for fertilizer, thereby reducing the potential for efficient manure and WWT P utilization at the county-level. P digestibility improvements in poultry and swine diets reduced the expected production of recoverable manure P by 36%, decreasing the total manure P that could be used to replace mined P fertilizer. However, P digestibility improvements also reduced county-level excess manure P by 25%. Prior studies have focused on quantifying P inputs or the potential of in-situ best management practices to reduce losses to water, but strategies to reduce P inputs are understudied.

Variable rate fertilizer application technology for nutrient management: A review

Variable rate fertilizer application technology for nutrient management: A review

Efficiency analysis and evaluation of centrifugal variable-rate fertilizer spreading based on real-time spectral information on rice

Investigations regarding the use of centrifugal variable-rate fertilizer spreaders and their impact on agriculture production has become increasingly important for determining the effects and economic benefits of precision agriculture variable-rate fertilizer technology applied in the rice-and-wheat rotation areas of the middle and lower reaches of the Yangtze River in China. This study examines a self-developed centrifugal variable-rate fertilizer spreader based on real-time growth information of rice and wheat focusing on rice variety Nanjing 9108 as its research object. Field tests of variable-rate fertilizer application (compound fertilizer) were conducted in the Dongtai rice planting base, Jiangsu Province. Different areas were set up for artificial fertilizer spreading, traditional empirical balanced spreading, and real-time variable-rate spreading. The fertilizer application rates, rice growths, and yields of these fertilizer spreading methods for three consecutive years were compared and analyzed. Furthermore, the operational effectiveness of centrifugal variable-rate spreading was evaluated via partial budget analysis. The experimental results showed that the spreading application rate for the real-time variable-rate fertilization area decreased year by year by approximately 47.64 kg/hm2, whereas the application rate per unit area was reduced by approximately 15.88 %, compared with those for the traditional empirical balanced fertilization area. After the application of topdressing tillering fertilizer, rice growth in the real-time variable-rate fertilization area was better than in the others, whereas the spatial difference in its population structure was the lowest. There were differences in rice yield among the experimental areas: the average yield of the variable-rate fertilization area was 8996.70 kg/hm2, which was 5.93 % higher than that of the traditional empirical balanced fertilization area. According to the operational effectiveness analysis of real-time variable-rate fertilizer application in rice production, its fertilizer cost was only 504.72 RMB/hm2, whereas its yield profit was 17993.40 RMB/hm2. Thus, the fertilizer cost was reduced by 95.28 RMB/hm2, whereas the yield profit was increased by 1007.62 RMB/hm2, compared with those of the traditional empirical balanced fertilizer application. To sum up, this investigation verified that the newly developed centrifugal variable-rate fertilizer spreader, using real-time variable-rate fertilizer, can save on fertilizer and reduce its application, improve the population structure and spatial difference in crop growth, help increase crop yield and degree of balance, and produce economic, ecological, and social benefits. This study can provide a theoretical reference for promoting the pilot application of variable-rate fertilization technology in the rice-and-wheat rotation areas of the middle and lower reaches of the Yangtze River.

Research on Precise Fertilization Method of Rice Tillering Stage Based on UAV Hyperspectral Remote Sensing Prescription Map

Tillering fertilization is an important part of field management in rice production. As the first peak fertilizer requirement period of rice, tillering fertilization directly affects the number of tillers and the growth of rice in the middle and late stages. In order to investigate a method of constructing an accurate fertilizer prescription map in the tillering stage using an unmanned aerial vehicle (UAV) remote sensing nitrogen demand diagnosis and reduce the amount of chemical fertilizer while ensuring the rice yield, this study realized the diagnosis of the rice nitrogen nutrient demand using UAV hyperspectral remote sensing during the tilling stage fertilization window. The results showed that the fertilizer amount was determined using the characteristic waveband and remote sensing. The results showed that five rice hyperspectral variables were extracted in the range of 450–950 nm by the feature band selection and feature extraction for the inversion of rice nitrogen content, and the inversion model of rice nitrogen content constructed by the whale-optimized extreme learning machine (WOA-ELM) was better than that constructed by the whale-optimized extreme learning machine (ELM). The model coefficient of determination was 0.899 and the prescription map variable fertilizer application method based on the nitrogen content inversion results reduced the nitrogen fertilizer by 23.21%. The results of the study can provide data and a model basis for precise variable fertilizer tracking by agricultural drones in the cold rice tillering stage.

Performance Assessment of a Sensor-Based Variable-Rate Real-Time Fertilizer Applicator for Rice Crop

Variable-rate technology (VRT) may reduce input costs, increase crop productivity and quality, and help to protect the environment. The present study was conducted to evaluate the performance of a variable-rate fertilizer applicator for rice (Oryza sativa L.). Three replications were conducted, each of which was divided into four plots. Field performance of the system was assessed at different nitrogen levels (N1 to N4, i.e., 75, 125, 175, 225 kg ha−1), growth stages (tillering, panicle initiation, heading), and heights (40, 60, 80, 100 cm) of the sensor from the crop canopy. Fertilizer rate was at minimum 12.59 kg ha−1 at 10 rpm of drive-shaft rotational speed and at maximum 50.41 kg ha−1 at 40 rpm. The system response time was within the range of 3.53 to 4.93 s, with overall error ranging between 0.83% to 4.92%. Across different growth stages, when fertilizer rate was increased from N1 to N4, NDVI increased from 0.49 to 0.69. Hence, drive-shaft rotational speed is decreased from 25 to 7 rpm to shift the application rate from 30.83 to 9.15 kg ha−1. There was a 45% reduction in total fertilizer rate applied by the system, with respect to the recommended rate.

Single-Neuron PID UAV Variable Fertilizer Application Control System Based on a Weighted Coefficient Learning Correction

Agricultural unmanned aerial vehicles (UAVs), which are a new type of fertilizer application technology, have been rapidly developed internationally. This study combines the agronomic characteristics of rice fertilization with weighted coefficient learning-modified single-neuron adaptive proportional–integral–differential (PID) control technology to study and design an aerial real-time variable fertilizer application control system that is suitable for rice field operations in northern China. The nitrogen deficiency at the target plot is obtained from a map based on a fertilizer prescription map, and the amount of fertilizer is calculated by a variable fertilizer application algorithm. The advantages and disadvantages of the two control algorithms are analyzed by a MATLAB simulation in an indoor test, which is integrated into the spreading system to test the effect of actual spreading. A three-factor, three-level orthogonal test of fertilizer-spreading performance is designed for an outdoor test, and the coefficient of variation of particle distribution Cv (a) as well as the relative error of fertilizer application λ (b) are the evaluation indices. The spreading performance of the spreading system is the best and can effectively achieve accurate variable fertilizer application when the baffle opening is 4%, spreading disc speed is 600 r/min, and flight height is 2 m, with a and b of evaluation indexes of 11.98% and 7.02%, respectively. The control error of the spreading volume is 7.30%, and the monitoring error of the speed measurement module is less than 30 r/min. The results show that the centrifugal variable fertilizer spreader improves the uniformity of fertilizer spreading and the accuracy of fertilizer application, which enhances the spreading performance of the centrifugal variable fertilizer spreader.

Calibration and Testing of Discrete Element Simulation Parameters for Urea Particles

The lack of accurate simulation model parameters in the optimization design process of variable fertilizer application devices has resulted in large errors between simulation and theoretical calculation results, which has restricted the development of variable fertilizer application devices to a certain extent. Additionally, there are few scholars studying urea granules, so many parameters of urea granular fertilizer cannot be directly obtained from the literature. The aim of this study is to calibrate a set of simulation parameters by combining physical and simulation tests. In this study, intrinsic parameters were systematically determined, including the particle size, particle density, elastic modulus, Poisson’s ratio and their static friction coefficients, rolling friction coefficients and restitution coefficients of urea particles. By performing the urea particle stacking test, the static friction coefficient between urea particles was calibrated to 0.27, and the rolling friction coefficient between particles was 0.11. To check the reliability of the calibration parameters, the simulation and physical tests of the repose angle and bulk density of urea particles were compared, and the results show that the relative error of repose angles and bulk density of urea particles was 0.78% and 1.19%, respectively. Through the simulation of the mechanical variable fertilizer discharger and the comparison test of the benchtop fertilizer discharging performance, the maximum relative error between the simulation and physical test fertilizer discharge is 3.69% when the working length of the outer sheave is 25 mm; the maximum relative error between the simulation and physical test fertilizer discharge is 3.39% when the working length is 35 mm; the maximum relative error between the simulation and physical test fertilizer discharge is 6.86% when the working length is 45 mm; the maximum relative error between the simulation and physical test fertilizer discharge is 4.95% when the working length is 55 mm. The maximum relative error between the simulated and physical test fertilizer discharge was 6.86% at 45 mm opening and 4.95% at 55 mm opening, and the results show that the urea particle calibration parameters are reliable. The results of this study can provide a theoretical reference for the optimization design and simulation study of variable fertilizer application devices.

Feasibility of variable rate application of diammonium phosphate fertilizer to wheat crop under center pivot irrigation system

A study was conducted, on a 30 ha wheat field under a solar energy powered center pivot irrigation system in a commercial farm located 400 km north of Khartoum, Sudan, to evaluate the feasibility of variable rate fertilizer application of Diammonium Phosphate (DAP) on wheat crop based on variable soil phosphorus content. Soil phosphorus content was divided into three categories (low: 3.75 to 4.50 ppm, medium: 4.51 to 5.25 ppm and high: 5.26 to 6.00 ppm) and a GIS soil phosphorus content map of the experimental field was generated. Three variable application rates (200 kg ha−1, 160 kg ha−1 and 120 kg ha−1) of granular DAP fertilizer were determined to fit the low, medium and high soil phosphorus contents, respectively. The the DAP fertilizer rate of 200 kg ha−1 was the rate practiced for wheat production in the experimental farm.The normalized Difference Vegetation Index (NDVI), measured at different wheat growth stages using sentinel-2 satellite images, and wheat grain yield were used to evaluate the response of wheat crop to the variable DAP fertilizer application rates. Excluding the tillering stage, the results showed significant differences in the NDVI values among different soil phosphorus levels and DAP fertilizer application rates at other growth stages, including stem elongation, grain filling and maturity stages. Moreover, wheat yield results showed significant differences among different soil phosphorus contents (P > F = 0.0001) and DAP fertilizer application rates (P > F = 0.0457). On the average, the highest yield of 2.449 t ha−1 was recorded in the field areas treated with the high DAP fertilizer application rate (200 kg ha−1), where the second highest yield of 2.441 t ha−1 was observed in field areas under the medium DAP fertilizer application rate (160 kg ha−1); however, no significant differences between these two yield values. Based on these results, the total savings of the DAP fertilizer was estimated to be 792 kg (equivalent to 475.2 $) in the experimental field (30 ha), only when the medium DAP fertilizer rate (160 kg ha−1) was used in the medium and high soil phosphorus zones, saving 15.84 $ ha−1 without affecting production.

Investigation of the Influencing Factors of Fertilizer Dropping Time for a Variable-rate Fertilizer Applicator

HighlightsThe influencing factors of the fertilizer dropping time are determined by simulation.The relationship between the influencing factors and the fertilizer dropping time is explored on the VRF applicator.A new method is established to calculate the fertilizer dropping time.Abstract. Lag time is one of the main factors that affect the accuracy of the variable rate fertilizer (VRF) applicator. The key to correcting the impact of the lag time is to determine its influencing factors. This article focuses on the fertilizer dropping time, which is a part of the lag time, and hypothesizes that the rotational speed of the fluted roller, working length of the fluted roller, number of fertilizer particles, and the length of the fertilizer tube may affect the fertilizer dropping time. First, taking advantage of the simple and convenient setting of the working parameters and conditions of the simulation software, different working parameters were set by the EDEM software for simulation, and the simulation results were analyzed to determine that the rotational speed of the fluted roller and the length of the fertilizer tube are the main influencing factors of the fertilizer dropping time. Second, to explore the relationship between the two factors and the fertilizer dropping time in the actual work, experiments were performed on the VRF applicator. The experimental results are analyzed by ANOVA, and the analysis results show that: the correlation coefficient R2 between the rotational speed of the fluted roller and fertilizer dropping time is greater than 0.95, and there is a linear relationship between the factor and fertilizer dropping time; the fertilizer dropping time increases with increasing the length of the fertilizer tube. Finally, the rotation speed-the length of the fertilizer tube-fertilizer dropping time model was established through the multiple regression analysis. With the model, the fertilizer dropping time was accurately calculated according to the rotational speed of the fluted roller and the length of the fertilizer tube. The accuracy of the model is greater than 85%, which helps to calculate the fertilizer dropping time. This study helps to correct the lag distance by sending instructions in advance and improving the accuracy of the VRF applicator. Keywords: Fertilizer dropping time, Fertilizer tube, Rotation speed, VRF.

РАЗРАБОТКА ЦЕНТРОБЕЖНОГО РАБОЧЕГО ОРГАНА РАЗБРАСЫВАТЕЛЯ МИНЕРАЛЬНЫХ УДОБРЕНИЙ

In variable-rate application of solid mineral fertilizers (SMF), working units of centrifugal fertilizer distributors can regulate precisely the application rate and evenly distribute pellets over the fi eld. To determine the most rational parameters and modes of a solid fertilizer distributor, infl uencing the fl ight path of pellets and the uniformity of their distribution over the fi eld, the authors carried out theoretical and experimental research of a centrifugal disc of a solid fertilizer distributor equipped with a rotary acceleration chamber and a set of exchangeable U-shaped blades. The authors describe the infl uence of the blade length on the trajectory and the fl ight distance of the fertilizer pellets as well as the infl uence of the rotation of the dispersal chamber outlet window on the fertilizer distribution pattern. The experiment on determining aerodynamic properties of the nitroammonium phosphate pellets (60:60:60) was carried out using the developed laboratory bench of the solid fertilizer distributor. The experiment allowed determining the physical parameters of pellets infl uencing the range and trajectory of their fl ight - the winglet ratio and the critical speed. It was found that the rotation displacement of the dispersal chamber outlet window of the spreading disc leads to the displacement of the intensive coverage zone in the direction of the window rotation. This makes it possible to regulate the intensity and has a direct impact on the distribution zone of solid mineral fertilizers. The paper justifi es the most rational design of the spreading disc. The research proved that the greatest uniformity of solid mineral fertilizer spreading is observed when using a disk with eight paired coaxially located blades with a length of 300, 250, 200, and 100 mm.

Precision Agricultural Technologies for enhancing crop productivity: A way forward to Sri Lankan Agriculture

Precision agriculture (PA) is an information-based production technology that manages spatial and temporal variability within a farming system to optimize its productivity and profitability while ensuring the sustainability of land resources. Today, several sophisticated technologies such as robotics, wireless sensor networks (WSN), aerial images, a global positioning system (GPS), global navigation satellite system (GNSS), smart mobile devices, internet of things (IoT), variable rate application (VRA), weather modelling, radio-frequency identification (RFI) are greeted with PA at a global scale. An exponentially increasing trend in adoption can be seen in developed countries such as the USA, Canada, Australia, and European countries, but to a limited extent in some developing countries. The degree of adoption of PA varies on economic, social, and geographic factors such as the scale of production, input cost, and features of the technology. Developing economies like Sri Lanka, where small-scale food crop agriculture is dominating, have the potential to benefit from precision agricultural technologies (PATs) to a greater extent. Relatively low-cost but effective PATs that would fit well with small-farm production units are emerging globally. Providing small farming units with the correct tools and greater control of the production process would support such farming communities, unlocking their potential and meeting the ever-increasing national and global food demand. Land laser levelling, real-time variable-rate fertilizer and pesticide application, mechanical harvesting and low-cost IoT-based crop management systems for protected agriculture are the most promising PATs that have great potential in Sri Lanka. This review presents a global overview of PA technologies for enhancing food crop production and their benefits, the adoption of PA technologies by different countries and the constraints, and the role of PA in Sri Lankan Agriculture, past and present. Finally, the synthesis and way forward.