Variable Rate Technology Research Articles

Whole farm implications on the application of variable rate technology to every cropped field

In the last 10 years precision agriculture has evolved and it is now possible to manage cropping inputs at the sub field scale. However, the expected return generated by these management practices varies with the amount and predictability of the spatial variation in crop yield across the field and may vary from field to field across the farm. We analysed the spatial variation of crop yield from 20 fields totalling 2832 ha from a 5200 ha farm in Western Australia at the field and the sub field scale to determine the economic value of introducing variable rate management (VRT) strategies to fields across the entire farm. In this case study, 6 out of 20 fields generated an additional economic payoff of AU$15/ha when managed with VRT over uniform management. Sensitivity analysis found that the starting levels of soil fertility were an important driver of the payoff for managing a field with VRT. If starting soil fertility was low and uniform across the field, then no fields generated an economic return of more than AU$7.00/ha when managed with VRT. Other factors, including commodity price, fertiliser price, amount of variation in crop yield within the field moderately increased the value of adopting VRT across fields within farm the value of VRT increased if fertiliser budgets were constrained, particularly if the yield distribution of the field was negatively skewed. While VRT does add value to many fields across the farm, the gains are small and the technology must be implemented cheaply for it to be viable.

Key Computer Technology of Precision Fruits in Suzhou City

Precision fruits system is based on new tools and sources of information provided by modern technologies, such as the global positioning systems (GPS), remote sensing (RS), geographic information system (GIS) and variable-rate technologies. The modern technologies are integrated based on computer technology. The study introduced foreign and domestic situation of computer technology in precision fruits in detail. The key computer technology, such as the basic geographic databases and intelligent decision support system in precision fruits were analyzed, and the theory and practical application of spectral diagnosis of soil-leaf nutrient and online detecting model of microelement of fruits was emphasized in Suzhou city. The study shows that computer technology is one of the keys to establish high quality and efficiency, ecological, safety precision fruits farming techniques system of Suzhou city, and provides technical support for an increase in income of fruits farmer while decreasing in cost and pollution of fruits farming.

Critical Review of Precision Agriculture Technologies and Its Scope of Adoption in India

Precision agriculture (PA) concept was initiated for site specific crop management as a combination of positioning system technology, variable rate technology, remote sensing, yield mapping etc. to optimize th e profitability, sustainability with a reduced environmental impact. From centuries Indian farms are experiencing some sort of soft precision agriculture technology. But the challenges of free and globalized market as well as ever-increasing population with huge food grain demand create the scope of adoption of hard precision agriculture technology in Indian farms. So learning the new agricultural technology invented in developed countries and its proper modification and application according to the domestic condition is necessary. Therefore, nearly hundred research papers generated in last three decades have been critically reviewed to find the status of main six components of PA, i.e., Positioning System, Remote Sensing, Variable Rate Technology, Crop & Soil Sensing & Analysis, Yield Mapping and Information Transmission Protocol. Additionally strategies for adoption of PA in Indian agriculture are discussed.

Estimation of single leaf chlorophyll content in sugar beet using machine vision

Estimating crop nitrogen status accurately during side-dressing operations is essential for effective management of site-specific nitrogen applications. Variable rate technology (VRT) is one of the major operations in precision agriculture to reduce environmental risks and increase fertilizer use efficiency. In the present study, color image analysis was performed to estimate sugar beet leaf chlorophyll status. The experiment was carried out in a phytotron and nitrogen was applied at 6 levels to the sugar beet grown in pots. Chlorophyll level of the leaves was measured by a SPAD-502 chlorophyll meter. To estimate chlorophyll status, a neural-network model was developed based on the RGB (red, green, and blue) components of the color image captured with a conventional digital camera. The results showed that the neural network model is capable of estimating the sugar beet leaf chlorophyll with a reasonable accuracy. The coefficient of determination (R2) and mean square error (MSE) between the estimated and the measured SPAD values, which were obtained from validation tests, appeared to be 0.94 and 0.006, respectively.

An approach for precision farming under pivot irrigation system using remote sensing and GIS techniques

Abstract The current work is aimed to realizing land and water use efficiency and determining the profitability of precision farming economically and environmentally. The studied area is represented by an experimental pivot irrigation field cultivated with maize in Ismailia province, Egypt. Two field practices were carried out during the successive summer growing seasons (2008 and 2009) to study the response of maize plants single hybrid 10 (S.H.10) to traditional and precision farming practices. Traditional farming (TF) as handled by the farm workers were observed and noted carefully. On the other hand precision farming (PF) practices included field scouting, grid soil sampling, variable rate technology and its applications. After applying PF a dramatic change in management zones was noticed and three management zones (of total four) were merged to be more homogenous representing 84.3% of the pivot irrigation field. Under PF Remote Sensing and Geographic Information System techniques have played a vital role in the variable rate applications that were defined due to management zones requirements. Fertilizers were added in variable rates, so that rationalization of fertilizers saved 23.566 tonnes/experimental pivot area. Natural drainage system was improved by designing vertical holes to break down massive soil layers and to leach excessive salts. Crop water requirements were determined in variable rate according to the actual plant requirements using SEBAL model with the aid of FAO Cropwat model. Irrigation schedule of maize was adopted considering soil water retention, depletion, gross and net irrigation saving an amount of water equal to 93,718 m3 in the pivot irrigation field (153.79 acre). However costs of applying PF were much higher than TF, the economic profitability (returns-costs) achieved remarkable increase of 29.89% as a result of crop yield increment by 1000, 2100, 800 and 200 kg/acre in the management zones 1, 2, 3 and 4, respectively. Finally applying adequate amounts of fertilizers beside water control the environmental hazards was reduced to the acceptable limits.

AN ECONOMIC ANALYSIS OF VARIABLE RATE TECHNOLOGY

Variable Rate Technology (VRT) offers an opportunity to improve production efficiency by allowing input applications to fluctuate in response to spatial variations in soil characteristics and nutrient levels. Society may also benefit from reduced negative externalities, such as surface and groundwater contamination, from input applications. Using a dynamic spatial model, this study examines how the interaction among variability, spatial autocorrelation, and mean level of soil fertility affects optimal sampling density and the economic gains from VRT. VRT was found to be profitable under selected conditions, and the optimal grid size will vary with these conditions. In the case where variability and mean fertility levels are significantly high associated with low spatial autocorrelation, VRT produces greater net returns than Uniform Rate Technology (URT), even with the smallest grid size to base the input application decisions. Results also demonstrate that optimal grid size increases with increased spatial autocorrelation.

ADOPTION OF VARIABLE RATE TECHNOLOGY

Site Specific Management (SSM), which also variously referred to as Variable Rate Technology (VRT), is an emerging technology that enables producers to make more precise input application decisions based on soil and field characteristics. This study analyzes factors influencing the adoption of VRT for fertilizer application for cash grain production in Ohio. Results show that producer and field characteristics might influence the adoption decision on various SSM components differently. It also provides insight as to the sequence of adoption of SSM component technologies and how this sequence might differ for producers of differing characteristics.

Comparing high density LIDAR and medium resolution GPS generated elevation data for predicting yield stability

High density light detection and ranging (LIDAR) imaging has been shown to be able to define yield stability areas of a field for multi-cropping. Since LIDAR imaging is expensive and not widely available, it was hypothesized that medium resolution GPS elevation data which is commonly collected with variable rate technology (VRT) controllers and crop yield monitors could be used in lieu of LIDAR imaging. If proven, growers would be able to construct yield stability maps of their fields without the expense of obtaining LIDAR imaging. After substituting medium resolution GPS elevation data derived from the crop yield monitors, the procedure developed for developing a crop yield stability map was invoked and tested. The hypothesis that medium resolution GPS data could be used in lieu of LIDAR data was found to be invalid as the map generated incorrectly identified both high yield and medium yield areas of the field as low yielding areas as well as the inverse. While disappointing, high resolution GPS data from real-time kinetics (RTK) systems is yet to be tested and may offer an additional avenue to developing crop yield stability maps.

Precise Placement and Variable Rate Fertilizer Application Technologies for Horticultural Crops

Fertilizer spreaders capable of variable rate application are increasingly important for enhancing nutrient management in horticultural crops because they improve placement and increase nutrient uptake efficiency. Matching applied fertilizer to fertilizer requirements represents a significant input cost saving for the grower and a reduction in potential pollutant loading to ground and surface water. Variable rate fertilization (VRF) is a precision agriculture technology made possible by embedded high-speed computers, accurate Global Positioning System (GPS) receivers, Geographic Information Systems (GIS), remote sensing, yield or soil maps, actuators, and electronic sensors capable of measuring and even forecasting crop properties in real time. For tree crops like Florida citrus (Citrus spp.), the most important function of the VRF spreader is to detect and avoid fertilizing spaces of the orchard not occupied by trees. Treeless spaces are becoming more common in Florida as diseases such as citrus greening (Candidatus Liberibacter asiaticus) and canker (Xanthomonas axonopodis) cause the removal of thousands of trees every year. VRF works best under those conditions. Because VRF exploits crop and soil variability, it has no value in a perfectly uniform field. VRF enables smaller trees including resets to be fertilized at lower, most appropriate rates, thus minimizing any excess application. This article examines the existing knowledge on using precision agriculture and variable rate technology to keep water and nutrients in the root zone of horticultural crops, thus facilitating maximum uptake efficiency.

Evaluating the Response Time of a Rate Controller Used with a Sensor-Based, Variable Rate Application System

Technology for real-time sensor-based variable rate application equipment can involve intricate systems. A sensor system typically provides the rate-controller a set-point every second creating a challenge in terms of the response time to achieve the desired rate using existing rate-controllers, valves, and nozzles. Response time of a commercially available rate-controller was evaluated with two applicator configurations: a pulse width modulated (PWM) system with fixed orifice nozzles (PWM-applicator) and a standard system with a fast close (FC) valve and variable orifice nozzles (FC-applicator). These applicator configurations were tested with two input signals: a step input rate change common in a map based system using variable rate technology (VRT) and a simulated real-time sensor-based VRT input that updated every second. Pressure, flow rate, and controller input from the simulated sensor system were measured and recorded with a data acquisition system. The data were analyzed to determine if the applied rate correctly followed the desired set-point rate while evaluating the associated response time of the rate-controller for different valve speed and brake point settings. Results suggest that corresponding minimum response time had to be determined for each configuration for optimum performance of VRT equipment. The PWM-applicator response time with a simulated sensor input was 0.5 s and with a simulated map input was 1.5 s. The FC-applicator response time with a simulated sensor input was 0.6 s but 2.1 s for a simulated map input. Although the PWM-applicator had a slightly lower response time than the FC-applicator, flow rate and pressure were more stable with the FC-applicator and the application error was less. However, if a variable rate controller is optimized for map-based application, it will likely function adequately in a sensor-based system. Results from our study can assist in determining the spatial resolution for variable rate application using commercially available VRT equipment.

Review. Precision viticulture. Research topics, challenges and opportunities in site-specific vineyard management

Precision Viticulture (PV) is a concept that is beginning to have an impact on the wine-growing sector. Its practical implementation is dependant on various technological developments: crop sensors and yield monitors, local and remote sensors, Global Positioning Systems (GPS), VRA (Variable-Rate Application) equipment and machinery, Geographic Information Systems (GIS) and systems for data analysis and interpretation. This paper reviews a number of research lines related to PV. These areas of research have focused on four very specific fields: 1) quantification and evaluation of within-field variability, 2) delineation of zones of differential treatment at parcel level, based on the analysis and interpretation of this variability, 3) development of Variable-Rate Technologies (VRT) and, finally, 4) evaluation of the opportunities for site-specific vineyard management. Research in these fields should allow winegrowers and enologists to know and understand why yield variability exists within the same parcel, what the causes of this variability are, how the yield and its quality are interrelated and, if spatial variability exists, whether site-specific vineyard management is justifiable on a technical and economic basis.

Variable Rate Technology for Florida Citrus

AE444, a 5-page illustrated fact sheet by Reza Ehsani, Arnold Schumann, and Masoud Salyani, describes this important site-specific management component of precision agriculture which provides economic benefits to growers while reducing the application of agrochemicals. Includes references. Published by the UF Department of Agricultural and Biological Engineering, January 2009.

The Value of Variable Rate Technology: An Information‐Theoretic Approach

AbstractWe present a theoretical treatment of the economics of variable rate technology and its interplay with information. The framework facilitates description of on‐farm empirical profitability studies of variable rate nitrogen application on Illinois cornfields. We estimate site‐specific ex ante economically optimal nitrogen application rates, and the value of site‐specific information in the management of variable rate technology. We find that with site‐specific information provided free, variable rate nitrogen application would have been profitable in six of eight fields. Because private markets are unlikely to provide such information sufficiently, more public funding of long‐term, multiregion, multiyear experimentation is appropriate.

Economic benefits of variable rate technology: case studies from Australian grain farms

In this study we attempt to quantify the economic benefits of the adoption of variable rate application of fertiliser on six case study farms from the Australian wheatbelt. The farm case studies covered a range of agro-climatic regions (Mediterranean, uniform, and summer-dominant rainfall patterns), cropping systems (wheat–lupin, wheat–canola, and winter and summer crops), farm sizes (1250–5800 ha cropping program), soil types (shallow gravels to deep cracking clays), and production levels (average wheat yields from 1.8 to 3.5 t/ha). The farmers had been practising some form of variable rate technology (VRT) management of fertiliser for 2–10 years. Capital investment in VRT equipment ranged from $37 000 to $73 000, which is at the medium to high end of investment for Australian farmers, and when expressed as investment per cropped hectare it varied from $11 to $30/ha. All farmers were able to quantify benefits of VRT, ranging from $1 to $22/ha across the six farms, and a break-even analysis showed that the initial capital outlay was recovered within 2–5 years. On a per paddock basis, benefits ranged from –$28 to +$57/ha.year, and reasons for this wide range could be explained by fertiliser management practices and the degree of within-paddock yield variation. Where VRT benefits were able to be estimated across a run of seasons for a given paddock, it was noticeable that benefits, albeit diminished, still occurred in below-average yielding years. This suggests that, once zones have been defined, benefits from VRT will occur in most seasons. This study demonstrates that the participating Australian grain growers have adopted VRT systems that are profitable and recover the initial capital outlay within a few years. The use of, and benefits from, VRT technology vary farm to farm, in line with farmer preferences and circumstances.

Development of an Airborne Remote Sensing System for Crop Pest Management: System Integration and Verification

Remote sensing is being used with Global Positioning Systems, Geographic Information Systems, and variable rate technology to ultimately help farmers maximize the economic and environmental benefits of crop pest management through precision agriculture. Airborne remote sensing is flexible and versatile because fields can be flown at variable altitude depending on the spatial resolution required. Although the use of airborne hyperspectral remote sensing in agricultural research and applications has been steadily increasing in the last decade, the airborne multispectral technique is still a good source of crop, soil, or ground cover information. The MS-4100 is a multispectral camera that produces and aligns images from different bands with a built-in prism. Data can be analyzed from the composite image or individual band images. The camera system evaluated herein uses a camera control system to physically compensate for roll, pitch, and yaw and maintain the camera at vertical nadir orientation. This article describes the automated airborne multi-spectral imaging system and image processing using sample imagery to demonstrate the capability and potential of the system for crop pest management.

Advances in precision agriculture in south-eastern Australia. I. A regression methodology to simulate spatial variation in cereal yields using farmers' historical paddock yields and normalised difference vegetation index

Despite considerable interest by Australian farmers in precision agriculture (PA), its uptake has been low. Analysis of the possible financial benefits of alternative management options that are based on the underlying patterns of observed spatial and temporal yield variability in a paddock could increase farmer confidence in adopting PA. The cost and difficulty in collecting harvester yield maps have meant that spatial yield data are generally not available in Australia. This study proposes a simple, economical and easy to use approach to generate simulated yield maps by using paddock-specific relationships between satellite normalised difference vegetation index (NDVI) and the farmer’s average paddock yield records. The concept behind the approach is illustrated using a limited dataset. For each of 12 paddocks in a property where a farmer’s paddock-level yield data were available for 3–5 years, the paddock-level yields showed a close to linear relationship with paddock-level NDVI across seasons. This estimated linear relationship for each paddock was used to simulate mean yields for the paddock at the subpaddock level at which NDVI data were available. For one paddock of 167 ha, for which 4 years of harvester yield data and 6 years of NDVI data were available, the map of simulated mean yield was compared with the map of harvester mean yield. The difference between the two maps, expressed as percentage deviation from the observed mean yield, was <20% for 63% of the paddock and <40% for 78% of the paddock area. For 3 seasons when there were both harvester yield data and NDVI data, the individual season simulated yields were within 30% of the observed yields for over 70% of the paddock area in 2 of the seasons, which is comparable with spatial crop modelling results reported elsewhere. For the third season, simulated yields were within 30% of the observed yield in only 22% of the paddock, but poor seasonal conditions meant that 40% of the paddock yielded <100 kg/ha. To illustrate the type of financial analysis of alternative management options that could be undertaken using the simulated yield data, a simple economic analysis comparing uniform v. variable rate nitrogen fertiliser is reported. This indicated that the benefits of using variable rate technology varied considerably between paddocks, depending on the degree of spatial yield variability. The proposed simulated yield mapping requires greater validation with larger datasets and a wider range of sites, but potentially offers growers and land managers a rapid and cost-effective tool for the initial estimation of subpaddock yield variability. Such maps could provide growers with the information necessary to carry out on-farm testing of the potential benefits of using variable applications of agronomic inputs, and to evaluate the financial benefits of greater investment in PA technology.

Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry

In the context of precision farming, quantitative information on plant nitrogen concentration (PNC) is necessary to apply variable rate technologies of top-dressing fertilization. Radiometric measurements are useful for monitoring crop conditions and, in particular, for nitrogen/chlorophyll assessment. This work aims to quantify PNC from canopy spectra collected in the field with a hand-held spectro-radiometer. We propose a vegetation index that is able to predict PNC in rice crops through a regressive model that was calibrated and validated with data from two field campaigns carried out in Northern Italy in 2004 and 2006. The index exploits availability of hyperspectral data (numerous very narrow bands, <10 nm) that can guide the choice of spectral band combinations for PNC estimation. The most suitable bands were selected in the visible (blue/green) region of the electromagnetic spectrum where nitrogen/chlorophyll compounds play a key role in radiation absorption. The index was also shown to be least affected by leaf area index and aboveground biomass variability thus assuring the highest sensitivity to PNC ( R 2 = 0.65, *** p < 0.001). The regressive model was applied, via a spatial interpolation algorithm, to field data in order to derive, maps of PNC; these showed a high correlation with experimental design and crop conditions through the rice growing cycle. Model precision and accuracy appear suitable for detecting spatial and temporal variations in rice crops and for supporting decisions for application of variable rate technology.

On-the-go variable-rate phosphorus fertilisation based on a visible and near-infrared soil sensor

As the inherent spatial variability of soil phosphorus (P) within a field is considerable, variable-rate (VR) technology of P fertilisation should be implemented over small areas (e.g. 1 m 2 ). The objective of this study was to design and implement a soil sensor-based VR fertilisation system for on-the-go application of phosphate (P 2 O 5 ) during maize planting. An on-the-go visible (VIS) and near-infrared (NIR) soil sensor with a measurement range of 305–1711 nm was installed at the front of a planter-applicator for on-the-go measurement of soil P. A previously developed VIS–NIR model was used to predict the extractable phosphorous (P-ext) and a custom-built LabVIEW programme was developed to record soil spectra, predict soil P-ext, calculate phosphate during on-the-go measurement and provide the signal to the fertiliser applicator to adjust the application rate. Alternate plots were used for VR application and for uniform-rate (UR) treatment. The number of plant leaves and grain yield were measured as growth indices that may be influenced by P deficiency. The coefficient of variation (CV) of P-ext measured on-the-go ranged from 5% to 51% while variation of phosphate ranged from 36% to 76% over the experimental plots. The average phosphate applied on VR plots was 28.75, 1.25 kg ha −1 less than the UR (30 kg ha −1 ) recommended according to the standard soil test. The application rate of the phosphate ranged from 0 to 100 kg ha −1 in the VR plots. Lower variation in plant leaves was observed in plots with VR treatment, possibly indicating better P distribution over the VR plots. The number of plant leaves variations were 25% and 31% for VR and UR plots, respectively. However, there was no significant difference between VR and UR plots. The maize yield was significantly higher (336 kg ha −1 ) and less variable on plots that received VR treatment.

Using Spatial Analysis to Study the Values of Variable Rate Technology and Information

AbstractFor adoption of variable rate technology to increase, more knowledge of how crop yields respond to inputs is needed. As the necessary agronomic research involves approximating site‐specific yield response functions, data used inherently lend themselves to spatial analysis. We discuss the different types of spatial analyses that may be appropriate. Then we present a taxonomy for the discussion of the economics of technology and information, and use it to review studies that have contributed significantly to the literature over the past few years. We contend that longer‐term, multilocation agronomic experiments are needed for the estimation of site‐specific ex ante optimal variable input rates, and of expected profitability of variable rate technology and information.

Wavelet based multi-spectral image analysis of maize leaf chlorophyll content

With recent advancement in precision farming, the need for variable rate technology has become apparent. Variable rate technology can improve the efficiency of farm operations and lessen farm's environmental impact. To implement effective variable rate applications, it is essential to gather and process information on crop nitrogen level reliably. This research is intended to develop an image-processing method to assess crop nitrogen level based on multi-spectral images of maize plants. This method first removed unnecessary information from the image and then converted the image into a one-dimensional (1D) signal representing the reflectance of the maize plant across leaves. The obtained data was further processed using the wavelet packet transform to find specific patterns that correspond to crop nitrogen stress. To implement wavelet analysis, the 1D signal was deconstructed into packets of narrow frequency bands to find the lowest level approximations at different levels. The maximum wavelet coefficients were identified for interested signal bands and then compared to SPAD meter readings, which were used as the ground-truth corn nitrogen level. Analysis results indicated that the db4 wavelet at a level 8 deconstruction had the highest linear regression coefficient ( R 2 = 0.78) with a high correlation coefficient ( r = 0.88) for corn nitrogen levels.