Site-specific Variable Rate Research Articles

Spatiotemporal Modeling of Soil Water Dynamics for Site-Specific Variable Rate Irrigation in Maize

This study aimed to simulate dynamic irrigation management zones (MZs) in two maize fields for a variable rate hose reel fertigation machine (VRFM) with a four-section boom control. Soil moisture content was measured from nine and four soil moisture sensors in Field 1 (8.2 ha) and Field 2 (2.5 ha), respectively, on different dates during the 2022 crop season. Three and five MZs scenarios were simulated per irrigation and the theoretical maps were processed for implementation. The application maps fitted to the VRFM showed significant spatiotemporal variations in irrigation requirements. For instance, in Field 1, 3-MZ modelling showed that the areas requiring high (H), medium (M), and low (L)-level irrigation on 21 July were 1.60, 4.84, and 1.85 ha, respectively, even though the farmer applied uniform rate over the whole field. H-level sub-areas ranged between 1.22 ha (25 July) and 3.25 ha (7 July), showing a coefficient of variation (CV) of 43.32% for the three MZs, whereas H-level sub-areas for the five MZs varied from 0.41 ha (2 July) to 1.49 ha (7 July) with a CV value of 48.84%. High levels of within-field variability can be addressed using precise and dynamic irrigation MZs fitted to the irrigation technology used.

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.

Position Accuracy Assessment of a UAV-Mounted Sequoia+ Multispectral Camera Using a Robotic Total Station

Remote sensing data in agriculture that are originating from unmanned aerial vehicles (UAV)-mounted multispectral cameras offer substantial information in assessing crop status, as well as in developing prescription maps for site-specific variable rate applications. The position accuracy of the multispectral imagery plays an important role in the quality of the final prescription maps and how well the latter correspond to the specific spatial characteristics. Although software products and developed algorithms are important in offering position corrections, they are time- and cost-intensive. The paper presents a methodology to assess the accuracy of the imagery obtained by using a mounted target prism on the UAV, which is tracked by a ground-based total station. A Parrot Sequoia+ multispectral camera was used that is widely utilized in agriculture-related remote sensing applications. Two sets of experiments were performed following routes that go along the north–south and east–west axes, while the cross-track error was calculated for all three planes, but also three-dimensional (3D) space. From the results, it was indicated that the camera’s D-GNSS receiver can offer imagery with a 3D position accuracy of up to 3.79 m, while the accuracy in the horizontal plane is higher compared to the vertical ones.

Precision Agroecology

In response to global calls for sustainable food production, we identify two diverging paradigms to address the future of agriculture. We explore the possibility of uniting these two seemingly diverging paradigms of production-oriented and ecologically oriented agriculture in the form of precision agroecology. Merging precision agriculture technology and agroecological principles offers a unique array of solutions driven by data collection, experimentation, and decision support tools. We show how the synthesis of precision technology and agroecological principles results in a new agriculture that can be transformative by (1) reducing inputs with optimized prescriptions, (2) substituting sustainable inputs by using site-specific variable rate technology, (3) incorporating beneficial biodiversity into agroecosystems with precision conservation technology, (4) reconnecting producers and consumers through value-based food chains, and (5) building a just and equitable global food system informed by data-driven food policy. As a result, precision agroecology provides a unique opportunity to synthesize traditional knowledge and novel technology to transform food systems. In doing so, precision agroecology can offer solutions to agriculture’s biggest challenges in achieving sustainability in a major state of global change.

Direct prediction of site-specific lime requirement of arable fields using the base neutralizing capacity and a multi-sensor platform for on-the-go soil mapping

Liming agricultural fields is necessary for counteracting soil acidity and is one of the oldest operations in soil fertility management. However, the best management practice for liming in Germany only insufficiently considers within-field soil variability. Thus, a site-specific variable rate liming strategy was developed and tested on nine agricultural fields in a quaternary landscape of north-east Germany. It is based on the use of a proximal soil sensing module using potentiometric, geoelectric and optical sensors that have been found to be proxies for soil pH, texture and soil organic matter (SOM), which are the most relevant lime requirement (LR) affecting soil parameters. These were compared to laboratory LR analysis of reference soil samples using the soil’s base neutralizing capacity (BNC). Sensor data fusion utilizing stepwise multi-variate linear regression (MLR) analysis was used to predict BNC-based LR (LRBNC) for each field. The MLR models achieved high adjusted R2 values between 0.70 and 0.91 and low RMSE values from 65 to 204 kg CaCO3 ha−1. In comparison to univariate modeling, MLR models improved prediction by 3 to 27% with 9% improvement on average. The relative importance of covariates in the field-specific prediction models were quantified by computing standardized regression coefficients (SRC). The importance of covariates varied between fields, which emphasizes the necessity of a field-specific calibration of proximal sensor data. However, soil pH was the most important parameter for LR determination of the soils studied. Geostatistical semivariance analysis revealed differences between fields in the spatial variability of LRBNC. The sill-to-range ratio (SRR) was used to quantify and compare spatial LRBNC variability of the nine test fields. Finally, high resolution LR maps were generated. The BNC-based LR method also produces negative LR values for soil samples with pH values above which lime is required. Hence, the LR maps additionally provide an estimate on the quantity of chemically acidifying fertilizers that can be applied to obtain an optimal soil pH value.

Potential Water Conservation Using Site-Specific Variable Rate Irrigation

Abstract. Site-specific variable-rate irrigation (VRI) systems can be used to spatially manage irrigation within sub-field-sized zones and optimize spatial water use efficiency. The goal of the research is to provide farmers and consultants a tool to evaluate the potential benefits of implementing VRI. The specific objective of this research is to evaluate the potential water savings using VRI management compared with uniform irrigation management to maintain soil water holding capacity above 50% depletion using two irrigation scenarios: 1) a standard 12.5 mm irrigation per application; and 2) an application to refill the soil profile to field capacity. A 21-year simulation study was carried out on a selected field with varying degrees of soil and topographic variability. The simulated field had 12 soil mapping units with water holding capacities in the top 0.30-m ranging from 42 to 70 mm. The 21-year simulation covering all weather conditions for each soil produced only two significantly different irrigation management zones for scenario 1, and for scenario 2 only one management zone. However, when the 21-year period was divided into periods with different ratios of rainfall to reference evapotranspiration, the simulations identified 1 to 5 management zones with significantly different irrigation requirements. These results indicate that variable rate irrigation system design and management should not be solely based on long term average weather conditions. Years with differing weather conditions should be used for potentially identifying management zones for VRI systems. Irrigation application depths between management zones ranged from 17 to 38 mm. However, when the actual soil areas of the study field were utilized to calculate the total volume of irrigation water applied, it resulted in an increase in water usage in the 2 and 4 management zones ranging from -1.2% to 5.8%. Water usage with VRI over uniform irrigation was greater by -1.6% to 6.8% in the 12.5 mm irrigations and by -1.2% to 2.2% for the field capacity irrigations Keywords: Management zones, Precision farming, Variable-rate irrigation, Water conservation.

Dynamic prescription maps for site-specific variable rate irrigation of cotton

A prescription map is a set of instructions that controls a variable rate irrigation (VRI) system. These maps, which may be based on prior yield, soil texture, topography, or soil electrical conductivity data, are often manually applied at the beginning of an irrigation season and remain static. The problem with static prescription maps is that they ignore spatiotemporal changes in crop water status. In a two-year study (2012 and 2013), a plant feedback system, including a wireless sensor network of infrared thermometers (IRTs), was used to develop dynamic prescription maps to accomplish adaptive irrigation scheduling for cotton (Gossypium hirsutum L.). One-half of a center pivot field was divided into manually and plant feedback-controlled irrigation treatment plots. Irrigation treatments were at three levels, 75, 50 and 25 percent of full as defined by either replenishment of crop water use to field capacity or by the equivalent threshold of the IRT sensed crop water stress. The system accepted user input to control irrigation for the manual treatment plots (I75M, I50M, and I25M), and calculated and compared a thermal stress index for each plant feedback-controlled treatment plot (I75C, I50C and I25C) with a pre-determined threshold for automated irrigation scheduling. The effectiveness of the plant feedback irrigation scheduling system was evaluated by comparing measured lint yield, crop water use (ETc), and water use efficiency (WUE) with the manually scheduled treatment plots. Results for both years indicated that average lint yields were similar between the manual and plant feedback-control plots at the I75 level (181 and 182gm−2, respectively, in 2012; 115 and 103gm−2, respectively, in 2013) and I50 level (146 and 164gm−2, respectively, in 2012; 95 and 117gm−2, respectively, in 2013). At the I25 level, average lint yield was significantly greater for the plant feedback-compared with the manual-control treatment plots (142gm−2 and 92gm−2, respectively), but the mean amount of irrigation was twice that of the manual-control plots. Mean water use efficiencies (WUE) within the same irrigation treatment levels were similar between methods. Importantly, the automatic plant feedback system did not require the time consuming and expensive manual reading of neutron probe access tubes that was required to schedule the manual treatments. These results demonstrate that the integration of a plant feedback system with a commercial VRI system could be used to control site-specific irrigation management for cotton at higher irrigation treatment levels, i.e., I75 percent and I50 percent of full. Such a system can facilitate the use of a VRI system by automating prescription map coding and providing dynamic irrigation control instructions to meet variable crop water needs throughout the irrigation season. As of yet, further research is required to maintain automatic deficit irrigation at a level equivalent to 25 percent replenishment of crop water use relative to field capacity.

Adoption of site-specific variable rate sprinkler irrigation systems

More than 20 years of private and public research on site-specific variable rate sprinkler irrigation (SS-VRI) technology on self-propelled center pivot and linear move irrigation systems has resulted in limited commercial adoption of the technology. Competing patents, liability, and proprietary software have affected industry's willingness to move into a new technology area. Docu- mented and proven water conservation strategies using site- specific irrigation are quite limited. Marginal costs associ- ated with site-specific technologies are high. Although sales of SS-VRI are increasing, they are primarily being used for eliminating irrigation and chemigation on non-cropped areas of a field or for land application of liquid agricultural and municipal wastes. Various aspects of SS-VRI technol- ogies for general crop production are beginning to slowly gain widespread acceptance; however, their uses are largely focused on addressing symptoms of poor design and sub- optimal water and nutrient management. Although cur- rently underutilized, SS-VRI technology has the potential to positively impact crop water productivity, water and energy conservation, and the environment. There are also few economic incentives to motivate growers to move to higher levels of SS-VRI management. Greater adoption rates will likely require higher costs for water and energy, severely restricted water diversions on a broad scale, and enforce- ment of compliance with environmental and other regula- tions. Sustainable use of SS-VRI will require strong research support, which is currently limited. In the short term, adoption of SS-VRI technologies will be enhanced by addressing equipment deficiencies and research developing basic criteria and systems for defining management zones and locations of various sensor systems for both arid and humid regions. Training adequate personnel to help write site-specific variable rate irrigation prescriptions in humid and arid areas to assist growers with the decision-making process is also a high priority. There is also a large need to educate government boards and bankers on the potential benefits of these systems. The long-term challenges will be to demonstrate that SS-VRI will improve water manage- ment or increase net returns. There is a critical need to develop fully integrated management systems with sup- porting elements that accurately and inexpensively define dynamic management zones, sense within-field variability in real time, and then adaptively control site-specific vari- able rate water applications, which will be challenging as significant knowledge gaps exist.

Site Specific Variable Rate Application by Automatic Driving Vehicle

Site Specific Variable Rate Application by Automatic Driving Vehicle