Effects of Growth Diagnosis Using Visible Canopy Images and Variable Rate Nitrogen Application at the Flag Leaf Appearing Stage on the Grain Protein Content of the Wheat Cultivar ‘Sanukinoyume 2009’

Variable-rate nitrogen (VR-N) application allows farmers to optimize nitrogen (N) input site-specifically within field boundaries, enhancing both economic efficiency and environmental sustainability. In this study, VR-N technology was applied to durum wheat in two small-scale commercial fields (3–4 ha each) located in distinct agro-climatic zones of Thessaly, central Greece. A real-time VR-N application algorithm was used to calculate N rates based on easily obtainable near-real-time data from unmanned aerial vehicle (UAV) imagery, tailored to the crop’s actual needs. VR-N implementation was carried out using conventional fertilizer spreaders equipped to read prescription maps. Results showed that VR-N reduced N input by up to 49.6% compared to the conventional uniform-rate N (UR-N) application, with no significant impact on wheat yield or grain quality. In one of the fields, the improved gain of VR-N when compared to UR-N was 7.2%, corresponding to an economic gain of EUR 163.8 ha−1, while in the second field—where growing conditions were less favorable—no considerable VR-N economic gain was observed. Environmental benefits were also notable. The carbon footprint (CF) of the wheat crop was reduced by 6.4% to 22.0%, and residual soil nitrate (NO3−) levels at harvest were 13.6% to 36.1% lower in VR-N zones compared to UR-N zones. These findings suggest a decreased risk of NO3− leaching and ground water contamination. Overall, the study supports the viability of VR-N as a practical and scalable approach to improve N use efficiency (NUE) and reduce the environmental impact of wheat cultivation which could be readily adopted by farmers.

The environmental assessment of using optical crop sensors for variable rate nitrogen application (VRNA) has been limited by the lack of a robust method to quantify site- and technology-specific impacts. This study aimed to (1) present a comparative life cycle assessment (LCA) of a conventional winter wheat production system with and without using a crop sensor for VRNA applied to an Austrian case study. Special emphasis was placed on simulating site-specific field emissions with the DeNitrification-DeComposition (DNDC) biogeochemical soil model; (2) assess the environmental impacts of only the fertilization process; and (3) compare soil emissions simulated by the DNDC with soil emissions coming from a benchmark ecoinvent wheat production process. Three nitrogen fertilization schemes – one conventional and two VRNA – were modeled. Two functional units were used – 1 ha of cultivated winter wheat and 1 kg of winter wheat produced. The system boundary includes tillage, seeding, plant protection, nitrogen fertilization, and harvesting processes. Information communication technologies (ICT) – manufacturing of the sensor, internet and computer manufacturing and usage – were also included within the boundary. Local and global environmental impacts attributed to nitrogen emissions due to fertilization were evaluated in this LCA, including climate change (CC), fine particulate matter formation (FPMF), freshwater eutrophication (FE), freshwater ecotoxicity (FET), terrestrial acidification (TA), marine eutrophication (ME), and human noncarcinogenic toxicity (HTnc). The CC of the fertilization process was 1,662.8 kg CO2 eq./ha with conventional nitrogen application versus 1,518.8 kg CO2 eq./ha as the lower of the two VRNA results, an 8.6% reduction due to less fertilizer applied. Fertilization was found to be responsible for more than 80% of the total emissions that impact CC, 55% of the FET, 44% of the HTnc, 96% of the FE and 96% of the TA. The largest greenhouse gas (GHG) emitters were soil N emissions as simulated by the DNDC, followed by the fertilizer manufacturing process in all of the impacts, except for FET and HTnc, where fertilizer production was the highest contributor. ICT components contributed less than 1% to all of the impacts assessed. The amount of applied N fertilizer has a greater influence on NH3 and NO3 indirect soil emissions than on direct N2O emissions. This study demonstrates that using optical crop sensors for VRNA could have a limited but positive environmental impact and highlights the importance of applying site-specific soil models to estimate field emissions.

A high grain protein content (GPC) must be achieved in durum wheat cultivation. However, GPC is negatively correlated with the yield, making it difficult to control. In this study, we tested whether variable-rate nitrogen application at the flag-leaf appearing stage (GS37), where other operations are not overlapping in durum wheat cultivation, could effectively increase GPC. In addition, the possibility of using a growth diagnostic index calculated from canopy images as a guide to variable-rate nitrogen applications was tested. GPC was significantly increased by 0.8 to 2% for each 5 g m−2 increase in nitrogen application at GS37, which was due to an increase in aboveground nitrogen content of approximately 2 g m−2 for every 5 g m−2 increase in nitrogen. Although 44 growth diagnostic indices calculated from 2D images were tested, only the Hue 120–170° ratio showed a significant correlation with aboveground nitrogen content at GS37 over the three seasons, and no significant differences in intercept and slope were found over the three seasons. When the nitrogen content at GS37 was estimated using the Hue 120–170° ratio, and nitrogen was applied at GS37 to achieve 12 g m−2 aboveground nitrogen content at maturity, the nitrogen content in the validation plot at maturity was approximately 12 g m−2 irrespective of the sowing density. Therefore, variable-rate nitrogen application using 2D image diagnosis at GS37 would be an effective cultivation method to increase the GPC of durum wheat.

To develop a time‐Specific and time‐critical spatial variable rate nitrogen application (VRN) method and to overcome the limitations of traditional field sampling methods, this study focused on the relationship between SPAD chlorophyll meter readings and nitrogen content in leaves in order to determine the amount of nitrogen fertilisation required for agricultural objectives. Field experiments were conducted in three wheat growth duration stages from 2003 to 2006. Grain yields and soil NO3‐N contents were measured in all plots. Our results indicated that VRN technology reduced wheat yield spatial variability. The benefits of VRN included low soil residual NO3‐N content and NO3‐N leaching potential, suggesting that VRN technology based on SPAD readings can potentially reduce groundwater pollution and therefore protect our limited environmental resources.

This study evaluates the long-term profitability and environmental impacts of variable rate versus uniform nitrogen application in seed potato production with nitrogen carry-over effects included. Seed potato yields were simulated for four different areas of a field using the EPIC crop growth model. A dynamic optimization model was used to determine optimal steady-state nitrogen levels for each area and the entire field. Average nitrogen losses and economic returns were evaluated for both uniform and variable rate nitrogen fertilizer. Variable rate nitrogen application was found to be unprofitable for the field when compared to uniform nitrogen application. Nitrogen losses for the field were about the same under both strategies. The results indicate greater economic and environmental benefits may be achieved by splitting nitrogen applications, especially for areas of the field exhibiting low yield productivity.

This paper presents the development of a sensor-based variable-rate application systemfor nitrogen side-dressing in corn fields. A multispectral corn nitrogen deficiency sensor was usedto provide the corn nitrogen stress information in real-time during the side-dress. This sensorassess the nitrogen stress by means of the estimated SPAD value of the corn based on corncanopy reflectance sensed using three channels (green, red, near-infrared) of the multispectralcamera. Some calibration relationships between the multispectral reflectance and SPAD valueshave been found from previous study. A variable-rate nitrogen application model based on theestimated SPAD values was developed in this research to search for the optimal amount ofnitrogen needed to achieve an optimal corn production. The nitrogen application using the sensorbasedVRA system was performed at V11 stage. Based on the limited results obtained from thisresearch, it has demonstrated that it is feasible to develop a sensor-based VRA system to achievethe goal of crop condition-based VRA to optimize the corn production on-the-go while performingthe nitrogen application.

A micro-level model of farmer decision making is developed to examine the extent to which uncertainty about potential yields influences the value of site-specific technologies. The economic and environmental benefits of these technologies arise from two sources: information gathering and variable-rate nitrogen application. Application of the model to fields in Illinois shows the value of variable-rate nitrogen application is higher on fields with low average potential yields, high spatial variability, positively skewed potential yield distributions, responsive yield to nitrogen, and low uncertainty. Variable-rate application decreases nitrogen use by reducing the extent of overapplication. However, in the presence of uncertainty about potential yields, the incentives to over apply nitrogen irrespective of the method of application, uniform or variable rate, can reduce the economic and environmental benefits of sitespecific technologies.

Real-time sensor systems for variable rate nitrogen (N) application (VRNA) are an established technology nowadays but they have some shortcomings in terms of their capability to consider multiple parameters relevant for plant growth. Further, the abundantly lacking section control in centrifugal spreaders limits the accuracy of a sensor-based VRNA, especially in combination with the temporal and spatial offsets between sensing and fertilizer placement. Fuzzy inference systems were incorporated into a real-time control to numerically fuse the crop N uptake sensed by a real-time sensor system, as well as mapped soil electrical conductivity (ECa) data for the calculation of site-specific N dose rates (DR). A distinction of two subsections within the working width of a sensor-spreader system was made based on the ECa data. Further, by implementing a generic model, the control system agronomically optimized the rate control of a centrifugal spreader in order to compensate positional lags and technical latencies and minimize the spatial offset between DR determination and application in a dynamic manner. With field tests at different driving speed scenarios going partly beyond the usual operation conditions, the real-time control was verified. The differentiation of the sections has resulted in slight DR differences, whereas the control system has shown a high consistency in calculating the DRs and sending commands to the spreader in a coordinated manner. The level of spatial concordance between DR determination and application had a highly stochastic character. However, the deviation was never beyond 1.5 m and the percentage of deviations beyond 1 m reached a maximum of 2.3% among the different recorded datasets, which can be considered as a sufficient performance for practical needs.

Meta-response functions for corn yields and nitrogen losses were estimated from EPIC-generated data for three soil types and three weather scenarios. These metamodels were used to evaluate variable rate (VRT) versus uniform rate (URT) nitrogen application technologies for alternative weather scenarios and policy options. Except under very dry conditions, returns per acre for VRT were higher than for URT and the economic advantage of VRT increased as realized rainfall decreased from expected average rainfall. Nitrogen losses to the environment from VRT were lower for all situations examined, except on fields with little spatial variability.

Capability of crop canopy sensing to predict crop parameters of cut grass swards aiming at early season variable rate nitrogen top dressings

We 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.

Variable rate nitrogen (N) application based on in-season remote sensing can potentially improve wheat (Triticum aestivum L.) N management and N use efficiency (NUE). The goal of this study was to evaluate the potential of improving in-season soft red winter wheat (SRWW) variable rate N recommendations based on crop canopy reflectance. Small-plot N rate response calibration studies guided development of the Virginia Wheat Algorithm (VWA) for grain yield prediction and variable rate N fertilizer rate determination for SRWW. Large plot, replicated validation studies conducted for 15 site-years included an N-rich strip installed at growth stage (GS) 25 and various treatments at GS 30; four or five fixed-rate treatments applied to evaluate site N response, a variable rate based on the VWA applied using a GreenSeeker® RT 200 system and a “standard” fixed rate based on GS 30 wheat tissue N concentration. All sites responded positively to GS 30 N application. When data from one site were excluded, rates were 8 and 3 kg ha−1 below the economically optimal N rate (EONR) for the VWA and standard methods, respectively. Based on these data, the GreenSeeker® RT 200 system employing the VWA was equivalent to the current standard method and offers real-time rate prescriptions with less labor and less delay than the current tissue N concentration sufficiency standard.

Soil, Water and Yield Relationships in developing Strategies for the Precision Application of Nitrogen Fertiliser to Winter Barley

The adoption and usage of precision agriculture technologies in North Dakota

Nitrogen management has been intensively studied on several crops and recently associated with variable rate on-the-go application based on crop sensors. Such studies are scarce for sugarcane and as a biofuel crop the energy input matters, seeking high positive energy balance production and low carbon emission on the whole production system. This article presents the procedure and shows the first results obtained using a nitrogen and biomass sensor (N-Sensor™ ALS, Yara International ASA) to indicate the nitrogen application demands of commercial sugarcane fields. Eight commercial fields from one sugar mill in the state of Sao Paulo, Brazil, varying from 15 to 25 ha in size, were monitored. Conditions varied from sandy to heavy soils and the previous harvesting occurred in May and October 2009, including first, second, and third ratoon stages. Each field was scanned with the sensor three times during the season (at 0.2, 0.4, and 0.6 m stem height), followed by tissue sampling for biomass and nitrogen uptake at ten spots inside the area, guided by the different values shown by the sensor. The results showed a high correlation between sensor values and sugarcane biomass and nitrogen uptake, thereby supporting the potential use of this technology to develop algorithms to manage variable rate application of nitrogen for sugarcane.