Development and validation of fuzzy logic inference to determine optimum rates of N for corn on the basis of field and crop features

A fuzzy inference system (FIS) was developed to generate recommendations for spatially variable applications of N fertilizer. Key soil and plant properties were identified based on experiments with rates ranging from 0 to 250 kg N ha⁻¹ conducted over three seasons (2005, 2006 and 2007) on fields with contrasting apparent soil electrical conductivity (EC_a), elevation (ELE) and slope (SLP) features. Mid-season growth was assessed from remotely sensed imagery at 1-m² resolution. Optimization of N rate by the FIS was defined against maximum corn growth in the weeks following in-season N application. The best mid-season growth was in areas of low EC_a, high ELE and low SLP. Under favourable soil conditions, maximum mid-season growth was obtained with low in-season N. Responses to N fertilizer application were better where soil conditions were naturally unfavourable to growth. The N sufficiency index (NSI) was used to judge plant N status just prior to in-season N application. Expert knowledge was formalized as a set of rules involving EC_a, ELE, SLP and NSI levels to deliver economically optimal N rates (EONRs). The resulting FIS was tested on an independent set of data (2008). A simulation revealed that using the FIS would have led to an average N saving of 41 kg N ha⁻¹ compared to the recommended uniform rate of 170 kg N ha⁻¹, without a loss of yield. The FIS therefore appears to be useful for incorporating expert knowledge into spatially variable N recommendations.     

Use of soil nitrogen parameters and texture for spatially-variable nitrogen fertilization

Recent studies have demonstrated the potential importance of using soil texture to modify fertilizer N recommendations. The objective of this study was to determine (i) if surface clay content can be used as an auxiliary variable for estimating spatial variability of soil NO₃–N, and (ii) if this information is useful for variable rate N fertilization of non-irrigated corn [Zea mays (L.)] in south central Texas, USA across years. A 64 ha corn field with variable soil type and N fertility level was used for this study during 2004–2007. Plant and surface and sub-surface soil samples were collected at different grid points and analyzed for yield, soil N parameters and texture. A uniform rate (UR) of 120 kg N ha⁻¹ in 2004 and variable rates (VAR) of 0, 60, 120, and 180 kg N ha⁻¹ in 2005 through 2007 were applied to different sites in the field. Distinct yield variation was observed over this time period. Yield and soil surface clay content and soil N parameters were strongly spatially structured. Corn grain yield was positively related to residual NO₃–N with depth and either negatively or positively related to clay content depending on precipitation. Residual NO₃–N to 0.60 and 0.90 m depths was more related to corn yield than from shallower depths. The relationship of clay content with soil NO₃–N was weak and not temporally stable. Yield response to N rate also varied temporally. Supply of available N with depth, soil texture and growing season precipitation determined proper N management for this field.     

Impact of Residual Soil Nitrate on In-Season Nitrogen Applications to Irrigated Corn Based on Remotely Sensed Assessments of Crop Nitrogen Status

Spatial and temporal variability of soil nitrogen (N) supply together with temporal variability of plant N demand make conventional N management difficult. This study was conducted to determine the impact of residual soil nitrate-N (NO₃-N) on ground-based remote sensing management of in-season N fertilizer applications for commercial center-pivot irrigated corn (Zea mays L.) in northeast Colorado. Wedge-shaped areas were established to facilitate fertigation with the center pivot in two areas of the field that had significantly different amounts of residual soil NO₃-N in the soil profile. One in-season fertigation (48 kg N ha⁻¹) was required in the Bijou loamy sand soil with high residual NO₃-N versus three in-season fertigations totaling 102 kg N ha⁻¹ in the Valentine fine sand soil with low residual NO₃-N. The farmer applied five fertigations to the field between the wedges for a total in-season N application of 214 kg N ha⁻¹. Nitrogen input was reduced by 78% and 52%, respectively, in these two areas compared to the farmer’s traditional practice without any reductions in corn yield. The ground-based remote sensing management of in-season applied N increased N use efficiency and significantly reduced residual soil NO₃-N (0–1.5 m depth) in the loamy sand soil area. Applying fertilizer N as needed by the crop and where needed in a field may reduce N inputs compared to traditional farmer accepted practices and improve in-season N management.     

Within-field nitrogen response in corn related to aerial photograph color

Precise management of nitrogen (N) using canopy color in aerial imagery of corn (Zea mays L.) has been proposed as a strategy on which to base the rate of N fertilizer. The objective of this study was to evaluate the relationship between canopy color and yield response to N at the field scale. Six N response trials were conducted in 2000 and 2001 in fields with alluvial, claypan and deep loess soil types. Aerial images were taken with a 35-mm slide film from ≥1100 m at the mid- and late-vegetative corn growth stages and processed to extract green and red digital values. Color values of the control N (0 kg N ha⁻¹) and sufficient N (280 kg N ha⁻¹ applied at planting) treatments were used to calculate the relative ratio of unfertilized to fertilized and relative difference color values. Other N fertilizer treatments included side-dressed applications in increments of 56 kg N ha⁻¹. The economic optimal N rate was weakly related (R ² ≤ 0.34) or not related to the color indices at both growth stages. For many sites, delta yield (the increase in yield between control N and sufficient N treatments) was related to the color indices (R ² ≤ 0.67) at the late vegetative growth stage; the best relationship was with green relative difference. The results indicate the potential for color indices from aerial photographs to be used for predicting delta yield from which a site-specific N rate could be determined.     

Effects of compost interactions on the alterations in mineral biochemistry,growth, tuber quality and production of <Emphasis Type="Italic">Solanum tuberosum</Emphasis>

Incorporation of compost in soil will not only protect the environment, but also take advantage of the nutrients and organic matter contained in the compost to enhance soil fertility and crop production. Field experiments were carried out during the 2006/2007 and 2007/2008 growing seasons at the College of Food and Agriculture Farm, United Arab Emirates University. The experiments were established in randomized complete block design (RCBD) with four replications. The plot dimension was 3.2m×2.8 m, with four rows per plot. The treatments were designed to study the effect of compost rates on the potato production and soil fertility properties. Five rates of compost were investigated (control, 40, 80, 120 ton compost per hectare; and inorganic fertilizers (250 kg N·ha⁻¹, 250 kg P₂O₅·ha⁻¹ and 300 kg K₂O·ha⁻¹)). Results of the first growing season 2006/2007 showed that marketable tuber yield, plant height and specific gravity were greater in compost amended soil than in non-amended soil even if inorganic fertilizers were added. Application of 120 ton compost per hectare gave the highest total tubers number, marketable tuber yield, height and specific gravity.     

Can Landform Stratification Improve Our Understanding of Crop Yield Variability?

Farmers account for yield and soil variability to optimize their production under mainly economic considerations using the technology of precision farming. Therefore, understanding of the spatial variation of crop yield and crop yield development within arable fields is important for spatially variable management. Our aim was to classify landform units based on a digital elevation model, and to identify their impact on biomass development. Yield components were measured by harvesting spring barley (Hordeum vulgare, L.) in 1999, and winter rye (Secale cereale, L.) in 2000 and 2001, respectively, at 192 sampling points in a field in Saxony, Germany. The field was stratified into four landform units, i.e., shoulder, backslope, footslope and level. At each landform unit, a characteristic yield development could be observed. Spring barley grain yields were highest at the level positions with 6.7 t ha⁻¹ and approximately 0.15 t ha⁻¹ below that at shoulder and footslope positions in 1999. In 2000, winter rye harvest exhibited a reduction at backslope positions of around 0.2 t ha⁻¹ as compared to the highest yield obtained again at level positions with 11.1 t ha⁻¹. The distribution of winter rye grain yield across the different landforms was completely different in 2001 from that observed in 2000. Winter rye showed the highest yields at shoulder positions with 11.1 t ha⁻¹, followed by the level position with 0.5 t ha⁻¹ less grain yield. Different developments throughout the years were assumed to be due to soil water and meteorological conditions, as well as management history. Generally, crop yield differences of up to 0.7 t ha⁻¹ were found between landform elements with appropriate consideration of the respective seasonal weather conditions. Landform analysis proved to be helpful in explaining variation in grain yield within the field between different years.     

Application of the CSM-CERES-Rice model for evaluation of plant density and nitrogen management of fine transplanted rice for an irrigated semiarid environment

The objectives of this study were to evaluate the performance of the cropping system model (CSM)-CERES-Rice to simulate growth and development of an aromatic rice variety under irrigated conditions in a semiarid environment of Pakistan and to determine the impact of various plant densities and nitrogen (N) application rates on grain yield and economic return. The crop simulation model was evaluated with experimental data collected in experiments that were conducted in 2000 and 2001 in Faisalabad, Punjab, Pakistan. The experimental design was a randomized complete block design with three replications and included three plant densities (one seedling hill⁻¹, PD₁; two seedlings hill⁻¹, PD₂; and three seedlings hill⁻¹, PD₃) and five N fertilizer regimes (control, N₀; 50 kg ha⁻¹, N₅₀; 100 kg ha⁻¹, N₁₀₀; 150 kg ha⁻¹, N₁₅₀; and 200 kg ha⁻¹, N₂₀₀). To determine the most appropriate combination of plant density and N levels, four plant densities from one seedling hill⁻¹ to four seedlings hill⁻¹ and 13 N levels ranging from 0 to 300 kg N ha⁻¹ (52 scenarios) were simulated for 35 years of historical daily weather data under irrigated conditions. The evaluation of CSM-CERES-Rice showed that the model was able to simulate growth and yield of irrigated rice in the semiarid conditions, with an average error of 11% between simulated and observed grain yield. The results of the stimulation analysis result showed that two seedlings hill⁻¹ along with 200 kg N ha⁻¹ (PD₂N₂₀₀) produced the highest yield as compared to all other scenarios. Furthermore, the economic analysis through the mean gini dominance also showed the dominance of this treatment (PD₂N₂₀₀) compared to the other treatment combinations. Thus, the management scenario that consisted of two seedlings hill⁻¹ and 200 kg N ha⁻¹ was the best for high yield and monitory return of irrigated rice in the semiarid environment. The mean monetary returns ranged from 291 US $ ha⁻¹ to 1 460 US $ ha⁻¹ to 1 460 US  ha⁻¹ among the 52 production options that were simulated. This approaching was demonstrated as effective way to optimize the density and N management for high yield and monetary return. It will help the rice production.     

Estimation of economic and environmental potentials of variable rate versus uniform N fertilizer application to spring barley on morainic soils in SE Norway

Spring barley was grown for 4 years (2001–2004) in field trials at two sites on morainic soil in central SE Norway, with five N level treatments: 0, 60, 90, 120 and 150 kg N ha^-1. Regression analyses showed that a selection of soil properties could explain 95–98% of the spatial yield variation and 47–90% of the yield responses (averaged over years). A strategy with uniform fertilizer application of 120 kg N ha⁻¹ (U _N120) was compared with two variable-rate (VR) strategies, with a maximum N rate of either 150 kg N ha⁻¹ (VR_N150) or 180 kg N ha⁻¹ (VR_N180). These strategies were tested using either Norwegian prices (low price ratio of N fertilizer to yield value; P_N/P_Y), or Swedish prices (high P_N/P_Y). The VR_N180 strategy had the highest potential yield and net revenue (yield value minus N cost) at both sites and under both price regimes. Using this strategy with Norwegian prices would increase the profit of barley cropping as long as at least 40 and 31% of the estimated potential increase in net revenue was realized, respectively. Using Swedish prices, uniform application appeared to be as good as or even better economically than the VR methods, when correcting for extra costs of VR application. The environmental effect of VR compared with uniform application, expressed as N not accounted for, showed contrasting effects when using Norwegian prices, but was clearly favourable using Swedish prices, with up to 20% reduction in the amount of N not accounted for.     

Subfield crop yields and temporal stability in thousands of US Midwest fields

Understanding subfield crop yields and temporal stability is critical to better manage crops. Several algorithms have proposed to study within-field temporal variability but they were mostly limited to few fields. In this study, a large dataset composed of 5520 yield maps from 768 fields provided by farmers was used to investigate the influence of subfield yield distribution skewness on temporal variability. The data are used to test two intuitive algorithms for mapping stability: one based on standard deviation and the second based on pixel ranking and percentiles. The analysis of yield monitor data indicates that yield distribution is asymmetric, and it tends to be negatively skewed (p?<?0.05) for all of the four crops analyzed, meaning that low yielding areas are lower in frequency but cover a larger range of low values. The mean yield difference between the pixels classified as high-and-stable and the pixels classified as low-and-stable was 1.04 Mg ha^?1 for maize, 0.39 Mg ha^?1 for cotton, 0.34 Mg ha^?1 for soybean, and 0.59 Mg ha^?1 for wheat. The yield of the unstable zones was similar to the pixels classified as low-and-stable by the standard deviation algorithm, whereas the two-way outlier algorithm did not exhibit this bias. Furthermore, the increase in the number years of yield maps available induced a modest but significant increase in the certainty of stability classifications, and the proportion of unstable pixels increased with the precipitation heterogeneity between the years comprising the yield maps.

     

Site-specific management of limiting nutrients in peanut (Arachis hypogaea) on the Texas High Plains

Nutrient data obtained from soil chemical tests were analyzed in an activity analysis model to identify limiting factors in peanut production on the Texas High Plains. A production function was estimated for the study field, and limiting factors were identified at individual sites where the production function indicated that yield did not respond. The estimated production function also enabled us to conduct a cost-return analysis of variable- and blanket-rate fertilizer applications. The results showed that peanut yields did not respond to most of the nutrients included in the study, which confirmed conclusions from previous studies in the study region. Calcium and nitrogen were the only two limiting factors identified in this study. Significant economic returns could be obtained by site-specific fertilizer application. The average economic return from variable-rate calcium fertilizer application was $27.84 ha⁻¹ and from blanket-rate it was $10.73 ha⁻¹. The return from variable-rate nitrogen fertilizer application was about $20 ha⁻¹ and from a blanket-rate it was about $14 ha⁻¹. There seems to be quite a strong economic incentive to adopt variable-rate application for calcium and nitrogen fertilizer application.

Soil water status mapping and two variable-rate irrigation scenarios

Irrigation is the major user of allocated global freshwaters, and scarcity of freshwater threatens to limit global food supply and ecosystem function—hence the need for decision tools to optimize use of irrigation water. This research shows that variable alluvial soil ideally requires variable placement of water to make the best use of irrigation water during crop growth. Further savings can be made by withholding irrigation during certain growth stages. The spatial variation of soil water supplied to (1) pasture and (2) a maize crop was modelled and mapped by relating high resolution apparent electrical conductivity maps to soil available water holding capacity (AWC) at two contrasting field sites. One field site, a 156-ha pastoral farm, has soil with wide ranging AWCs (116–230 mm m⁻¹); the second field site, a 53-ha maize field, has soil with similar AWCs (161–164 mm m⁻¹). The derived AWC maps were adjusted on a daily basis using a soil water balance prediction model. In addition, real-time hourly logging of soil moisture in the maize field showed a zone where poorly drained soil remained wetter than predicted. Variable-rate irrigation (VRI) scenarios are presented and compared with uniform-rate irrigation scenarios for 3 years of climate data at these two sites. The results show that implementation of VRI would enable significant potential mean annual water saving (21.8% at Site 1; 26.3% at Site 2). Daily soil water status mapping could be used to control a variable rate irrigator.     

Profitability of variable rate nitrogen application in wheat production

Using plant sensing to determine the amount of nitrogen (N) to apply has the potential to increase profits in wheat (Triticum aestivum) production by reducing N cost or by increasing grain yield. The objective of this paper was to determine if yields and profits from experimental trials that used a precision N applicator to apply N were significantly different from trials that applied pre-determined amounts of N. Across Oklahoma, USA, experiments were designed to test 10 N treatments that included two variable rate treatments (VRT), two uniform rate treatments (URT) where the level of N applied was based on optical reflectance measurements (ORM), and six conventional treatments (i.e., pre-determined uniform rates of N). Data included treatments during 2005–2009 from eight different locations. Results indicated no statistical difference in yields between the conventional treatments that apply 90 kg ha⁻¹ of N and the VRT and URT treatments. On average, the conventional treatment that applied 90 kg ha⁻¹ of top-dress N produced the largest yield, with a VRT treatment producing the third largest yield. Profits were calculated for each treatment using a partial budget. On average, the treatment that received 90 kg ha⁻¹ of top-dress N was the most profitable even though the pre-plant N (anhydrous ammonia) had a cost advantage relative to top-dress N (urea and ammonium nitrate).     

Regional model for nitrogen fertilization of site-specific rainfed corn in haplustolls of the central Pampas,Argentina

In semi-arid regions, soil water and nitrogen (N) are generally limiting factors for corn (Zea mays L.) production; hence, implementation of appropriate N fertilization strategies is needed. The use of precision agriculture practices based on specific site and crop properties may contribute to a better allocation of fertilizer among management zones (MZ). The aim of this study was to develop a model for diagnosis of N availability and recommendation of N fertilizer rates adjusted to MZ for dryland corn crops growing in Haplustolls. The model considered variability between MZ by including site-specific variables [soil available water content at sowing (SAW) and Available Nitrogen (soil available N-NO₃ at planting + applied N, Nd)] using spatial statistical analysis. The study was conducted in Córdoba, Argentina in Haplustolls and consisted in four field trials of N fertilizer (range 0–161 kg N ha⁻¹) in each MZ. The MZ were selected based on elevation maps analysis. Grain yields varied between MZ and increased with larger SAW and Nd at sowing. Grain responses to Nd and SAW in any MZ were not different between sites, allowing to fit a regional model whose parameters (Nd, Nd², SAW, SAW²) contributed significantly (p < 0.001) to yield prediction. Agronomical and economically optimum N rates varied among MZs. However, the spatial variability of optimum N rates among MZs within sites was not enough to recommend variable N fertilizer rates instead of a uniform rate. Variable N fertilizer rates should be recommended only if variability in SAW and soil N among MZ is greater than that found in this work.     

Characterization and modeling of water movement and salts transfer in a semi-arid region of Tunisia (Bou Hajla,Kairouan) – Salinization risk of soils and aquifers

The semi-arid region of Bou Hajla (Kairouan – Central Tunisia) is exposed to the risk of soils and aquifers salinization. A characterization of water movement through the use of TDR probes installed at up to 4 m in depth, and of salts transfer by soil sampling was conducted to highlight this risk. At the same time, climatic parameters were monitored. The results were gathered over the period of approximately 1 year (June 12, 2006 to May 08, 2007). Water infiltration and evaporation, occurred at within distinct materials: two zero flux planes at 1 and 3 m, and a clay-silt layer at 2 m where the soil water content and electrical conductivity is highly varied. Saline profiles show salt accumulation at this layer where the electrical conductivity of soil paste extract exceeds 20 dS m⁻¹. However, the additive salt balance between soil surface and a depth of 4 m highlights the salt transfer beyond the studied unsaturated zone, increasing the salinization risk of the aquifer. The water movement and salts transfer were simulated by Hydrus-1d model, and inverse modeling was used to optimize the required hydrodynamic parameters. It was found that the simulated profiles of volumetric humidity and the electrical conductivity of soil are close to those measured. The calculated RMSE values are low, indicating the reliability of Hydrus-1d for the simulation of the hydro-saline dynamics in field conditions.     

Widescale testing of the Crop-meter for site-specific farming

A sensor for measuring crop biomass density has been designed and developed to meet the demands for practical use in site-specific farming. The mechanical sensor named ‘Crop-meter’ is based on the pendulum principle. The suitability and measuring stability of the Crop-meter has been confirmed under field conditions in different regions of Germany. Significant correlations were obtained between Crop-meter signals and soil electrical conductivity (R ²=0.16−0.66) and grain yield (R ²=0.42−0.57). To test the suitability of the Crop-meter for site-specific management, it was used to control variable application rates for nitrogen fertiliser, growth regulators and fungicides in real time. A small increase in yield (3.1%) as well as reduced application rates for agrochemicals (14.6% nitrogen fertilisers; 23.1% fungicides and growth regulators) were proved in large-scale trials.     

Quantifying spatial variability of indigenous nitrogen supply for precision nitrogen management in small scale farming

Understanding spatial variability of indigenous nitrogen (N) supply (INS) is important to the implementation of precision N management (PNM) strategies in small scale agricultural fields of the North China Plain (NCP). This study was conducted to determine: (1) field-to-field and within-field variability in INS; (2) the potential savings in N fertilizers using PNM technologies; and (3) winter wheat (Triticum aestivum L.) N status variability at the Feekes 6 stage and the potential of using a chlorophyll meter (CM) and a GreenSeeker active crop canopy sensor for estimating in-season N requirements. Seven farmer’s fields in Quzhou County of Hebei Province were selected for this study, but no fertilizers were applied to these fields. The results indicated that INS varied significantly both within individual fields and across different fields, ranging from 33.4 to 268.4 kg ha⁻¹, with an average of 142.6 kg ha⁻¹ and a CV of 34%. The spatial dependence of INS, however, was not strong. Site-specific optimum N rates varied from 0 to 355 kg ha⁻¹ across the seven fields, with an average of 173 kg ha⁻¹ and a CV of 46%. Field-specific N management could save an average of 128 kg N ha⁻¹ compared to typical farmer practices. Both CM and GreenSeeker sensor readings were significantly related to crop N status and demand across different farmer’s fields, showing a good potential for in-season site-specific N management in small scale farming systems. More studies are needed to further evaluate these sensing technology-based PNM strategies in additional farmer fields in the NCP.     

Calibration of a capacitance probe for measurement and mapping of dry matter yield in Mediterranean pastures

The main objective of this study was to calibrate a commercial capacitance probe for measuring pasture dry matter yields under Mediterranean conditions. The standard method of assessing pasture biomass is based on cutting all the forage within a specified area and requires great effort and expense to collect enough samples to accurately represent a pasture. The field tests were carried out in 2007, 2008 and 2009 on different dates (phenological stages), and on five dairy farms, representing typical pastures in the region (grasses; legumes; and bio-diverse flora, mixture of grasses, legumes and others species). The linear regression techniques used in 2007 to relate the weight of the herbage (direct measurements) to the meter reading of capacitance (indirect measurements) led to high regression coefficients in grasses (R² = 0.90; P < 0.01) and heterogeneous botanical composition (R² = 0.87; P < 0.001) and moderate regression coefficient in legumes species (R² = 0.48; P < 0.05). The validation of the calibration equations in 2008 and 2009 in two sites showed RSME values of 130 kg ha⁻¹ in heterogeneous botanical composition and 456 kg ha⁻¹ in legumes. The results indicated that the capacitance probe together with a GPS receiver might support site-specific management of pastures which would be useful in large areas.     

Delineating productivity zones in a citrus grove using citrus production,tree growth and temporally stable soil data

The productivity of a citrus grove with variation in tree growth was mapped to delineate zones of productivity based on several indicator properties. These properties were fruit yield, ultrasonically measured tree canopy volume, normalized difference vegetation index (NDVI), elevation and apparent electrical conductivity (EC_a). The spatial patterns of soil series, soil color and EC_a, and their correspondence with the variation in yield emphasized the importance of variation in the soil in differentiating the productivity of the grove. Citrus fruit yield was positively correlated with canopy volume, NDVI and EC_a, and yield was negatively correlated with elevation. Although all the properties were strongly correlated with yield and were able to explain the productivity of the grove, citrus tree canopy volume was most strongly correlated (r = 0.85) with yield, explaining 73% of its variation. Tree canopy volume was used to classify the citrus grove into five productivity zones termed as ‘very poor’, ‘poor’, ‘medium’, ‘good’ and ‘very good’ zones. The study showed that productivity of citrus groves can be mapped using various attributes that directly or indirectly affect citrus production. The productivity zones identified could be used successfully to plan soil sampling and characterize soil variation in new fields.     

Optimization of corn plant population according to management zones in Southern Brazil

Precision agriculture relies on site-specific interventions determined by the spatial variability of factors driving plant growth. The main objective of this study was to assess the efficiency of variable-rate seeding of corn (Zea mays L.) with delineated management zones. This study involved two experiments carried out in Não-Me-Toque, Rio Grande do Sul, Brazil. For the first experiment, carried out in 2009/2010, management zones were delineated by the farmer’s knowledge of the crop field. The field was split into low (LZ), medium (MZ) and high (HZ) crop performance zones. In the second experiment, carried out in 2010/2011, management zones were delineated by overlaying standardized yield data from nine crop seasons (seven of soybean and two of corn). The experiment was carried out with a randomized block design with three management zones and five corn seeding rates ranging from 50 000 to 90 000 seeds per ha^?1. The soil was a Rhodic Hapludox with a subtropical climate. Optimization of the corn plant population within the field increased grain yield compared to the reference plant population (70 000 plants ha^?1). Yield increases in the LZ, due to corn plant population reduction in relation to the target population, were 1.20 and 1.90 Mg ha^?1 for first and second experiments, respectively. This resulted in economic gains of 19.8 and 28.7 %, respectively. Yield increases in the HZ were 0.89 and 0.94 Mg ha^?1, respectively, and were due to an increase in plant population in relation to the target population. This resulted in economic gains of 5.6 and 6.6 % for the first and second experiments, respectively. In the MZ, the adjustment of the target plant population was not necessary. Optimizing corn population according to management zones is a promising tool for precision agriculture in Southern Brazil.