D. G. Westfall

Evaluating Farmer Defined Management Zone Maps for Variable Rate Fertilizer Application

In the U.S.A. intensive grid soil sampling has conventionally been used to develop prescription maps for variable rate (VRT) fertilizer application. Grid sampling can provide an accurate basis for variable rate application; however the cost and labor requirements suggest other approaches may be more economical. This research was initiated to determine if farmer-developed management zone maps based on soil color from aerial photographs, topography, and the farmers past management experience can be effective in developing variable rate application maps. The accuracy of farmer-developed management zone maps was investigated on two center pivot irrigated fields near Wiggins, Colorado. Using aerial photographs as a template, the farmer defined high, medium, and low productivity management zones. Cluster analysis confirmed that management zones represent different suites of soil characteristics. In field one, soil organic matter (SOM), clay, nitrate, potassium, zinc, conductivity and corn yield data followed the trends indicated by the management zones. In field two, however, the medium productivity zone had the highest values for these parameters. Farmer developed management zones appear to be effective in identifying different management zones; however, ground truthing is needed to develop accurate VRT maps from the zones.

Evaluation of two crop canopy sensors for nitrogen variability determination in irrigated maize

Advances in precision agriculture technology have led to the development of ground-based active remote sensors that can determine normalized difference vegetation index (NDVI). Studies have shown that NDVI is highly related to leaf nitrogen (N) content in maize (Zea mays L.). Remotely sensed NDVI can provide valuable information regarding in-field N variability and significant relationships between sensor NDVI and maize grain yield have been reported. While numerous studies have been conducted using active sensors, none have focused on the comparative effectiveness of these sensors in maize under semi-arid irrigated field conditions. Therefore, the objectives of this study were (1) to determine the performance of two active remote sensors by determining each sensor’s NDVI relationship with maize N status and grain yield as driven by different N rates in a semi-arid irrigated environment and, (2) to determine if inclusion of ancillary soil or plant data (soil NO3 concentration, leaf N concentration, SPAD chlorophyll and plant height) would affect these relationships. Results indicated that NDVI readings from both sensors had high r2 values with applied N rate and grain yield at the V12 and V14 maize growth stages. However, no single or multiple regression using soil or plant variables substantially increased the r2 over using NDVI alone. Overall, both sensors performed well in the determination of N variability in irrigated maize at the V12 and V14 growth stages and either sensor could be an important tool to aid precision N management.

Spatial Variation and Site-Specific Management Zones

Many approaches have been proposed over the last two decades for managing the spatial variation of soil and crops. In this chapter we discuss the importance of quantifying and managing spatial variation in crop production fields to implement site-specific crop management. We outline the challenges that soil and crop scientists have addressed since the inception of precision agriculture (PA) in terms of managing soil spatial variation, and the development of simple, stable and inexpensive techniques for quantifying and managing it with tools such as site-specific management zones. This chapter summarizes and cites the work of several scientists who have worked in the area of development and evaluation of site-specific management zones from around the world. Geostatistics is being applied increasingly in PA because of the need for accurate maps on which to base site-specific management. For soil and crop properties that require costly sampling and analysis, there are often insufficient data for geostatistical analyses and this chapter shows how management zones can provide an interim solution to more comprehensive site-specific management. Physical and chemical soil properties have been the most widely used properties for delineating management zones, however, intensive data from remote and proximal sensors are being used increasingly. The case study describes methods of delineating and evaluating management zones.

Mobility of Organic and Inorganic Zinc Fertilizers in Soils

Abstract Zinc sulfate (ZnSO4 · H2O) has traditionally been the “reliable” source of zinc (Zn) fertilizer, but other sources of Zn are also available. Some are derived from industrial by‐products, varying from flue dust reacted with sulfuric acid to organic compounds derived from the paper industry. The degree of Zn mobility in Zn sources derived from these various by‐products is related to the manufacturing process, the source of complexing or chelating agents (organic sources), and the original product used as the Zn source. Many claims are made regarding the relative efficiency of traditional inorganic Zn fertilizers and complexed Zn sources. The objective of this column study was to compare the mobility of several commercial Zn fertilizer materials (organic and inorganic) that are commonly used to correct Zn deficiencies in soils. The sources included three granular inorganic Zn sources, two granular organically complexed Zn sources, and liquid ZnEDTA. Soil columns were leached five times with deionized water. Leaching events were separated by approximately 48 h. At the conclusion of the leaching phase, columns were analyzed for plant‐available Zn. Water solubility was the primary factor affecting Zn movement, not total Zn content or organic complexation of the fertilizers. The Zn sources evaluated can be separated into three groups: ZnEDTA, ZnLigno, and ZnSO4 were the most mobile Zn sources; the ZnOx55 was less mobile, but seemed mobile enough to meet crop needs; ZnOx26 and ZnSuc were relatively immobile Zn sources.

Temporal and Spatial Stability of Soil Test Parameters Used in Precision Agriculture

Abstract Variable‐rate technology provides crop producers with the opportunity to vary the crop and soil management practices. The objective of this study was to assess the temporal and spatial stability of nitrogen (N), phosphorus (P), potassium (K), zinc (Zn), pH, and soil organic matter (OM) for precision nutrient management. This study was conducted over three growing seasons on a continuous maize (Zea Mays L.) production field in northeastern Colorado, USA. Soil samples were collected using a soil sample grid size of 76.2 m×76.2 m. The field was classified into areas of low, medium, and high productivity potential management zones. Spatial statistical analysis was performed. Measured soil parameters varied significantly over space and time (p<0.01). Management zones were effective in identifying homogenous subregions within the field across time (p<0.01). The data suggest that management zones account for spatial and temporal variability for the various soil parameters evaluated in this study.

Precision Manure Management on Site-Specific Management Zones: Topsoil Quality and Environmental Impact

Maintenance and improvement of soil quality across spatially variable soils in continuous cropping systems are critical to sustaining agricultural productivity and environmental quality. The objectives of this project were (i) to study the effects of variable-rate application of animal manure on selected topsoil quality parameters across site-specific management zones (MZs) and (ii) to evaluate the variable-rate applications of manure using risk-assessment tools of nitrogen (N) leaching and phosphorus (P) runoff indices to understand its impact on environmental quality. This study was conducted in northeastern Colorado on continuous and furrow-irrigated maize fields. Experimental strips, 4.5 m wide and 540 m long, spanned across all MZs with treatments nested within MZs in the field. Variable rates of dairy and beef feedlot manure applied on irrigated and dryland fields respectively ranged from 0 to 67 Mg ha−1. Surface soil quality parameters evaluated before and after this study included bulk density, organic matter, water-holding capacity, electrical conductivity, and particle-size analysis. Results indicate that animal manure applications of 44 and 67 Mg ha−1 significantly (P ≤ 0.05) increased soil organic matter and decreased bulk density of low- and medium-productivity-level MZs and had no significant impact on surface soil organic matter and bulk density of the high-productivity-level MZs. Animal manure significantly (P ≤ 0.05) increased surface soil water-holding capacity and soil electrical conductivity across zones; however, the maximum manure-induced soil EC was 1.0 dS m−1, which was below levels regarded as potentially harmful for maize production. Soil texture was not affected by animal manure applications. Colorado N leaching and P index indicated no environmental hazard associated with variable rate application of animal manure across MZs. This study indicates that variable-rate application of animal manure across MZs has potential to improve or maintain soil quality parameters over time without impairing the environment.

Can fluorescence based sensing detect nitrogen variability at early growth stages of maize

Early detection of nitrogen (N) variability is essential to site-specific N management for practical and physiological reasons. Current proximal sensing techniques based on reflectance do not reliably detect N variability prior to V8 growth stage of maize. Another technique based on fluorescence also offers the possibility to detect N variability. This study assessed the possibility to detect N variability in maize before V8 growth stage. An experiment was conducted in a greenhouse environment using four nitrogen rates from 0 to 225 kg/ha N equivalent. The Multiplex3® sensor was used to measure the nitrogen balance index (far-red fluorescence induced by UV divided by red fluorescence induced by either red or green light) from V4 to V8 growth stages of maize. The results obtained indicate that fluorescence sensing provides an indication of maize N variability from V5 growth stage of maize when using red excitation index.