Yield and nutrient mapping for site specific fertilizer management

Penney, D. C.; Nolan, S. C.; McKenzie, R. C.; Goddard, T. W.; Kryzanowski, L.

doi:10.1080/00103629609369631

Cited by 20 publications

(14 citation statements)

References 7 publications

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“…Within-field yield variation is typically attributed to variability in soil texture, changes in landscape position, cropping history, soil physical and chemical properties, and nutrient availability across fields (Wibawa et al, 1993;Penny 1996). However, these generalizations regarding the source of variability are not always supported by other research.…”

Section: Introductionmentioning

confidence: 92%

By-Plant Prediction of Corn Grain Yield Using Optical Sensor Readings and Measured Plant Height

Martin

Raun

Solie

2012

Journal of Plant Nutrition

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Section: Introductionmentioning

confidence: 92%

By-Plant Prediction of Corn Grain Yield Using Optical Sensor Readings and Measured Plant Height

Martin

Raun

Solie

2012

Journal of Plant Nutrition

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“…Soil characteristics vary from point to point within a field and have impact on the use, fate, and transport of chemical inputs as well as on crop yield (Jaynes et al, 1995). Mulla et al (1992) reported that soil-fertility variations can be so extensive that some portions of a field require no fertilizer application, while others require significant N or P. The large variations found in nutrient levels and crop yields support the need for variable rate fertilization (Penny et al, 1996).…”

Section: Rightsmentioning

confidence: 99%

Using Soil Attributes and Gis for Interpretation of Spatial Variability in Yield

Bakhsh¹,

Colvin²,

Jaynes³

et al. 2000

Transactions of the ASAE

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Precision farming application requires better understanding of variability in yield patterns in order to determine the cause-effect relationships. This field study was conducted to investigate the relationship between soil attributes and corn (Zea mays L.)-soybean (Glycine max L.) yield variability using four years yield data from a 22-ha field located in central Iowa. Corn was grown in this field during 1995, 1996, and 1998, and soybean was grown in 1997. Yield data were collected on nine east-west transects, consisting of 25-yield blocks per transect. To compare yield variability among crops and years, yield data were normalized based on N-fertilizer treatments. The soil attributes of bulk density, cone index, organic matter, aggregate uniformity coefficient, and plasticity index were determined from data collected at 42 soil sampling sites in the field. Correlation and stepwise regression analyses over all soil types in the field revealed that Tilth Index, based upon soil attributes, did not show a significant relationship with the yield data for any year and may need modifications. The regression analysis showed a significant relationship of soil attributes to yield data for areas of the field with Harps and Ottosen soils. From a geographic information system (GIS) analysis performed with ARC/INFO, it was concluded that yield may be influenced partly by management practices and partly by topography for Okoboji and Ottosen soils. Map overlay analysis showed that areas of lower yield for corn, at higher elevation, in the vicinity of Ottosen and Okoboji soils were consistent from year to year; whereas, areas of higher yield were variable. From GIS and statistical analyses, it was concluded that interaction of soil type and topography influenced yield variability of this field. These results suggest that map overlay analysis of yield data and soil attributes over longer duration can be a useful approach to delineate subareas within a field for site specific agricultural inputs by defining the appropriate yield classes. RightsWorks produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.This article is available at Iowa State University Digital Repository: http://lib.dr.iastate.edu/abe_eng_pubs/517 T oday's scientists are facing many challenges in developing strategies for sustainable crop production systems. The focus of earlier efforts in the 1960s increased crop yield by twofold or more by applying high-yield agricultural inputs (Bottrell and Weil, 1995). These inputs were comprised of biological inputs (crop varieties), mechanical inputs (farm mechanization), water inputs (irrigation systems), and chemical inputs. Use of chemical inputs such as herbicides, insecticides, fungicides, and fertilizers have become an integral part of the high-yield package despite some of their negative effects on the environment. This high-input strategy has been successful in narrowing the gap between food and fib...

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“…This indicated that a constant rate of N applied based on a composite sample of the field would result in over fertilization of the areas with high levels of N and under fertihzation of large areas with low levels of available N. Penney et al (1996) also refers to the fact that the cost of intensive grid sampling is high and alternative methods are needed for mapping the spatial variability of soil nutrients. According to Han et al (1994), if a field is subdivided into small enough regions (grid cells), the soill properties within the regions will be uniform, hence, application rates and actual soil productivity are closely matched.…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, a composite sample estimates the mean soil test nutrient level which does not address the variability encountered in that field (Raun et aI., 1998), Wibawa et al (1993) Penney et al (1996) also evaluated nutrient variability using grid sampling.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimum Field Element Size for Maximum Yields in Winter Wheat, Using Variable Nitrogen Rates

LaRuffa

Raun

Phillips

et al. 2001

Journal of Plant Nutrition

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Yield and nutrient mapping for site specific fertilizer management

Cited by 20 publications

References 7 publications

By-Plant Prediction of Corn Grain Yield Using Optical Sensor Readings and Measured Plant Height

By-Plant Prediction of Corn Grain Yield Using Optical Sensor Readings and Measured Plant Height

Using Soil Attributes and Gis for Interpretation of Spatial Variability in Yield

Optimum Field Element Size for Maximum Yields in Winter Wheat, Using Variable Nitrogen Rates

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