Adding value to spatially managed inputs by understanding site‐specific yield response

By D. S. Bullock, J. Lowenberg‐DeBoer, S. Swinton. 2002

113 citations recorded by the source corpus.

Many mechanized crop producers and agribusinesses are fascinated with precision agriculture technology, but adoption has lagged behind the expectations. Among the reasons for slow adoption of precision agriculture technology is that initial users focused excessively on in-field benefits from variable-rate fertilizer application using regional average fertilizer recommendations. This article illustrates how greater use of site-specific crop response information can improve variable rate input application recommendations. Precision agriculture is spatial information technology applied to agriculture. The technologies include global position systems (GPS), geographic information systems (GIS), yield monitoring sensors, and computer controlled within-field variable rate application (VRA) equipment. Experimentation with these technologies is occurring everywhere there is large scale mechanized agriculture. Commercial use has been greatest in the US, where 43% of farm retailers offered VRA services in 2001. Except for certain high-value crops like sugar beet, farmer adoption ofVRA has been modest. The farm level profitability of VRA continues to be questionable for bulk commodity crops. The theoretical model and illustration presented here suggest that VRA fertilization has not yet reached its profitability potential. Most VRA field trials to date have relied upon existing state-wide or regional input rate recommendations. Unobserved soil characteristics can potentially interact with an input to make its effect on yield vary site-specifically within fields. Failure to use site-specific response functions for VRA applications may lead to a misallocation of inputs just as great as that which results from using uniform applications instead of VRA. Agricultural economists have a long history of estimating output response to input applications. Several have started to develop tools to estimate site-specific responses from yield monitor and other precision agriculture data. Likewise, agricultural economists have developed an important body of research results on information value based on managing variabilitytypically in temporal settings. With these tools, a major potential exists to develop further benefits from precision agriculture technologies that permit truly spatially tailored input applications. © 2002 Elsevier Science B.V. All rights reserved.

Subfields: Environmental Chemistry, Environmental Engineering, General Agricultural and Biological Sciences

View Paper: https://www.semanticscholar.org/paper/df015477b32c54894674c47de09d9c52e7f60d76

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Chemistry

1. Dayton M. Lambert
2. G. Malzer
3. J. Lowenberg‐DeBoer
4. José María Sarabia

In Environmental Engineering

1. G. Malzer
2. Dayton M. Lambert
3. J. Lowenberg‐DeBoer
4. Donald Bullock
5. G. Bollero
6. R. Bongiovanni

In General Agricultural and Biological Sciences

1. G. Malzer
2. Dayton M. Lambert
3. J. Lowenberg‐DeBoer

Citations in the corpus

• Variable rate fertilization in citrus: a long term study (2017, background): “According to Bullock et al. (2002), the use of state-wide or regional fertilizer prescriptions, instead of local input response algorithms, is often related to the failure of variable rate technology worldwide.”
• A Comparison of Four Spatial Regression Models for Yield Monitor Data: A Case Study from Argentina (2004, background): “Bullock et al. (2002) identify the lack of site-specific crop response information as a key constraint to adoption of spatial crop management.”
• Site-specific production functions for variable rate corn nitrogen fertilization (2006, background): “Unfortunately, very little research has attempted to explain the causes of this variability or to develop site-specific response functions (Bullock and Bullock 2000; Bullock et al. 2002).”
• Evaluating Management Zone Optimal Nitrogen Rates with a Crop Growth Model (2006, background): “, 2004), and information on spatial crop response variability was not sufficiently used in developing such recommendations (Hurley et al., 2001; Swinton et al., 2002; Bullock et al., 2002).”
• Economic Analysis of Spatial-Temporal Patterns in Corn and Soybean Response to Nitrogen and Phosphorus (2006, methodology): “A spatial optimization framework proposed by Bullock et al. (2002) is modified to accommodate the multi-period corn– soybean rotation.”