Modeling and prediction of below-ground performance of agricultural biological products in precision agriculture

Inactive Publication Date: 2019-02-14
DTN LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0012]In addition to agricultural biological products, environmental matching through machine learning with variables generated by customized field models may also be advantageous for identifying agricultural pests that spend a signifi

Problems solved by technology

Such field testing is a major component of the high cost and extensive time required to commercialize such biological agricultural products.
Predicting performance and writing recommendations for many agricultural biological products is more challenging and requires more extensive field testing compared to most agricultural chemical products due to greater environmental sensitivity.
Identifying the relevance of different and temporally-variant environment factors is also complicated when the product itself is a living organism that is strongly influenced by environment, and activity is slower and efficacy is lower as compared to optimal environ

Method used

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  • Modeling and prediction of below-ground performance of agricultural biological products in precision agriculture
  • Modeling and prediction of below-ground performance of agricultural biological products in precision agriculture

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Embodiment Construction

[0022]In the following description of the present invention reference is made to the exemplary embodiments illustrating the principles of the present invention and how it is practiced. Other embodiments will be utilized to practice the present invention and structural and functional changes will be made thereto without departing from the scope of the present invention.

[0023]The present invention is a below-ground agricultural biological performance model 100 for performing sub-surface assessments of a soil state, and for generating recommendations for agricultural activity from such assessments. This below-ground agricultural biological performance model 100 presents multiple approaches for analyzing agricultural biological performance in precision agriculture, and is embodied in one or more systems and methods that at least in part include developing one or more customized field models, and one or more machine learning and artificial intelligence models, that together represent a s...

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Abstract

A below-ground agricultural biological performance modeling approach in precision agriculture combines customized field modeling with machine learning techniques for environmental matching of variables to describe a below-surface soil state, to understand and predict the performance of soil-active agricultural biological products such as bio-pesticides, bio-stimulants, plant growth regulators, and other biologically-derives soil adjuvants. The modeling approach characterizes the influence of environmental relationships on the performance of such soil-active agricultural biological products to develop a suite of predictive models to provide notifications, advisories, and recommendations for appropriate products for individual fields.

Description

FIELD OF THE INVENTION[0001]The present invention relates to the field of precision agriculture. Specifically, the present invention relates to a system and method of assessing the impact of biological processes in a soil system, based on correlated relationships between environmental variables, to predict a future below-ground performance of soil-active agricultural biological products.BACKGROUND OF THE INVENTION[0002]Agricultural biologicals are products derived from or composed of living organisms that are used in agriculture to enhance plant productivity and fertility or to provide protection from pests and diseases. Such products inhibit or mitigate the effects of organisms or environmental conditions that have adverse consequences on crop growth, vigor, or yield, or that stimulate crop growth, vigor, or yield, either directly or through effects on an intermediary substance or organism. They include bio-pesticides such as fungi, bacteria and other organisms that help protect pl...

Claims

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Application Information

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IPC IPC(8): G06N5/04G06F17/50G06N99/00G01S19/14G01N33/24A01G1/00
CPCA01G22/00G06N5/04G06N20/00G01S19/14G01N33/24G06F17/5004A01B79/005G01S19/42Y02A40/10G06F30/13A01C21/007
Inventor MEWES, JOHN J.HALE, ROBERT C.
Owner DTN LLC
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