REMOTE MONITORING INDICATORS OF PLANT STRESS

Period of Performance: 01/01/1990 - 12/31/1990

$500K

Phase 2 SBIR

Recipient Firm

Agave Analytics
8726d S Sepulveda #b71
Los Angeles, CA 90045
Principal Investigator

Abstract

IN A CELSS ENVIRONMENT WHERE ALL RESOURCES INCLUDING SPACE AND LABOR ARE SCARCE IT IS ESSENTIAL THAT CROP PRODUCTION BE CONSTANTLY AND EFFICIENTLY MANAGED. DETERMINING THE HEALTH OF THE CROP QUICKLY AND ACCURATELY IS ESSENTIAL FOR GOOD CROP MANAGEMENT. THE PRESENT METHODS FOR EVALUATING CROP HEALTH DEPEND EXTENSIVELY ON PERSONAL OBSERVATION AND JUDGEMENT ALONG WITH PERIODIC DESTRUCTIVE SAMPLING. REMOTE SENSING TECHNIQUES ARE BEGINNING TO BE USED TO EXAMINE CROP GROWTH, HOWEVER DISTINGUISHING AMONG MULTIPLE STRESSES IS DIFFICULT. THE RECENT AVAILABILITY OF HIGH SPECTRAL RESOLUTION SENSORS MAY PROVIDE THE POTENTIAL FOR DISTINGUISHING INDIVIDUAL STRESSES. IN ORDER TO UTILIZE HIGH SPECTRAL RESOLUTION SENSORS FOR CROP PRODUCTION IT IS NECESSARY TO DEVELOP ALGORITHMS WHICH CHARACTERIZE INDIVIDUAL STRESSES. WE INTEND TO UTILIZE EXISTING SPECTRALDATA FROM CONTROLLED EXPERIMENTS TO DETERMINE THE FEASIBILITY OF DEVELOPING ALGORITHMS FOR EVALUATING CROP HEALTH. IF THESE ALGORITHMS ARE DEVELOPED IT WILL BE POSSIBLE TO DETERMINE THE HEALTH STATUS OF PLANTS IN REAL TIME. KNOWING HEALTH STATUS IN REAL TIME FROM SPECTRAL ALGORITHMS MAKES EFFICIENT MANAGEMENT POSSIBLE WITH THE POTENTIAL OF FULL AUTOMATION OF CROP PRODUCTION.