2005 · 45 citations · 5 references
AgricultureComputer ScienceCrop SciencesArtificial IntelligenceMachine LearningPlant Disease DiagnosisDiagnosisDiagnosticsDisease DetectionDisease DiagnosisExpert SystemsSymptom RecognitionCrop Nutrient DiagnosisDiagnostic Expert SystemsExpert Systems For AgricultureExpert Systems For DiagnosisFlash MemoryMachine IntelligenceNeural Network-based DiagnosisNutrient Deficiency Symptom Recognition
This research aims at designing an intelligent and carry-home diagnosis expert system (ES) to help inexpert farmers detect crop nutrition disorders in time. To ensure the reasoning veracity of the system, artificial neural networks (ANN) were proposed, and a single chip computer was applied for spot using possibility. Two subsystems and their corresponding ANN clusters were created according to the location where the nutrition disorders first took place. The symptoms of six crops were collected. The confidences and conclusions of symptoms diagnosis by field experts were used as input and output neurons of ANN. Study results were saved as a knowledge base in a flash memory. Using MCS-51C language, single chip computer diagnosis was realized. Field validation indicated that diagnosis errors were less than 8%. Moreover, the combination of ANN and ES can make up traditional expert system defects and improve the systems intelligence and diagnosis efficiency.
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STATISTICAL AND NEURAL METHODS FOR SITESPECIFIC YIELD PREDICTION
Scott T. Drummond, Kenneth A. Sudduth, Anupam Joshi et al. · Transactions of the ASAE · 2003 · 201 citations · Full text
C.P. Yialouris, H.C. Passam, Alexander B. Sideridis et al. · Computers and Electronics in Agriculture · 1997 · 29 citations