Maqola

Seed Assessment Using Fuzzy Logic and Gas Discharge Visualization Data

Michael ArkhipovAgrophysical Research Institute, St. PetersburgElena KruegerInsight Global, Greenwood Village, CODmitry KurtenerEuropean Agrophysical Institute, AmriswilN. S. PriyatkinAgrophysical Research Institute, St. PetersburgAndrey BondarenkoSaint-Petersburg Forestry Research Institute, St. Petersburg

European Agrophysical Journaljournal2014en

ABI

Annotatsiya

Assessment of sowing material is a significant concern in seed science. A promising tool for assessing seed material is Corona Discharge Photography or Gas Discharge Visualization (GDV). In this study, this tool was applied to determine relationships between sowing material characteristics and GDV parameters; an Adaptive Neuro-Fuzzy Inference System (ANFIS) was utilized to interpret the experimental data. By using ANFIS, a three input fuzzy inference system was constructed to define the contiguous relations between GDV parameters (i.e., glow area and shape factor) and root length.

Mavzular

Leaf Properties and Growth Measurement Smart Agriculture and AI Water Quality Monitoring and Analysis

Identifikatorlar

DOI: 10.17830/j.eaj.2014.01.124

Iqtiboslar va manbalar

1 ta iqtibos 21 ta foydalanilgan manba

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