Research background and significance
Precision agriculture basic research: By capturing the subtle differences in crop spectra, we deeply explore the relationship between crop physiological and biochemical processes (such as chlorophyll synthesis and water transport) and spectral characteristics, and provide data support for establishing more accurate crop growth models. Efficient use of agricultural resources: Quantify the demand and utilization efficiency of crops for water, fertilizer, and light energy, help formulate resource (such as water resources, fertilizer) optimization allocation plans, and promote sustainable agricultural development.
Equipment application introduction
1. Crop physiology and growth status monitoring
Nutrient (nitrogen, phosphorus, potassium) content estimation: Using the spectral characteristics of visible light-near infrared bands (such as red edge bands), invert the nitrogen content of crop leaves to guide precise fertilization. For example, the reflectivity of nitrogen-deficient crops in the red light band increases and the reflectivity of near infrared decreases.
2. Crop classification and planting structure analysis
Crop fine identification: Based on the spectral "fingerprints" of different crops (such as the reflectivity differences of rice, corn, and wheat in the near infrared band), large-scale farmland crop type classification is achieved to assist agricultural statistics and policy making.
3. Planting density and plant type assessment: Through canopy spectral reflectance and vegetation index (such as NDVI), analyze whether the crop planting density is reasonable and optimize field management.
3. Early detection of pests and diseases: When crops are attacked by pests and diseases, leaf pigments (such as chlorophyll) and cell structures change, and the spectrum shows abnormal absorption in the visible light band (400-700nm), which can detect diseases before the symptoms are observed by the naked eye.
Training site
