Traditional farming methods often rely on the human eye to evaluate crop health, quality, and environmental conditions. However, hyperspectral imaging extends our perception by capturing data across hundreds of narrow, contiguous spectral bands that go beyond the limits of human vision. Here we explore the implications of this technology in agriculture:
Visible Data Range (400 to 700 nanometers):
While hyperspectral sensors encompass wavelengths beyond human vision, they also excel in capturing data within the visible spectrum with unparalleled precision. This data range is invaluable for assessing crop health, quality, and more. It detects subtle variations in colour and pigmentation, serving as an indicator of crop stress, disease, or nutrient deficiencies.
Data Analytics:
Hyperspectral data is processed using advanced analytics and machine learning, generating actionable insights that guide data-driven decisions in crop management. These insights include the ability to pinpoint specific irregularities in crop health, detect patterns related to nutrient deficiencies, and track the progression of diseases in plants.
Enhancing Crop Quality:
With hyperspectral imagery-based decision support system, farmers can assess the quality of their crops more accurately. This is particularly significant for high-value crops like fruits and vegetables, where appearance and quality are crucial for market success. Hyperspectral imaging can analyse the spectral signature of produce, helping farmers evaluate factors such as sugar content, ripeness, and the presence of blemishes or diseases.
Diese Geschichte stammt aus der December 2023-Ausgabe von AgroSpectrum.
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