Imaging could help precision agriculture

Hyperspectral imaging is a new term that is associated with precision agriculture. It is basically a new method of measuring oxygen saturation in tissue and can help identify microvascular disease during the early phases of crops.

A team from a number of universities in China combined their capabilities and conducted research on efficient and automated data acquisition techniques, including hyperspectral imaging, and published a paper, A research review on deep learning combined with hyperspectral Imaging in multiscale agricultural sensing, on ScienceDirect. The team said their goal was to apply the “right treatment at the right time and place to achieve adaptive-precision inputs, ensure high-quality outputs, and reduce environmental impacts”.

“The acquisition and processing of crop and farmland information play a crucial role in precision agriculture. However, traditional methods of data collection and processing are slow and labour-intensive.

“Fortunately, advancements in imaging and image-processing technologies have led to the automation and intelligence of agricultural data acquisition and processing, resulting in improved efficiency and accuracy,” they wrote.

The researchers used various high-performance sensors for information acquisition.

The technique they used to extract features from hyperspectral imaging is called deep learning. They concentrated on processing agricultural data and potential solutions to enhance their techniques.

They found that their data will be invaluable to farmers in preventing failed harvests and detecting diseases much earlier. –