A novel image analysis method for identifying nutrient deficiencies in plant based on its leaf
is proposed. First, the proposed method divides an input leaf image into small blocks …

Tomato crops are one of the most important agricultural products at economic level in the
world. However, the quality of the tomato fruits is highly dependent to the growing conditions …

This paper investigates the use of various deep convolutional neural networks (CNNs) with
transfer learning to identify nutrient deficiencies from a leaf image. Experiments were …

Plants need adequate amount of nutrients for complete and healthy life-cycle. Sufficient
amount of six macronutrients like Nitrogen, Calcium, Phosphorous, Potassium, Sulphur …

Nutrient deficiency is a common condition that can spread and affect plants, if it is not
handled quickly. For this time, deficiency surveillance is carried on manually which needs …

This paper's goal is to identify nutrient deficiencies in crops by merely taking a photograph of
their leaves. The image analysis technique can identify nutrient deficiencies in the plant by …

Tomato crops are considered the most important agricultural products worldwide. However,
the quality of tomatoes depends mainly on the nutrient levels. Visual inspection is made by …

Symptoms of nutrient deficiencies in rice plants often appear on the leaves. The leaf color
and shape, therefore, can be used to diagnose nutrient deficiencies in rice. Image …

Plant nutrient deficiency classification is vital for the agricultural industry to improve both the
qualities and the quantities of crops. Computer vision and deep learning technologies …

Nutrient deficiency is one of the main causes of the decline in oil palm production. In fact, oil
palm farmers cannot diagnose the symptoms of the nutrient deficiency by themselves …