Pepper Nutrient Deficiency Dataset

Description This dataset comprises high-resolution RGB images of hydroponically grown pepper (Capsicum annuum L.) plants cultivated under controlled environmental conditions and subjected to specific macro- and micronutrient deficiencies. The plants were grown in climate-controlled plant growth rooms at 25°C, with a 16-hour light/8-hour dark photoperiod and 65% relative humidity. Nutrient deficiency conditions were created by removing nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), iron (Fe), and zinc (Zn) from the standard nutrient solution, respectively. Each treatment was performed in three biological replicates, and the nutrient solutions were changed weekly. Images were captured with a SONY ALPHA A7 II camera (6000 × 4000 px, 350 dpi, JPG). Images were resized to 3000 × 2000 pixels and stored in JPG format at 300 dpi. The dataset includes multiple plant morphological structures such as leaves, stems, buds, flowers, fruits, roots, back leaves, and bottom leaves.. All images have been prepared for object detection tasks; additionally, this dataset can also be used for image classification after preprocessing steps. Value of the Data High-resolution RGB images of hydroponically grown Capsicum annuum plants under well-defined macro- and micronutrient deficiency conditions. Suitable for deep learning, object detection, and early nutrient deficiency prediction. Valuable for agricultural AI and plant phenotyping research.