TY  - JOUR
T1  - A Deep Learning Model for Detection and Classification of Nutritional Deficiency in  Coffee Plant
AU  - Chellamanı, Umarani
AU  - Kaliaperumal, Baskaran
PY  - 2025
DA  - September
Y2  - 2025
DO  - 10.15832/ankutbd.1568929
JF  - Journal of Agricultural Sciences
JO  - J Agr Sci-Tarim Bili
PB  - Ankara University
WT  - DergiPark
SN  - 1300-7580
SP  - 960
EP  - 980
VL  - 31
IS  - 4
LA  - en
AB  - Coffee is one of the most popular beverages consumed worldwide and is also an important economic driver in agricultural economies. However, nutritional deficiencies in coffee plants have a major effect on the quality and yield of the crop. Detection of these deficiencies early and accurately is critical for effective intervention and management. In this work, we introduce a novel deep-learning framework for detection and classification of nutritional deficiencies in coffee plants. DenseNet-201, AlexNet, and MobileNet-V2 are integrated to extract discriminative features from coffee leaf images, and an attention-based feature fusion mechanism is proposed using squeeze-and-excitation blocks to improve feature representation. A differential evolution algorithm is used to optimize a Kernel extreme learning machine for learning efficiency and generalization to classify the extracted features. A benchmark dataset is used for the evaluation of the proposed model and its performance is assessed against multiple performance metrics such as accuracy, precision, recall, specificity, F1-score, and the Matthews correlation coefficient. The proposed method is compared with existing deep learning models, and it is found that the proposed method outperforms the other models with a classification accuracy of 99.50%, precision of 99.22%, recall of 99.24%, specificity of 0.9947, F1-score of 0.9957, and M correlation coefficient of 0.9908. The model is able to identify nutritional deficiencies accurately, and these results confirm the model’s effectiveness as a practical and scalable solution for precision agriculture and sustainable coffee cultivation.
KW  - Coffee plant
KW  - Nutritional deficiency detection
KW  - Deep learning
KW  - Differential evolution algorithm
KW  - Kernel extreme learning machine
KW  - Classification
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UR  - https://doi.org/10.15832/ankutbd.1568929
L1  - https://dergipark.org.tr/en/download/article-file/4294828
ER  -