Plant diseases are accountable for economic losses in an agricultural country. The manual process of plant diseases diagnosis is a key challenge from last one decade; therefore, researchers in this area introduced automated systems. In this research work, automated system is proposed for citrus fruit diseases recognition using computer vision technique. The proposed method incorporates five fundamental steps such as preprocessing, disease segmentation, feature extraction and reduction, fusion, and classification. The noise is being removed followed by a contrast stretching procedure in the very first phase. Later, watershed method is applied to excerpt the infectious regions. The shape, texture, and color features are subsequently computed from these infection regions. In the fourth step, reduced features are fused using serial-based approach followed by a final step of classification using multiclass support vector machine. For dimensionality reduction, principal component analysis is utilized, which is a statistical procedure that enforces an orthogonal transformation on a set of observations. Three different image data sets (Citrus Image Gallery, Plant Village, and self-collected) are combined in this research to achieving a classification accuracy of 95.5%. From the stats, it is quite clear that our proposed method outperforms several existing methods with greater precision and accuracy.
Various explants (stem, leaf, and root) of Citrus assamensis were cultured on MS media supplemented with various combinations and concentrations (0.5-2.0 mg L(-1)) of NAA and BAP. Optimum shoot and root regeneration were obtained from stem cultures supplemented with 1.5 mg L(-1) NAA and 2.0 mg L(-1) BAP, respectively. Explant type affects the success of tissue culture of this species, whereby stem explants were observed to be the most responsive. Addition of 30 gL(-1) sucrose and pH of 5.8 was most optimum for in vitro regeneration of this species. Photoperiod of 16 hours of light and 8 hours of darkness was most optimum for shoot regeneration, but photoperiod of 24 hours of darkness was beneficial for production of callus. The morphology (macro and micro) and anatomy of in vivo and in vitro/ex vitro Citrus assamensis were also observed to elucidate any irregularities (or somaclonal variation) that may arise due to tissue culture protocols. Several minor micromorphological and anatomical differences were observed, possibly due to stress of tissue culture, but in vitro plantlets are expected to revert back to normal phenotype following full adaptation to the natural environment.