In the present paper we have used a noncontact and non-destructive laser biospeckle technique for detection, differentiation and mapping of noninfected region of a fresh Indian gooseberry and bright yellow and blue regions of a blue mold disease infected Indian gooseberry (Emblica Officinalis G.) for the first time to the best of our knowledge. Existing image processing algorithms such as Co-occurrence Matrix, Inertia Moment, Absolute Value of Differences, Fujii, Inverse Fujii, Alternative Fujii, Parameterized Fujii, Generalized Difference (GD), Parameterized GD, Alternative GD (AGD), and three newly proposed algorithms namely Cubic Absolute Difference (CAD), qFujii, Parameterized Geometrical Mean of Temporal Difference (PGMTD), have been used for this purpose. It is concluded that for detection and differentiation, CAD provides the highest value of bioactivity difference between non-infected & bright yellow (3463.81), non-infected & blue (4250.29) and bright yellow & blue (786.48) regions where as qFujii and Fujii give better results for mapping apart from detection and differentiation of the different regions. PGMTD, Alternative Fujii, Parameterized Fujii and AGD also provide quite acceptable results for detection, differentiation and mapping of the three regions. In addition, it is also found that bioactivity decreases when Indian gooseberry is infected with the pathogen and the infected blue region has lowest bioactivity compared to the infected bright yellow region.