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In the last thirty years, numerous scientific revolutions have been planned to improve the ecological balance of agricultural production methods, via a considerable decrease of inorganic compounds like pesticides, synthetic plant growth hormones and fertilizers. A favorable and environment sustainable modernization should be the practice of normal plant biostimulants (PBs) which augment flowering, plant evolution, fruit formation, crop output and efficient nutrient mobilization, and ability to endure a varied array of abiotic stressors. PBs was primarily deciphered via exclusive of various functions similar to fertilizers or plant protection by-products. They are assorted constituents and microbes resorted to boost plant development. This review aimed to present the plant biostimulants definition, major classifications, and impacts on floras, soil and ecology.

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Aim: To assess the soil quality indices and its impact on rice yield in Upper Brahmaputra Valley Zone of Assam. Methodology: Seventy-three numbers of geo referenced soil samples were collected from the rice ecosystems and analysed for twenty-one soil physical, chemical and biological parameters. The soil quality indices (SQI) were developed using statistical tools like principal component analysis (PCA) techniques and expert opinion (EO). Relative soil quality index (RSQI) was also developed for grouping the soils into categories. Correlation matrices were drawn between different soil quality indices. The optimum values of soil quality indices were computed to sustain 80% or more of the existing in field maximum rice yield (5.20 t ha-1). Results: Multivariate statistics showed that four biological parameters viz., fluorescein di-acetate activity, phosphate solubilising bacteria, total bacterial population and collembolan population and three chemical parameters viz., cation exchange capacity, electrical conductivity? and diethylene tri amine penta acetic acid-Zinc could explain 70.2% of the cumulative variance. RSQI demonstrated that >50% and >30% of soils belonged to medium and good category. The regression of percent relative rice yield obtained from farmers field, illustrated that soil functions based EO-SQI could explain high degree of relationship (R2=0.289; r=0.537*), followed by RSQI (R2=0.284;r=0.532*) and PCA-SQI (R2=0.143; r=0.378*) to explain the variability of soils. The optimum value indicates that the rice soils having PCA-SQI value >0.55 were likely to give 80% or more of the maximum yield of UBVZ of Assam. Interpretation: Approaches of rating of soil quality based on PCA-SQI may be a useful tool, and there is need of more extensive investigations to validate its usefulness for assessment of soil quality in different cropping sequences of Assam.