Search

The soil test value is based on the soil test-based fertilizer prescription/ recommendation equation. Each crop harvesting after the next crop is necessary to analyze the soil. Therefore, it is necessary to develop an alternative technique to predict postharvest soil tests after the harvest of every crop. For that a study was conducted in mixed black calcareous soils at Tamil Nadu agricultural University, Coimbatore to develop the post-harvest prediction equations for available nitrogen, phosphorus and potassium in barnyard millet cropping sequence based on a multiple regression model by considering post-harvest soil test value as the dependent variable and initial available nutrients, fertilizer doses and crop yield or crop nutrient uptake as an independent variables. The developed model was validated by computing R2 value, RMSE (root means square error), RE (relative error), and the ratio of performance to deviation (RPD) and the developed model was found to be valid. Using the validated model, post-harvest soil test values were predicted. A fertilizer recommendation was made for blackgram based on predicted post-harvest soil test values in the barnyard millet-blackgram cropping sequence. The predicted soil test values were compared with actual soil test values and it revealed that the developed model is fairly accurate and best-fitted with more precision. The predicted post-harvest soil test values of barnyard millet could be used in order to prescribe fertilizer for desired yield targets for subsequent crops.

Globally, drought stress causes the negative impact on agriculture production. However, microbial inoculation is the suitable cost-effective technology to attenuate the drought stress. The aim of this experiment was conducted to evaluate the impact of microbial inoculation on morpho-physiological characters of sorghum under moisture stress condition. A pot experiment with sorghum was conducted to access the role of previously identified bacterial endophyte strains. For comparison, two non-inoculated control treatments (T1: absolute control and T2: drought control) were maintained to compare the drought and inoculation effect. Drought was imposed at flowering stage and soil moisture was measure at frequent days. When the soil moisture attains close to zero, plants were rehydrated. During drought and rehydration period, plant morphological and physiological characters were evaluated. Drought stress drastically reduces the plant characters in control (T2-uninoculated) plant. Whereas, in the presence of bacterial inoculation considerably reduces the drought effect also Bacillus sp. inoculation treatment promoted better recovery during their rehydration process than absolute control. Overall, Bacillus sp. inoculation was the most promising bacterium for possible field trials.

The present investigation was undertaken to assess the spectrum of chlorophyll mutation in Hibiscus rosa-sinensis L. Cultivar Red Single and also to study the mutagenic effectiveness and efficiency in M1V1 generation of Hibiscus rosa-sinensis L. Cultivar Red Single. Semi-hardwood cuttings of Hibiscus were treated with three doses of gamma rays viz., 25, 30 and 35 Gy and three doses of EMS viz., 0.8% (64.43 mM), 0.9% (72.48 mM, 1.0% (80.54 mM) separately. Physical mutagens created a high frequency as well as a wide spectrum of chlorophyll mutants. Totally five types of chlorophyll mutant’s viz., albino, xantha, viridis, chlorina and xantha-viridis were observed as a result of physical and chemical mutation. The mutagenic effectiveness and efficiency were calculated based on biological damage as well as chlorophyll mutation frequency on M1V1 plants. Mutagenic efficiency and effectiveness were higher in gamma radiation-induced plants particularly in a lower dose of 25 Gy. The highest mutation rate in terms of effectiveness and efficiency was observed in gamma rays than the Ethyl Methane Sulphonate treatment.

Ozone stress identification in crops through remote sensing is a promising technology that has a major role in predicting stress-related physiological response. The spectral reflectance approach to phenotyping of rice cultivars is a non-destructive and accurate method to assess ozone stress. In this study, the leaf spectral reflectance of 15 rice cultivars was explored to evaluate the photosynthetic capacity under elevated ozone stress. Ozone injury percentage (OIP), a common indicator to identify ozone stress of rice leaves combined with leaf spectral signatures was used to identify the best fit spectral indices. The normalized difference spectral index (NDSI) was used to determine significant wavebands that showed the best correlation with leaf ozone injury. The correlation coefficient (r) between NDSI and OIP were ranged from -0.79 to 1. Normalized difference spectral index, NDSI[R564,R568], and NDSI[R558,R573] were identified as the best Pearson's correlation with leaf ozone injury percentage with correlation coefficient more than 0.96. The evaluated NDSI in visible regions were identified as a sensitive region to ozone injury. Additionally, results were compared with previously established indices and also evaluated for correlation with plant physiological traits. The correlation coefficient of determination (R2) > 0.5 was observed for newly developed spectral indices, NDSI[R564,R568] and NDSI[R558,R573] with physiological traits compared to previously established 20 indices. The highest R2 of 0.674 were observed for the spectral index, NDSI[R558,R573] with photosynthetic rate and R2 of 0.673 for NDSI[R564,R568] with relative chlorophyll content. As a result, the current research has implications for the selection of the best capable spectral regions for early detection of ozone stress in rice cultivars without destructing the crop. The outcome of the present work suggests that newly developed spectral indices could assist in remote sensing technology in monitoring large scale ozone stress and crop modeling studies to ensure food security.