Optimization of irrigation timing for sprinkler irrigation system using convolutional neural network-based mobile application for sustainable agriculture

The conventional sprinkler irrigation time calculation does not consider current soil moisture, leading to inadequate or excess irrigation due to daily weather changes. In present study, a new approach for calculating sprinkler irrigation time was proposed, which used in-field soil moisture values obtained by a convolutional neural network (CNN). To enhance accuracy and limit its size, the CNN architecture incorporated depth-wise separable convolution and residual connections. A deep-learning-based mobile application was developed, which predicted soil moisture class via in-field soil images, crop factors, and sprinkler system details. The system was assessed based on soil moisture class prediction accuracy, energy usage, water savings, and water productivity. The CNN model had an average classification accuracy of 97.10%, precision of 85.50%, recall of 86.80%, F1-score of 85.80%, and true prediction score of 75.30%. The developed mobile application saved 27.59% water and 27.42% energy by accurately estimating irrigation time using the predicted soil moisture class. The developed system corrected conventional irrigation depth in some instances, thereby reducing crop yield losses due to inadequate water supply. Compared to conventional sprinkler irrigation, the developed system increased water productivity by 32.75%. Thus, the system has the potential to conserve water and energy while improving crop yield

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Not AvailableThe conversion of primary forests to cultivation brings a significant change in soil carbon (C) forms. In the foothills of the Eastern Himalayan Region of India (Manipur), such conversions are prevalent. However, little is known about the response of C forms, particularly in deep soil, to land use conversion in the region. We evaluated changes in soil C forms (total organic, inorganic, and pools) and microbiological properties (up to 1.0 m depth) mediated by C when the 45-year-old forest had been cultivated for 18–25 years. The cultivated land uses were tree-based agroforestry (LAF: legumes, NAF: non-legumes), horticultural fruits (WHF: woody, NHF: non-wood, mainly vegetables), and paddy agriculture system (AUS: upland, ALS: lowlands). Forest conversion significantly (p 0.45 m–1.0 m). Forests converted to seasonal cultivation (upland rice and vegetables) caused higher degradation of soil C forms and overall soil health in the Himalayan foothills of northeastern India. We suggest the promotion of Agroforestry based on legumes (Parkia spp.) and woody fruits (mango/citrus/guava) in the uplands to minimize soil C degradation while ensuring nutritional security in the hill agro-ecosystems of the Indian Himalayas.Not Availabl

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Not AvailableCanopy reflectance based spectral indices help in effective irrigation scheduling of wheat for optimization of yield in water-scarce regions. A field experiment for two consecutive years (2013 to 2015) was conducted to evaluate the responses of wheat crop to exogenous application of plant bio-regulators (PBRs) in the water-scarce Deccan region of India (Baramati, Pune, Maharashtra). We predicted grain and biomass yields of wheat using water stress-sensitive spectral indices under varied water regimes. The water regimes were seven levels of irrigation water (equaling to 1.00, 0.85, 0.70, 0.55, 0.40, 0.25 and 0.10 times of cumulative open pan evaporation, CPE) and applied using a line-source sprinkler system. There were five PBRs, viz. thiourea, salicylic acid, potassium nitrate, gibberellin and ortho−silicic, with concentration 10 mM, 10 μM, 15 g L−1, 25 ppm and 8 ppm, respectively, applied at various growth stages, namely crown root initiation, flag leaf and seed milking stages. Water stress indices were computed from spectral reflectance pattern recorded at different crop growth stages using ASD FieldSpec-4 Spectroradiometer (350–2500 nm). The PBRs significantly influenced the canopy reflectance pattern and maintained superior values of water stress indices over the control (without PBRs) by stabilizing leaf pigments and water contents, controlling the stomatal opening and better water use. Among the five PBRs, thiourea and salicylic acid mitigated water stress better and improved overall grain yield (4.6–17.5%) and total biomass (3.6–15.3%). There was no significant (p < 0.05) variation in both yields (grains and biomass) up to IW: CPE 0.70, indicating that irrigation scheduling at 0.70 IW: CPE could be a better option rather than full irrigation in water-scarce areas. At flowering and milking stages, all spectral indices were correlated significantly with the wheat yields. Thus, these stages could be considered as more water-sensitive stages during entire wheat growth period. Regression models based on WI and NWI-2 accounted for 92% and 78% variation in the observed yields for grain and biomass, respectively, with minimum root-mean square error. Hence, to predict the grain and biomass yields of wheat, regression models based on WI and NWI-2 at milking stage can be used successfullyNot Availabl

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Not AvailableCanopy reflectance based spectral indices help in effective irrigation scheduling of wheat for optimization of yield in water-scarce regions. A field experiment for two consecutive years (2013 to 2015) was conducted to evaluate the responses of wheat crop to exogenous application of plant bio-regulators (PBRs) in the water-scarce Deccan region of India (Baramati, Pune, Maharashtra). We predicted grain and biomass yields of wheat using water stress-sensitive spectral indices under varied water regimes. The water regimes were seven levels of irrigation water (equaling to 1.00, 0.85, 0.70, 0.55, 0.40, 0.25 and 0.10 times of cumulative open pan evaporation, CPE) and (applied using a line-source sprinkler system). There were five PBRs, viz. thiourea, salicylic acid, potassium nitrate, gibberellin and ortho-silicic, with concentration 10 mM, 10 lM, 15 g L-1 , 25 ppm and 8 ppm, respectively, applied at various growth stages, namely crown root initiation, flag leaf and seed milking stages. Water stress indices were computed from spectral reflectance pattern recorded at different crop growth stages using ASD FieldSpec-4 Spectroradiometer (350–2500 nm). The PBRs significantly influenced the canopy reflectance pattern and maintained superior values of water stress indices over the control (without PBRs) by stabilizing leaf pigments and water contents, controlling the stomatal opening and better water useNot Availabl

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Not AvailableDolichos bean is an important hardy legume vegetable crop, grown widely in the region during August to March. The photo-insensitive line gave an advantage for year round production of the crop however the productivity is very low. Keeping in view an experiment was conducted to study the response of semi-dwarf photo-insensitive line (RCDL- 10) of dolichos bean on time of planting (May, June, July, August, September and October) and graded doses of phosphorus (30, 40, 50 and 60 kg/ha P2O5). May sowing took the least number of days to complete the physiological and developmental stages. Longest vine length, pod length and highest number of primary branches were recorded in the July sowing whereas; shortest vine length and lowest number of branches per plant was recorded in October sowing. The highest yield and yield attributes; highest total NPK uptake by the plant was observed in early planting. For higher nutrient uptake, early sowing is preferred. However, in late sown crop, there is need to apply the higher levels of phosphorus to compensate the loss of nutrient uptake. Phosphorus dose of 60 kg/ha recorded the highest yield (123.04 g/plant), total NPK uptake by the plant.Not Availabl

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Not AvailableLand-use change, particularly soil organic carbon (SOC) loss induced by shifting cultivation (jhum) is a common land degradation issue in the hilly tracts of the humid tropics. The SOC concentration comprises different pools (labile and recalcitrant fractions), and each fraction responds to temporal dynamics of adopted management practices at varying magnitudes, such as deforestation followed by cultivation. However, information on the variation of different SOC pools due to cultural practices of vegetation burning and postburn agricultural practices (crop production) associated with shifting cultivation remains inadequate. In the present investigation, we examined the effect of burning and postburning cultivation on SOC pools across different forest fallow periods at Kolasib district, Mizoram state of the north-eastern Himalayan Region of India. Results revealed increase in the soil C stocks and total organic carbon (TOC) due to the increase in the length of fallow periods ranging from 3 to 23 years. The TOC decreased significantly compared with antecedent concentrations before vegetation burning. This was mostly attributed to the reduction in contribution of active pools (very labile and labile) to TOC from 69% to 60%. However, contribution of passive pools (less labile and nonlabile) to TOC concentration increased from 31% to 40%. Postburn cultivation also resulted in reduction of TOC as well as considerable variation in the proportion of different SOC pools to TOC concentration. Among the different pools of SOC, the very labile C pool was most sensitive to land-use change induced by shifting cultivation (phytomass burning and postburn cultivation). The labile SOC pools can act as a sensitive indicator for devising suitable location specific management practices for restoration of soil health through SOC dynamics in degraded jhum lands in hilly ecosystems.Not Availabl

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