Jitendra Rajput | INDIAN AGRICULTURAL RESEARCH INSTITUTE, NEW DELHI, INDIA (original) (raw)

Papers by Jitendra Rajput

Environment Conservation Journal/Environment conservation journal, Jan 19, 2024

Ecological Informatics, Jul 1, 2023

Review article, 2023

Planting method is the one of the important agronomic interventions for enhancing productivity an... more Planting method is the one of the important agronomic interventions for enhancing productivity and quality of sugarcane.
Right technique could enhance not only the cane yield but also input use efficiency. Increased use of better technologies,
such as planting techniques, is essential to maintaining the production and productivity of the sugar industry in an ethical way.
Additionally, it is necessary to improve the efficiency of the inputs used in sugarcane farming, particularly the prudent utilization
of water and site-specific nutrient management. Planting techniques in sugarcane play a significant role in determining the overall
productivity and sustainability of sugarcane cultivation. Proper planting techniques ensure that the sugarcane crop establishes well
and produces higher yields. New planting techniques must be made widely known to producers to make sugarcane cultivation a
sustainable and lucrative sector that contributes to national food security. Therefore, the development and adoption of enhanced
planting methods and its impact on cane productivity and input usage efficiency for sustainable sugarcane farming system are
described in this review in order to maintain cane production and its sustainability towards national food security. This review
aims to enlist the impact of different planting methods on sugarcane productivity and input use efficiency.

Inefficient management of irrigation and fertilizers emerges as the primary hurdle constraining t... more Inefficient management of irrigation and fertilizers emerges as the primary hurdle constraining the crop performance, profitability of broccoli (Brassica oleracea L. var. italica) production, resource wastage and environmental harm. To address this issue, a field experiment was conducted during winter (rabi) seasons of 2020-21 and 2021-22 at the research farm of ICAR-Indian Agricultural Research Institute, New Delhi. The research focused on investigating the effect of irrigation techniques and nitrogen management on broccoli yield, water use efficiency (WUE) and economic feasibility. The two main irrigation methods of drip irrigation and furrow irrigation as main factor, 2 irrigation regimes of full irrigation (100% ET C) and limited irrigation (75% ET C) as sub-factor, 3 nitrogen doses (N) of 125, 100 and 75% recommended dose of N as sub-sub factor were given and replicated thrice. The study aimed to analyse the yield, water use efficiency and assessment of economics under diverse irrigation water and N-management approaches. Under drip irrigation the mean yield and water-use efficiency shown substantial increase by 12 and 52% in comparison with furrow irrigated purple broccoli grown under the same condition. The highest benefit to cost (B:C) ratio of 3.81 and 4.79 was obtained in the treatment DRI 1 N 1 during 2020-21 and 2021-22, respectively. Undoubtedly, the significance of adequate irrigation regime (100% ET C) and optimal N dose (125% RDN) became apparent, as they played significant roles in enhancing crop performance and ensuring the attainment of maximum broccoli yield, WUE and economics in Trans-Gangetic Plains region.

Water Science & Technology

Crop evapotranspiration is essential for planning and designing an efficient irrigation system. T... more Crop evapotranspiration is essential for planning and designing an efficient irrigation system. The present investigation assessed the capability of four machine learning algorithms, namely, XGBoost linear regression (XGBoost Linear), XGBoost Ensemble Tree, Polynomial Regression (Polynomial Regr), and Isotonic Regression (Isotonic Regr) in modeling daily reference evapotranspiration (ET0) at IARI, New Delhi. The models were developed considering full and limited dataset scenarios. The efficacy of the constructed models was assessed against the Penman–Monteith (PM56) model estimated daily ET0. Results revealed that the under full and limited dataset conditions, XGBoost Ensemble Tree gave the best results for daily ET0 modeling during the model training period. While, in the testing period under scenarios S1(Tmax) and S2 (Tmax, and Tmin), the Isotonic Regr models yielded superior results over other models. In addition, the XGBoost Ensemble Tree models outperformed others for the rest ...

Journal of Water and Climate Change

Reference evapotranspiration (ET0) is used to determine crop water requirements under different c... more Reference evapotranspiration (ET0) is used to determine crop water requirements under different climatic conditions. In this study, soft computing tools viz. artificial neural network (ANN) and k-nearest neighbors (KNN) models were evaluated for forecasting daily ET0 by comparing their performance with the Penman-Monteith model (PM) using climatic data from 1990 to 2020 of the Indian Agricultural Research Institute (IARI) farm observatory, New Delhi, India. The performance of these models was assessed using statistical performance indices viz., mean absolute error (MAE), mean squared error (MSE), correlation coefficient (r), mean absolute percentage error (MAPE), and index of agreement (d). Results revealed that the ANN model with sigmoid activation function and L-BFGS (Limited memory-Broyden-Fletcher-Goldfarb-Shanno) learning algorithm was selected as the best performing model amongst 36 ANN models. Amongst 4 KNN models developed and tested, the K4 KNN model was observed to be the ...

Reference evapotranspiration (ET 0) is used to determine crop water requirements under different ... more Reference evapotranspiration (ET 0) is used to determine crop water requirements under different climatic conditions. In this study, soft computing tools viz. artificial neural network (ANN) and k-nearest neighbors (KNN) models were evaluated for forecasting daily ET 0 by comparing their performance with the Penman-Monteith model (PM) using climatic data from 1990 to 2020 of the Indian Agricultural Research Institute (IARI) farm observatory, New Delhi, India. The performance of these models was assessed using statistical performance indices viz., mean absolute error (MAE), mean squared error (MSE), correlation coefficient (r), mean absolute percentage error (MAPE), and index of agreement (d). Results revealed that the ANN model with sigmoid activation function and L-BFGS (Limited memory-Broyden-Fletcher-Goldfarb-Shanno) learning algorithm was selected as the best performing model amongst 36 ANN models. Amongst 4 KNN models developed and tested, the K4 KNN model was observed to be the best in forecasting daily ET 0. Overall, the best ANN model (M11) outperformed the K4 KNN model with MAE, MSE, r, MAPE, and d values of 0.075, 0.018, 0.997, 2.76 %, and 0.974, respectively and 0.091, 0.053, 0.984, 3.16 %, and 0.969, respectively during training and testing periods. Thus, we conclude that the ANN technique performed better than the KNN technique in forecasting daily ET 0. Sensitivity analysis of the best ANN model revealed that wind speed was the most influential input variable compared to other weather parameters. Thus, the ANN model to forecast daily ET 0 accurately for efficient irrigation scheduling of different crops in the study region may be recommended.

Water Resource Modeling and Computational Technologies

Faulty operation and poor upkeep of irrigation infrastructures have caused low irrigation efficie... more Faulty operation and poor upkeep of irrigation infrastructures have caused low irrigation efficiency inmany major and medium schemes globally. Low performance is mainly caused due to poor physicalcondition and low maintenance. This study was done to carry out the diagnostic and socio-economic analysisof the Bhimsagar irrigation scheme. In the diagnostic analysis, operational problems in the entire canalnetwork of Bhimsagar irrigation project were assessed by conducting several field surveys and by holdingfarmers meeting. As agriculture developmental schemes in any area cause changes in the economic conditionof farmers. The socio-economic survey was undertaken on total of 600 families engaged in agriculture andcovering 3118 persons/farmers in the scheme’s entire command area. Results revealed that water deliveryand distribution system is not satisfactory. Head reach farmers utilize more water than the middle and tailend section without considering the actual crop water demand. Overal...

ISH Journal of Hydraulic Engineering, Apr 26, 2022

Journal of Chemistry

Ascertaining water quality for irrigational use by employing conventional methods is often time t... more Ascertaining water quality for irrigational use by employing conventional methods is often time taking and expensive due to the determination of multiple parameters needed, especially in developing countries. Therefore, constructing precise and adequate models may be beneficial in resolving this problem in agricultural water management to determine the suitable water quality classes for optimal crop yield production. To achieve this objective, five machine learning (ML) models, namely linear regression (LR), random subspace (RSS), additive regression (AR), reduced error pruning tree (REPTree), and support vector machine (SVM), have been developed and tested for predicting of six irrigation water quality (IWQ) indices such as sodium adsorption ratio (SAR), percent sodium (%Na), permeability index (PI), Kelly ratio (KR), soluble sodium percentage (SSP), and magnesium hazards (MH) in groundwater of the Nand Samand catchment of Rajasthan. The accuracy of these models was determined seri...

Dams significantly impact river hydrology, mainly by changing the timing, size, and frequency of ... more Dams significantly impact river hydrology, mainly by changing the timing, size, and frequency of low and high flows, resulting in a hydrologic regime that differs significantly from the natural flow regime before the impoundment. For precise planning and judicious use of available water resources for agricultural operations and aquatic habitats, it is critical to accurately assess the dam water's temperature. The building of dams, particularly several dams in rivers, can significantly impact downstream water. In this study, we predict the daily water temperature of the Yangtze River at Cuntan. Thus, this work reveals the potential of machine learning models; namely, M5 pruned (M5P), random forest (RF), Random Subspace (RSS), and reduced error pruning tree (REPTree). The best and effectives input variables combinations were determined based on the correlation coefficient. The outputs of the various machine learning algorithm models were compared with recorded daily water temperat...

Environment Conservation Journal, 2021

Irrigation system development results in improvements of farmers' economy, followed by liveli... more Irrigation system development results in improvements of farmers' economy, followed by livelihood sustainability, standard of living and social attitude. Present analysis focused on socio-economic status of farming families in the command area of Baroda Branch Canal of Som Kamla Amba Irrigation Project. The study considered survey sampling of 10 per cent beneficiaries in the Baroda branch canal command which consisted 150 farming families having 787 persons in numbers. The socio-economic indicators viz., the family structures, employment pattern, education status, livestock ownership, farm asset distribution, cost of cultivation, and cost of returns were analysed. Results indicated that education and living standards are of farmers was low which may be one of the reasons for not adoption of newly farming technologies. Cost of cultivation per hectare for wheat, barley, gram, and mustard crops were found as Rs. 28,503.00, Rs. 26,727.00, Rs. 21,184.00 and Rs. 21,697.00, respective...

Hydrology, 2022

India’s water resources are under tremendous pressure due to elevated demand for various purposes... more India’s water resources are under tremendous pressure due to elevated demand for various purposes. The over-exploitation of these valuable resources has resulted in an imbalance in the watershed ecology. The application of spatial analysis tools in studying the morphological behaviour of watersheds has increased in recent decades worldwide due to the accessibility of the geospatial database. A morphometric analysis of a river basin is vital to determine the hydrological behaviour to develop effective management. Under the current study, morphological behaviour of Nand Samand catchment in the hard rock region was evaluated employing remote sensing (RS) and geographical information system (GIS) tools. The Nand Samand catchment (Rajasthan State, India) has an area of 865.18 km2 with the highest and lowest elevations of 1318 m and 570 m above mean sea level, respectively. This study utilises a 30 m high-spatial-resolution ASTER imagery digital elevation model for delineating the catchme...

Earth and Environmental Sciences Library, 2021

In India, agriculture contributes together with allied sectors to being the largest source of liv... more In India, agriculture contributes together with allied sectors to being the largest source of livelihoods. Farmers face a variety of biological, respiratory, noise damage, skin disorders, some cancers, chemicals related to environmental and safety problems, musculoskeletal injuries, etc. In India, there are 120 fatalities in agriculture every day. Climatic transition causes increased concern among farmers because it results in crop damage and resulting in low productivity. Drought and extreme flood events can form ecological disruptions impacting agricultural products and human health. On-farm, skin cancer is a problem because farmers spend long hours in the Sun. Most farmworkers are frequently exposed to chemicals. When they neglect to take adequate care, it may result in sickness or even death. Tractors, thresher, harvester, etc. noises are called agricultural noise which is also a major concern toward the health hazards of farmers. When the body heats more heat than it can bear, heat stress occurs. The possibilities of heat stress increase from high temperatures, high humidity, bright sunlight, and workloads. In this chapter, we are discussing the health hazards of farmers or people who work in agriculture due to agricultural activities, and to reduce or eliminate these hazards, we have tried to explain safety measures, government policies, etc. Farmers can reduce health hazards by following certain safety measures, such as sometimes a tarp or a canopy can shade a work area. Before, during, and after work, drink plenty of water and start wearing cooling vests, which are ice garments or frozen gel inserts. Give time to adapt to the workload and heat. Those are used to working in the Sun are less vulnerable to heat stress. To be adapted, work in the heat for several days in a row for around 2 h of light work a day; then slowly raise the work time and workload for the next several days. When workers are subject to noisy sounds constantly, they will have regular hearing checks. The test, called an audiogram, can show signs of loss of hearing. Once finding a hearing loss, take action to reduce exposure, thereby preventing more ear damage.

International Journal of Current Microbiology and Applied Sciences, 2020

Agronomy

Lysimetric and eddy covariance techniques are commonly used to directly estimate actual crop evap... more Lysimetric and eddy covariance techniques are commonly used to directly estimate actual crop evapotranspiration (ETa). However, these technologies are costly, laborious, and require skills which make in situ ET estimation difficult, particularly in developing countries. With this in mind, an attempt was made to determine ETa and stagewise crop coefficient (Kc) values of transplanted puddled rice using a modified non-weighing paddy lysimeter. The results were compared to indirect methods, viz., FAO Penman–Monteith and pan evaporation. Daily ETa ranged from 1.9 to 8.2 mmday−1, with a mean of 4.02 ± 1.35 mmday−1, and their comparison showed that the FAO Penman–Monteith equation performed well for the coefficient of determination (R2 of 0.63), root mean squared error (RMSE = 0.80), and mean absolute percentage error (MAPE = 13.6 %), and was highly correlated with ETa throughout the crop season. However, the pan evaporation approach was underestimated (R2 of 0.24; RMSE = 0.98; MAPE = 22....

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Ascertaining water quality for irrigational use by employing conventional methods is often time t... more Ascertaining water quality for irrigational use by employing conventional methods is often time taking and expensive due to the determination of multiple parameters needed, especially in developing countries. erefore, constructing precise and adequate models may be bene cial in resolving this problem in agricultural water management to determine the suitable water quality classes for optimal crop yield production. To achieve this objective, ve machine learning (ML) models, namely linear regression (LR), random subspace (RSS), additive regression (AR), reduced error pruning tree (REPTree), and support vector machine (SVM), have been developed and tested for predicting of six irrigation water quality (IWQ) indices such as sodium adsorption ratio (SAR), percent sodium (%Na), permeability index (PI), Kelly ratio (KR), soluble sodium percentage (SSP), and magnesium hazards (MH) in groundwater of the Nand Samand catchment of Rajasthan. e accuracy of these models was determined serially using the mean squared error (MSE), correlation coe cients (r), mean absolute error (MAE), and root mean square error (RMSE). e SVM model showed the best-t model for all irrigation indices during testing, that is, RMSE: 0.

Environment Conservation Journal/Environment conservation journal, Jan 19, 2024

Ecological Informatics, Jul 1, 2023

Review article, 2023

Planting method is the one of the important agronomic interventions for enhancing productivity an... more Planting method is the one of the important agronomic interventions for enhancing productivity and quality of sugarcane.
Right technique could enhance not only the cane yield but also input use efficiency. Increased use of better technologies,
such as planting techniques, is essential to maintaining the production and productivity of the sugar industry in an ethical way.
Additionally, it is necessary to improve the efficiency of the inputs used in sugarcane farming, particularly the prudent utilization
of water and site-specific nutrient management. Planting techniques in sugarcane play a significant role in determining the overall
productivity and sustainability of sugarcane cultivation. Proper planting techniques ensure that the sugarcane crop establishes well
and produces higher yields. New planting techniques must be made widely known to producers to make sugarcane cultivation a
sustainable and lucrative sector that contributes to national food security. Therefore, the development and adoption of enhanced
planting methods and its impact on cane productivity and input usage efficiency for sustainable sugarcane farming system are
described in this review in order to maintain cane production and its sustainability towards national food security. This review
aims to enlist the impact of different planting methods on sugarcane productivity and input use efficiency.

Inefficient management of irrigation and fertilizers emerges as the primary hurdle constraining t... more Inefficient management of irrigation and fertilizers emerges as the primary hurdle constraining the crop performance, profitability of broccoli (Brassica oleracea L. var. italica) production, resource wastage and environmental harm. To address this issue, a field experiment was conducted during winter (rabi) seasons of 2020-21 and 2021-22 at the research farm of ICAR-Indian Agricultural Research Institute, New Delhi. The research focused on investigating the effect of irrigation techniques and nitrogen management on broccoli yield, water use efficiency (WUE) and economic feasibility. The two main irrigation methods of drip irrigation and furrow irrigation as main factor, 2 irrigation regimes of full irrigation (100% ET C) and limited irrigation (75% ET C) as sub-factor, 3 nitrogen doses (N) of 125, 100 and 75% recommended dose of N as sub-sub factor were given and replicated thrice. The study aimed to analyse the yield, water use efficiency and assessment of economics under diverse irrigation water and N-management approaches. Under drip irrigation the mean yield and water-use efficiency shown substantial increase by 12 and 52% in comparison with furrow irrigated purple broccoli grown under the same condition. The highest benefit to cost (B:C) ratio of 3.81 and 4.79 was obtained in the treatment DRI 1 N 1 during 2020-21 and 2021-22, respectively. Undoubtedly, the significance of adequate irrigation regime (100% ET C) and optimal N dose (125% RDN) became apparent, as they played significant roles in enhancing crop performance and ensuring the attainment of maximum broccoli yield, WUE and economics in Trans-Gangetic Plains region.

Water Science & Technology

Crop evapotranspiration is essential for planning and designing an efficient irrigation system. T... more Crop evapotranspiration is essential for planning and designing an efficient irrigation system. The present investigation assessed the capability of four machine learning algorithms, namely, XGBoost linear regression (XGBoost Linear), XGBoost Ensemble Tree, Polynomial Regression (Polynomial Regr), and Isotonic Regression (Isotonic Regr) in modeling daily reference evapotranspiration (ET0) at IARI, New Delhi. The models were developed considering full and limited dataset scenarios. The efficacy of the constructed models was assessed against the Penman–Monteith (PM56) model estimated daily ET0. Results revealed that the under full and limited dataset conditions, XGBoost Ensemble Tree gave the best results for daily ET0 modeling during the model training period. While, in the testing period under scenarios S1(Tmax) and S2 (Tmax, and Tmin), the Isotonic Regr models yielded superior results over other models. In addition, the XGBoost Ensemble Tree models outperformed others for the rest ...

Journal of Water and Climate Change

Reference evapotranspiration (ET0) is used to determine crop water requirements under different c... more Reference evapotranspiration (ET0) is used to determine crop water requirements under different climatic conditions. In this study, soft computing tools viz. artificial neural network (ANN) and k-nearest neighbors (KNN) models were evaluated for forecasting daily ET0 by comparing their performance with the Penman-Monteith model (PM) using climatic data from 1990 to 2020 of the Indian Agricultural Research Institute (IARI) farm observatory, New Delhi, India. The performance of these models was assessed using statistical performance indices viz., mean absolute error (MAE), mean squared error (MSE), correlation coefficient (r), mean absolute percentage error (MAPE), and index of agreement (d). Results revealed that the ANN model with sigmoid activation function and L-BFGS (Limited memory-Broyden-Fletcher-Goldfarb-Shanno) learning algorithm was selected as the best performing model amongst 36 ANN models. Amongst 4 KNN models developed and tested, the K4 KNN model was observed to be the ...

Reference evapotranspiration (ET 0) is used to determine crop water requirements under different ... more Reference evapotranspiration (ET 0) is used to determine crop water requirements under different climatic conditions. In this study, soft computing tools viz. artificial neural network (ANN) and k-nearest neighbors (KNN) models were evaluated for forecasting daily ET 0 by comparing their performance with the Penman-Monteith model (PM) using climatic data from 1990 to 2020 of the Indian Agricultural Research Institute (IARI) farm observatory, New Delhi, India. The performance of these models was assessed using statistical performance indices viz., mean absolute error (MAE), mean squared error (MSE), correlation coefficient (r), mean absolute percentage error (MAPE), and index of agreement (d). Results revealed that the ANN model with sigmoid activation function and L-BFGS (Limited memory-Broyden-Fletcher-Goldfarb-Shanno) learning algorithm was selected as the best performing model amongst 36 ANN models. Amongst 4 KNN models developed and tested, the K4 KNN model was observed to be the best in forecasting daily ET 0. Overall, the best ANN model (M11) outperformed the K4 KNN model with MAE, MSE, r, MAPE, and d values of 0.075, 0.018, 0.997, 2.76 %, and 0.974, respectively and 0.091, 0.053, 0.984, 3.16 %, and 0.969, respectively during training and testing periods. Thus, we conclude that the ANN technique performed better than the KNN technique in forecasting daily ET 0. Sensitivity analysis of the best ANN model revealed that wind speed was the most influential input variable compared to other weather parameters. Thus, the ANN model to forecast daily ET 0 accurately for efficient irrigation scheduling of different crops in the study region may be recommended.

Water Resource Modeling and Computational Technologies

Faulty operation and poor upkeep of irrigation infrastructures have caused low irrigation efficie... more Faulty operation and poor upkeep of irrigation infrastructures have caused low irrigation efficiency inmany major and medium schemes globally. Low performance is mainly caused due to poor physicalcondition and low maintenance. This study was done to carry out the diagnostic and socio-economic analysisof the Bhimsagar irrigation scheme. In the diagnostic analysis, operational problems in the entire canalnetwork of Bhimsagar irrigation project were assessed by conducting several field surveys and by holdingfarmers meeting. As agriculture developmental schemes in any area cause changes in the economic conditionof farmers. The socio-economic survey was undertaken on total of 600 families engaged in agriculture andcovering 3118 persons/farmers in the scheme’s entire command area. Results revealed that water deliveryand distribution system is not satisfactory. Head reach farmers utilize more water than the middle and tailend section without considering the actual crop water demand. Overal...

ISH Journal of Hydraulic Engineering, Apr 26, 2022

Journal of Chemistry

Ascertaining water quality for irrigational use by employing conventional methods is often time t... more Ascertaining water quality for irrigational use by employing conventional methods is often time taking and expensive due to the determination of multiple parameters needed, especially in developing countries. Therefore, constructing precise and adequate models may be beneficial in resolving this problem in agricultural water management to determine the suitable water quality classes for optimal crop yield production. To achieve this objective, five machine learning (ML) models, namely linear regression (LR), random subspace (RSS), additive regression (AR), reduced error pruning tree (REPTree), and support vector machine (SVM), have been developed and tested for predicting of six irrigation water quality (IWQ) indices such as sodium adsorption ratio (SAR), percent sodium (%Na), permeability index (PI), Kelly ratio (KR), soluble sodium percentage (SSP), and magnesium hazards (MH) in groundwater of the Nand Samand catchment of Rajasthan. The accuracy of these models was determined seri...

Dams significantly impact river hydrology, mainly by changing the timing, size, and frequency of ... more Dams significantly impact river hydrology, mainly by changing the timing, size, and frequency of low and high flows, resulting in a hydrologic regime that differs significantly from the natural flow regime before the impoundment. For precise planning and judicious use of available water resources for agricultural operations and aquatic habitats, it is critical to accurately assess the dam water's temperature. The building of dams, particularly several dams in rivers, can significantly impact downstream water. In this study, we predict the daily water temperature of the Yangtze River at Cuntan. Thus, this work reveals the potential of machine learning models; namely, M5 pruned (M5P), random forest (RF), Random Subspace (RSS), and reduced error pruning tree (REPTree). The best and effectives input variables combinations were determined based on the correlation coefficient. The outputs of the various machine learning algorithm models were compared with recorded daily water temperat...

Environment Conservation Journal, 2021

Irrigation system development results in improvements of farmers' economy, followed by liveli... more Irrigation system development results in improvements of farmers' economy, followed by livelihood sustainability, standard of living and social attitude. Present analysis focused on socio-economic status of farming families in the command area of Baroda Branch Canal of Som Kamla Amba Irrigation Project. The study considered survey sampling of 10 per cent beneficiaries in the Baroda branch canal command which consisted 150 farming families having 787 persons in numbers. The socio-economic indicators viz., the family structures, employment pattern, education status, livestock ownership, farm asset distribution, cost of cultivation, and cost of returns were analysed. Results indicated that education and living standards are of farmers was low which may be one of the reasons for not adoption of newly farming technologies. Cost of cultivation per hectare for wheat, barley, gram, and mustard crops were found as Rs. 28,503.00, Rs. 26,727.00, Rs. 21,184.00 and Rs. 21,697.00, respective...

Hydrology, 2022

India’s water resources are under tremendous pressure due to elevated demand for various purposes... more India’s water resources are under tremendous pressure due to elevated demand for various purposes. The over-exploitation of these valuable resources has resulted in an imbalance in the watershed ecology. The application of spatial analysis tools in studying the morphological behaviour of watersheds has increased in recent decades worldwide due to the accessibility of the geospatial database. A morphometric analysis of a river basin is vital to determine the hydrological behaviour to develop effective management. Under the current study, morphological behaviour of Nand Samand catchment in the hard rock region was evaluated employing remote sensing (RS) and geographical information system (GIS) tools. The Nand Samand catchment (Rajasthan State, India) has an area of 865.18 km2 with the highest and lowest elevations of 1318 m and 570 m above mean sea level, respectively. This study utilises a 30 m high-spatial-resolution ASTER imagery digital elevation model for delineating the catchme...

Earth and Environmental Sciences Library, 2021

In India, agriculture contributes together with allied sectors to being the largest source of liv... more In India, agriculture contributes together with allied sectors to being the largest source of livelihoods. Farmers face a variety of biological, respiratory, noise damage, skin disorders, some cancers, chemicals related to environmental and safety problems, musculoskeletal injuries, etc. In India, there are 120 fatalities in agriculture every day. Climatic transition causes increased concern among farmers because it results in crop damage and resulting in low productivity. Drought and extreme flood events can form ecological disruptions impacting agricultural products and human health. On-farm, skin cancer is a problem because farmers spend long hours in the Sun. Most farmworkers are frequently exposed to chemicals. When they neglect to take adequate care, it may result in sickness or even death. Tractors, thresher, harvester, etc. noises are called agricultural noise which is also a major concern toward the health hazards of farmers. When the body heats more heat than it can bear, heat stress occurs. The possibilities of heat stress increase from high temperatures, high humidity, bright sunlight, and workloads. In this chapter, we are discussing the health hazards of farmers or people who work in agriculture due to agricultural activities, and to reduce or eliminate these hazards, we have tried to explain safety measures, government policies, etc. Farmers can reduce health hazards by following certain safety measures, such as sometimes a tarp or a canopy can shade a work area. Before, during, and after work, drink plenty of water and start wearing cooling vests, which are ice garments or frozen gel inserts. Give time to adapt to the workload and heat. Those are used to working in the Sun are less vulnerable to heat stress. To be adapted, work in the heat for several days in a row for around 2 h of light work a day; then slowly raise the work time and workload for the next several days. When workers are subject to noisy sounds constantly, they will have regular hearing checks. The test, called an audiogram, can show signs of loss of hearing. Once finding a hearing loss, take action to reduce exposure, thereby preventing more ear damage.

International Journal of Current Microbiology and Applied Sciences, 2020

Agronomy

Lysimetric and eddy covariance techniques are commonly used to directly estimate actual crop evap... more Lysimetric and eddy covariance techniques are commonly used to directly estimate actual crop evapotranspiration (ETa). However, these technologies are costly, laborious, and require skills which make in situ ET estimation difficult, particularly in developing countries. With this in mind, an attempt was made to determine ETa and stagewise crop coefficient (Kc) values of transplanted puddled rice using a modified non-weighing paddy lysimeter. The results were compared to indirect methods, viz., FAO Penman–Monteith and pan evaporation. Daily ETa ranged from 1.9 to 8.2 mmday−1, with a mean of 4.02 ± 1.35 mmday−1, and their comparison showed that the FAO Penman–Monteith equation performed well for the coefficient of determination (R2 of 0.63), root mean squared error (RMSE = 0.80), and mean absolute percentage error (MAPE = 13.6 %), and was highly correlated with ETa throughout the crop season. However, the pan evaporation approach was underestimated (R2 of 0.24; RMSE = 0.98; MAPE = 22....

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Ascertaining water quality for irrigational use by employing conventional methods is often time t... more Ascertaining water quality for irrigational use by employing conventional methods is often time taking and expensive due to the determination of multiple parameters needed, especially in developing countries. erefore, constructing precise and adequate models may be bene cial in resolving this problem in agricultural water management to determine the suitable water quality classes for optimal crop yield production. To achieve this objective, ve machine learning (ML) models, namely linear regression (LR), random subspace (RSS), additive regression (AR), reduced error pruning tree (REPTree), and support vector machine (SVM), have been developed and tested for predicting of six irrigation water quality (IWQ) indices such as sodium adsorption ratio (SAR), percent sodium (%Na), permeability index (PI), Kelly ratio (KR), soluble sodium percentage (SSP), and magnesium hazards (MH) in groundwater of the Nand Samand catchment of Rajasthan. e accuracy of these models was determined serially using the mean squared error (MSE), correlation coe cients (r), mean absolute error (MAE), and root mean square error (RMSE). e SVM model showed the best-t model for all irrigation indices during testing, that is, RMSE: 0.