ABSTRACT Effect of cropping systems (CS) on the soil quality (SQ) and its determinants was assess... more ABSTRACT Effect of cropping systems (CS) on the soil quality (SQ) and its determinants was assessed for the clay loam soil of Hisar, India. Collected surface soil samples were analyzed for four physical indicators viz. bulk density (BD), saturated hydraulic conductivity (SHC), porosity and mean weight diameter (MWD) seven chemical indicators viz. pH, electrical conductivity (EC), organic carbon (OC), nitrate nitrogen (NO3-N), ammoniacal nitrogen (NH4-N), available phosphorous (AV-P) and available potassium (AV-K) and two biological ...
Puddling is known to increase the yield of rice due to the creation of suitable physical environm... more Puddling is known to increase the yield of rice due to the creation of suitable physical environment that favours growth of the crop. However, in rice–wheat system, wheat yield has been reported to decrease due to the deterioration of soil structure caused by puddling in rice. This affects seedling emergence in wheat. Seedling emergence model that predicts seedling emergence and
ABSTRACT Soil physical quality is one of the three important aspects of soil quality, besides bio... more ABSTRACT Soil physical quality is one of the three important aspects of soil quality, besides biological and chemical quality. Decline in soil physical quality can have serious consequences on biological and chemical properties thereby making it relevant to study soil physical quality for maintaining soil health in long run. Changes in this property of soil affect the productivity of crops. In this investigation, Dexter S theory has been applied to evaluate the soil physical quality in maize-wheat system under two tillage/land configurations namely raised bed planting (BP) and conventional tillage (CT) and nine nutrient treatments viz (1) T-1-control (crop without fertilizer), (2) T-2-100 % recommended dose of nitrogen (N), phosphorous (P) and potassium (K), (3) T-3-100 % NPK (25 % N substituted by farmyard manure (FYM)), (4) T-4-100 % NPK + green manure (Sesbania), (5) T-5-100 % NPK (25 % N substituted by biofertilizer), (6) T-6-100 % NPK (25 % N substituted by sewage sludge), (7) T-7-100 % NPK + crop residue incorporated (from previous crop), (8) T-8-100 % organic source (50 % FYM + 25 % bio-fertilizer + 25 % crop residue), and (9) T-9-no crop no fertilizer; were identified for this study. BP significantly improved the soil physical quality compared to CT. Within nutrient treatments, S index was highest in T-8 followed by the T-5, whereas lowest in T-1. There is high and significant correlation between S index and soil physical parameter and crop yield which shows that S index can be used effectively for quantifying soil physical quality under diverse environments vis-A -vis crop yield.
Soil compaction may restrict deep root growth and adversely affect plant access to sub-soil layer... more Soil compaction may restrict deep root growth and adversely affect plant access to sub-soil layer. Therefore it is important to study rooting behaviour of crops to soil compaction that are imparted on it naturally or artificially. The objective of this study was to determine the effect of soil compaction levels by varying the soil bulk density (BD) on rooting parameters and to model the root growth to understand the dynamics of rooting behaviour of chickpea (Cicer arietinum L.). Compaction level treatments, i.e. BDs were (i) 1.2, (ii) 1.4, (iii) 1.5 and (iv) 1.6 Mg/m3. When BD was increased from 1.2 Mg/m3 to 1.6 Mg/m3, there was 58% and 44% reduction in plant height of JG 11 and JG 130, respectively. There was 59% and 45% reduction in root length of JG 11 and JG 130, with increase in BD from 1.2 Mg/ m3 to 1.6 Mg/m3. On an average, an increase in BD by 0.1 unit resulted in 19.34 and 19.11% decrease in root main axis length of JG 11 and JG 130, respectively. There was a negative correlation between root penetration rate and soil BD (R2 = 0.88). The critical growth limiting BD for chickpea was found to be 1.89 Mg/m3 in our study. The logistic growth model was fitted well with the observed dataset obtained from study with R2 of 0.98** (P < 0.01). In this study, the chickpea variety JG 130 proved to be better than JG 11 while selecting chickpea cultivars for highly compacted soils.
The frequency, size and rate of development of cracks influence the transport of water, nutrients... more The frequency, size and rate of development of cracks influence the transport of water, nutrients and gases in the soil profile and plant growth processes in Vertisols. Despite their importance, studies on characterising cracks in Vertisols of India are limited. This study attempts to evaluate the influence of different tillage practices, nutrient management and cropping systems on cracking behaviour of aVertisol in central India. The length, depth, width, area and volume of cracks were recorded after the harvest of the wet season crops, i.e. soybean (Glycine max L.) and rice (Oryza sativa L.) from three ongoing tillage experiments with three different cropping systems, i.e. soybean–wheat (Triticum aestivum L.), soybean–linseed (Linum usitatissimum L.) and rice–wheat. The results revealed that all the crack parameters were significantly negatively correlated with the water content of the 0–15 cm soil layer and, crack width and crack volume were significantly positively correlated with the bulk density of the 0–15 cm soil layer. Gravimetric water content and bulk density of the 0–15 cm soil layer together explained 79% variation in the crack volume. The crack volume was significantly negatively correlated (r = 0.86, P = 0.01) with the root length density of the previous soybean crop. Rice grown under puddled condition significantly enhanced different crack parameters viz., length, depth, width, surface area and volume of the cracks over nonpuddled direct seeded rice. Sub-soiling practised in soybean under the soybean–linseed system significantly reduced the width, depth, length and surface area of cracks by 12.5, 10, 5 and 12%, respectively, over conventional tillage. No tillage practised in soybean under soybean–wheat system resulted in significant increase in width, depth and volume of the cracks but decrease in length and surface area of cracks over conventional tillage and mould board tillage practice. Application of manure reduced the magnitude of different crack parameters in soybean–linseed cropping system. Thus cracking in Vertisols can be favourably managed by the selection of proper tillage practice, cropping system and organic manure amendments.
Soybean [Glycine max (L.) Merrill] has emerged as one of the major rainy
season oilseed cash crop... more Soybean [Glycine max (L.) Merrill] has emerged as one of the major rainy season oilseed cash crops in central India. Despite its phenomenal growth in this agro-climatic zone, the average productivity of soybean has remained more or less at 1 t ha 1 due to several abiotic, biotic and socio-economic factors. The climate change (increase in temperature, CO2 concentration and rainfall) will affect this rainfed crop in the future. So, proper management practices which include crop management (use of nutrients, planting time and plant population) will play a major role in future productivity in these regions. Simulation models with demonstrated accuracy and reliability provide an alternative method of investigating both short- and long-term agricultural practices with less time requirements and low cost. They have been evaluated and used as a research tool to study risks associated with various management strategies and to assist in decision-making. Hence, the present study aims at using the APSIM model in the decision-making process to evaluate the impact of climate change on soybean yield. For the simulation study, the optimum date of sowing was chosen based on the literature available for this region. A well-calibrated and validated APSIM model was used for a long-term simulation study on the impact of rainfall pattern on soybean yield. The long-term prediction revealed that there was an interannual variation in soybean yield due to the variation in rainfall pattern. The distribution of rainfall rather than the amount during the soybean growing season is important for soybean yield. There was a significant decrease in soybean yield (as high as 96 %) when the rainfall receded during the initiation of flowering to maximum pod stage. The yield reduction was 56 % when a drought spell of around 2 weeks occurs during mid-vegetative stage. There was a significant decrease in yield (37 %) from the maximum when the drought spell occurs at some parts of the growing season. The validated APSIMmodel was also used to simulate the impact of climate change on soybean production in central India. The projected temperature scenarios for the Indian subcontinent as reported by IPCC have been used in the present study. There was a decrease (ranging between 20 and 35 %) in soybean yield when the effect of the rise in surface air temperature during soybean growing season was considered. The simulation results obtained on the mitigatory option for reducing the negative impacts of temperature increases indicate that delaying the sowing dates would be favourable for increased soybean yields for this region. This will help in recommending a better alternative management options to improve the productivity of soybean in the region.
The quality of farmyard manure (FYM) prepared by farmers by traditional method is poor due to los... more The quality of farmyard manure (FYM) prepared by farmers by traditional method is poor due to loss of nutrients during its preparation and low nutrient content of inputs. Earlier studies showed that the groundwater collected from habitation areas contained higher concentration of nitrates than those of field areas which was attributed to movement of nutrients from FYM pits to nearby water sources. But little quantitative data exist on nutrient mass balances or their losses via leaching. To address these shortcomings, a study was conducted on a representative, traditional FYM pit in Geelakhedi village, Madhya Pradesh. Cattle dung was the main component of FYM (67%) followed by cattle shed waste (20%); ash, household sweepings, and vegetable waste were minor components. A total of 3700 kg of FYM was produced from the 5760 kg of materials that were put into the pit. Importantly, 39% of the N, 20% of the P and 32% of the K inputs were lost during the preparation of FYM. Nutrients capture on exchange resin cores showed that at least 27% of the N, 30% of the P and 50% of the K were lost through leaching. Further studies are needed to improve accuracy and to determine losses through other mechanisms. Despite nutrient losses, FYM is an important resource that could be even more valuable with reduced nutrient losses.
Pedotransfer functions (PTFs) for estimation of soil water retention at field capacity (θFC, -33 ... more Pedotransfer functions (PTFs) for estimation of soil water retention at field capacity (θFC, -33 kPa) and permanent wilting point (θPWP, -1500 kPa) were developed under three soil categories (<20%, 20-40% and >40% clay) through linear, log-linear and stepwise-regression (SR) approach, using particle size distribution and bulk density data. Under <20% clay, the log-linear model was better than other models in predicting θFC, whereas SR model was better for predicting θPWP. Under 20-40% clay category, all the three approaches predicted θFC with equal efficiency, while SR was superior for θPWP. The log-linear models performed better in predicting both the θFC and θPWP with >40% soil clay.
Abstract A series of long-term simulations were carried
out to investigate alternative management... more Abstract A series of long-term simulations were carried out to investigate alternative management practices to increase grain yields of soybean and wheat by optimizing sowing dates, nitrogen (N) and water requirements, along with complimenting farmyard manure (FYM) as a N source in the soybean–wheat cropping system of Madhya Pradesh. The APSIM simulation study showed that the mean soybean yield ranged from 1.0 to 1.6 t ha-1 for the different dates of sowing. The average wheat grain yield was 3.2–3.9 t ha-1, whereas, the crop sown on 15 November gave the highest yield. In this region, there is a potential to increase soybean and wheat yields by 0.6 and 2.2 t ha-1, respectively. Among the various irrigation practices simulated, five irrigations of 60 mm at 20 days interval was the best option for wheat. Application of 16 t FYM ha-1 to soybean produced 50 % higher wheat yield than the same amount of FYM applied to wheat. The wheat yield obtained from inorganic application of N was at par with that obtained from the application of integrated and organic sources. However, the amount of N loss from the integrated use of fertilizer N was lower than that from the current recommended practice for the region. Application of FYM alone or in combination with inorganic fertilizer maintained higher soil organic carbon concentration as compared to the application of inorganic fertilizer alone. Thus, the model provided a mean of evaluating alternative crop N and water management options for effectively managing the soybean–wheat cropping system.
In
recent
years,
nutrient
management
of
soybean–wheat
systems
in
central
India
has
be... more In recent years, nutrient management of soybean–wheat systems in central India has become a cause for concern because of stagnation of grain yields of soybean and wheat. The reduction in grain yield was mainly attributed to a suboptimal supply of nutrients to both the crops, use of poor quality farmyard manures and erratic distribution of rainfall during soybean’s growing season and unavailability of irri- gation water during wheat season. In this connection, the crop growth simulation models are handy in identifying the constraints to yield and recommending appropriate management practices to optimize the productivity of soybean–wheat system. To achieve this, the APSIM model was parameterized and validated for soybean and wheat crop of subtropical central India. Independent data set was used to parameterize soybean cultivar (JS 335) and wheat cultivar (Sujata) to be used for APSIM simulation. Genetic coefficient generated from this study was used for subsequent model validation. The data on water use, N uptake, grain yield and soil organic C from an ongoing long- term experiment was used for validation purpose. Three nutrient treatments, viz., control (no nutrient), inorganic (recommended rate) and FYM (8 t ha−1 to soybean and 16 t ha−1 to wheat) were used to validate the APSIM model. For organic treatments, we simulated N management using the FYM as the source of plant available N under field condition. The model was parameterized by specifying the N mineralized from the manure in the laboratory incubation. The model predicted successfully grain yield and N uptake under FYM treatments in soybean and wheat. For other treatments, model prediction was satisfactory in most of the cases in simulating water and organic carbon, grain yield and N uptake by both the crops. The discrepancy observed between the observed and predicted yield in the control under soybean was due to the P limiting condition of the treatment rather than the model. The predicted variability of crop yield was also due to the variation of weather during soybean growing season and amount of irrigation and N used during wheat growing season. Therefore, this APSIM simulation study can satisfactorily be used to make appropriate management decisions to provide farmers and others with alternative options for nutrient management for soybean–wheat cropping systems.
Predicting N mineralization from organic manures like farmyard manure (FYM) is more difficult than... more Predicting N mineralization from organic manures like farmyard manure (FYM) is more difficult than from fresh organic materials like crop residues, as the manures vary greatly in composition. A laboratory incubation experiment was carried out for 98 days at 30◦C under aerobic conditions to study the effects on N dynamics of Gliricidia (Gliricidia sepium, Jacquin) and FYM application to soil at 5 and 10gkg−1. ApplicationofGliricidiainducedNmineralizationfromthestartofincubationperiod,withtheamountofN mineralizedincreasingwithrateofapplication.Incontrast,applicationofFYMresultedinimmobilization of mineral N in soil, irrespective of the rate of application. The initial net immobilization from FYM was limited by availability of N in the soil for the higher rate of application. We used the APSIM SoilN module to simulate these contrasting patterns of mineralization of N from Gliricidia and from FYM. The prediction of N mineralized from Gliricidia was better than FYM. The default model parameters specify that the fresh organic matter pools (FPOOL1, FPOOL2 and FPOOL3) have the same C:N ratio and this assumption was ineffective in predicting N mineralized from FYM. The predictive ability of the model improved when this default assumption was modified based on the size of the individual pools (FPOOL1, FPOOL2 and FPOOL3), and the pool’s C:N ratios. The modelling efficiency, a measure of goodness of fit between the simulated and observed data, improved markedly for the modified model. The discrepancy between the modelled and observed data was a tendency for the model to underestimate the rate of re-mineralization at the lower rate of application of FYM in the later part of incubation. Unfortunately the appropriate modification to the size and C:N ratios of the FPOOLs could not be determined on the basis of chemical analysis alone. Thus, a true predictive application of the model to a new FYM material is not yet possible.
A laboratory incubation experiment was carried out for 98 days at 30ºC under aerobic conditions ... more A laboratory incubation experiment was carried out for 98 days at 30ºC under aerobic conditions to study the effects of rice (Oryza sativa, L.) and wheat (Triticum aestivum, L.) straw applied at 5 and 10 g kg-1 in the presence or absence of additional N (as urea). The study showed an interactive effect between the rate of appli- cation of the residues and additional N. Without additional N, the mineral N in soil was completely immobilized within two weeks irrespective of the rate of application; initial net immobilization was limited by the availability of N and was independent of residue rate. When additional N was supplied, initial net immobilization was dependent on the rate of application of the residue. We used the APSIM SoilN module to simulate N mineralization from high C:N ratio crop residues, and compared the predictions with the observed data from our incubation study. Model performance was generally satisfactory, and the model was able to simulate the observed interaction between rate of application of residue and added N. The modelling efficiency, a measure of goodness of fit between the simulation and observed data, was 0.82 for the treatments in the incubation study. The major discrepancy between the model and the observed data was a tendency for the model to underestimate the initial rate of immobilization.
Tillage and residue management practices are known to affect seedling emergence and growth. Howev... more Tillage and residue management practices are known to affect seedling emergence and growth. However, information on direct seeded rice (Oryza sativa L.) in rice–wheat (Triticum spp.) cropping system is lacking. Thus a study was undertaken under different tillage (conventional and zero tillage) and residue (residue-retained and removed) management options on rice seedling emergence and growth in rice–wheat system on a Vertisol of Central India. Seedling emergence was greater in residue removed plots compared to residue-retained one. Prediction of rice seedling emergence with the France and Thornley [Mathematical Models in Agriculture and Related Sciences, Butterworths, London, 1984] model and growth by the Logistic and Gompertz model, and Monomolecular model were also attempted. Emergence indicators showed that seedling emergence of rice was favored more by conventional tillage than zero tillage in wheat. Of the three models tested, the Gompertz model gave the best fit. The effect of tillage and residue of wheat on the estimated parameters of the models were also studied.
ABSTRACT Effect of cropping systems (CS) on the soil quality (SQ) and its determinants was assess... more ABSTRACT Effect of cropping systems (CS) on the soil quality (SQ) and its determinants was assessed for the clay loam soil of Hisar, India. Collected surface soil samples were analyzed for four physical indicators viz. bulk density (BD), saturated hydraulic conductivity (SHC), porosity and mean weight diameter (MWD) seven chemical indicators viz. pH, electrical conductivity (EC), organic carbon (OC), nitrate nitrogen (NO3-N), ammoniacal nitrogen (NH4-N), available phosphorous (AV-P) and available potassium (AV-K) and two biological ...
Puddling is known to increase the yield of rice due to the creation of suitable physical environm... more Puddling is known to increase the yield of rice due to the creation of suitable physical environment that favours growth of the crop. However, in rice–wheat system, wheat yield has been reported to decrease due to the deterioration of soil structure caused by puddling in rice. This affects seedling emergence in wheat. Seedling emergence model that predicts seedling emergence and
ABSTRACT Soil physical quality is one of the three important aspects of soil quality, besides bio... more ABSTRACT Soil physical quality is one of the three important aspects of soil quality, besides biological and chemical quality. Decline in soil physical quality can have serious consequences on biological and chemical properties thereby making it relevant to study soil physical quality for maintaining soil health in long run. Changes in this property of soil affect the productivity of crops. In this investigation, Dexter S theory has been applied to evaluate the soil physical quality in maize-wheat system under two tillage/land configurations namely raised bed planting (BP) and conventional tillage (CT) and nine nutrient treatments viz (1) T-1-control (crop without fertilizer), (2) T-2-100 % recommended dose of nitrogen (N), phosphorous (P) and potassium (K), (3) T-3-100 % NPK (25 % N substituted by farmyard manure (FYM)), (4) T-4-100 % NPK + green manure (Sesbania), (5) T-5-100 % NPK (25 % N substituted by biofertilizer), (6) T-6-100 % NPK (25 % N substituted by sewage sludge), (7) T-7-100 % NPK + crop residue incorporated (from previous crop), (8) T-8-100 % organic source (50 % FYM + 25 % bio-fertilizer + 25 % crop residue), and (9) T-9-no crop no fertilizer; were identified for this study. BP significantly improved the soil physical quality compared to CT. Within nutrient treatments, S index was highest in T-8 followed by the T-5, whereas lowest in T-1. There is high and significant correlation between S index and soil physical parameter and crop yield which shows that S index can be used effectively for quantifying soil physical quality under diverse environments vis-A -vis crop yield.
Soil compaction may restrict deep root growth and adversely affect plant access to sub-soil layer... more Soil compaction may restrict deep root growth and adversely affect plant access to sub-soil layer. Therefore it is important to study rooting behaviour of crops to soil compaction that are imparted on it naturally or artificially. The objective of this study was to determine the effect of soil compaction levels by varying the soil bulk density (BD) on rooting parameters and to model the root growth to understand the dynamics of rooting behaviour of chickpea (Cicer arietinum L.). Compaction level treatments, i.e. BDs were (i) 1.2, (ii) 1.4, (iii) 1.5 and (iv) 1.6 Mg/m3. When BD was increased from 1.2 Mg/m3 to 1.6 Mg/m3, there was 58% and 44% reduction in plant height of JG 11 and JG 130, respectively. There was 59% and 45% reduction in root length of JG 11 and JG 130, with increase in BD from 1.2 Mg/ m3 to 1.6 Mg/m3. On an average, an increase in BD by 0.1 unit resulted in 19.34 and 19.11% decrease in root main axis length of JG 11 and JG 130, respectively. There was a negative correlation between root penetration rate and soil BD (R2 = 0.88). The critical growth limiting BD for chickpea was found to be 1.89 Mg/m3 in our study. The logistic growth model was fitted well with the observed dataset obtained from study with R2 of 0.98** (P < 0.01). In this study, the chickpea variety JG 130 proved to be better than JG 11 while selecting chickpea cultivars for highly compacted soils.
The frequency, size and rate of development of cracks influence the transport of water, nutrients... more The frequency, size and rate of development of cracks influence the transport of water, nutrients and gases in the soil profile and plant growth processes in Vertisols. Despite their importance, studies on characterising cracks in Vertisols of India are limited. This study attempts to evaluate the influence of different tillage practices, nutrient management and cropping systems on cracking behaviour of aVertisol in central India. The length, depth, width, area and volume of cracks were recorded after the harvest of the wet season crops, i.e. soybean (Glycine max L.) and rice (Oryza sativa L.) from three ongoing tillage experiments with three different cropping systems, i.e. soybean–wheat (Triticum aestivum L.), soybean–linseed (Linum usitatissimum L.) and rice–wheat. The results revealed that all the crack parameters were significantly negatively correlated with the water content of the 0–15 cm soil layer and, crack width and crack volume were significantly positively correlated with the bulk density of the 0–15 cm soil layer. Gravimetric water content and bulk density of the 0–15 cm soil layer together explained 79% variation in the crack volume. The crack volume was significantly negatively correlated (r = 0.86, P = 0.01) with the root length density of the previous soybean crop. Rice grown under puddled condition significantly enhanced different crack parameters viz., length, depth, width, surface area and volume of the cracks over nonpuddled direct seeded rice. Sub-soiling practised in soybean under the soybean–linseed system significantly reduced the width, depth, length and surface area of cracks by 12.5, 10, 5 and 12%, respectively, over conventional tillage. No tillage practised in soybean under soybean–wheat system resulted in significant increase in width, depth and volume of the cracks but decrease in length and surface area of cracks over conventional tillage and mould board tillage practice. Application of manure reduced the magnitude of different crack parameters in soybean–linseed cropping system. Thus cracking in Vertisols can be favourably managed by the selection of proper tillage practice, cropping system and organic manure amendments.
Soybean [Glycine max (L.) Merrill] has emerged as one of the major rainy
season oilseed cash crop... more Soybean [Glycine max (L.) Merrill] has emerged as one of the major rainy season oilseed cash crops in central India. Despite its phenomenal growth in this agro-climatic zone, the average productivity of soybean has remained more or less at 1 t ha 1 due to several abiotic, biotic and socio-economic factors. The climate change (increase in temperature, CO2 concentration and rainfall) will affect this rainfed crop in the future. So, proper management practices which include crop management (use of nutrients, planting time and plant population) will play a major role in future productivity in these regions. Simulation models with demonstrated accuracy and reliability provide an alternative method of investigating both short- and long-term agricultural practices with less time requirements and low cost. They have been evaluated and used as a research tool to study risks associated with various management strategies and to assist in decision-making. Hence, the present study aims at using the APSIM model in the decision-making process to evaluate the impact of climate change on soybean yield. For the simulation study, the optimum date of sowing was chosen based on the literature available for this region. A well-calibrated and validated APSIM model was used for a long-term simulation study on the impact of rainfall pattern on soybean yield. The long-term prediction revealed that there was an interannual variation in soybean yield due to the variation in rainfall pattern. The distribution of rainfall rather than the amount during the soybean growing season is important for soybean yield. There was a significant decrease in soybean yield (as high as 96 %) when the rainfall receded during the initiation of flowering to maximum pod stage. The yield reduction was 56 % when a drought spell of around 2 weeks occurs during mid-vegetative stage. There was a significant decrease in yield (37 %) from the maximum when the drought spell occurs at some parts of the growing season. The validated APSIMmodel was also used to simulate the impact of climate change on soybean production in central India. The projected temperature scenarios for the Indian subcontinent as reported by IPCC have been used in the present study. There was a decrease (ranging between 20 and 35 %) in soybean yield when the effect of the rise in surface air temperature during soybean growing season was considered. The simulation results obtained on the mitigatory option for reducing the negative impacts of temperature increases indicate that delaying the sowing dates would be favourable for increased soybean yields for this region. This will help in recommending a better alternative management options to improve the productivity of soybean in the region.
The quality of farmyard manure (FYM) prepared by farmers by traditional method is poor due to los... more The quality of farmyard manure (FYM) prepared by farmers by traditional method is poor due to loss of nutrients during its preparation and low nutrient content of inputs. Earlier studies showed that the groundwater collected from habitation areas contained higher concentration of nitrates than those of field areas which was attributed to movement of nutrients from FYM pits to nearby water sources. But little quantitative data exist on nutrient mass balances or their losses via leaching. To address these shortcomings, a study was conducted on a representative, traditional FYM pit in Geelakhedi village, Madhya Pradesh. Cattle dung was the main component of FYM (67%) followed by cattle shed waste (20%); ash, household sweepings, and vegetable waste were minor components. A total of 3700 kg of FYM was produced from the 5760 kg of materials that were put into the pit. Importantly, 39% of the N, 20% of the P and 32% of the K inputs were lost during the preparation of FYM. Nutrients capture on exchange resin cores showed that at least 27% of the N, 30% of the P and 50% of the K were lost through leaching. Further studies are needed to improve accuracy and to determine losses through other mechanisms. Despite nutrient losses, FYM is an important resource that could be even more valuable with reduced nutrient losses.
Pedotransfer functions (PTFs) for estimation of soil water retention at field capacity (θFC, -33 ... more Pedotransfer functions (PTFs) for estimation of soil water retention at field capacity (θFC, -33 kPa) and permanent wilting point (θPWP, -1500 kPa) were developed under three soil categories (<20%, 20-40% and >40% clay) through linear, log-linear and stepwise-regression (SR) approach, using particle size distribution and bulk density data. Under <20% clay, the log-linear model was better than other models in predicting θFC, whereas SR model was better for predicting θPWP. Under 20-40% clay category, all the three approaches predicted θFC with equal efficiency, while SR was superior for θPWP. The log-linear models performed better in predicting both the θFC and θPWP with >40% soil clay.
Abstract A series of long-term simulations were carried
out to investigate alternative management... more Abstract A series of long-term simulations were carried out to investigate alternative management practices to increase grain yields of soybean and wheat by optimizing sowing dates, nitrogen (N) and water requirements, along with complimenting farmyard manure (FYM) as a N source in the soybean–wheat cropping system of Madhya Pradesh. The APSIM simulation study showed that the mean soybean yield ranged from 1.0 to 1.6 t ha-1 for the different dates of sowing. The average wheat grain yield was 3.2–3.9 t ha-1, whereas, the crop sown on 15 November gave the highest yield. In this region, there is a potential to increase soybean and wheat yields by 0.6 and 2.2 t ha-1, respectively. Among the various irrigation practices simulated, five irrigations of 60 mm at 20 days interval was the best option for wheat. Application of 16 t FYM ha-1 to soybean produced 50 % higher wheat yield than the same amount of FYM applied to wheat. The wheat yield obtained from inorganic application of N was at par with that obtained from the application of integrated and organic sources. However, the amount of N loss from the integrated use of fertilizer N was lower than that from the current recommended practice for the region. Application of FYM alone or in combination with inorganic fertilizer maintained higher soil organic carbon concentration as compared to the application of inorganic fertilizer alone. Thus, the model provided a mean of evaluating alternative crop N and water management options for effectively managing the soybean–wheat cropping system.
In
recent
years,
nutrient
management
of
soybean–wheat
systems
in
central
India
has
be... more In recent years, nutrient management of soybean–wheat systems in central India has become a cause for concern because of stagnation of grain yields of soybean and wheat. The reduction in grain yield was mainly attributed to a suboptimal supply of nutrients to both the crops, use of poor quality farmyard manures and erratic distribution of rainfall during soybean’s growing season and unavailability of irri- gation water during wheat season. In this connection, the crop growth simulation models are handy in identifying the constraints to yield and recommending appropriate management practices to optimize the productivity of soybean–wheat system. To achieve this, the APSIM model was parameterized and validated for soybean and wheat crop of subtropical central India. Independent data set was used to parameterize soybean cultivar (JS 335) and wheat cultivar (Sujata) to be used for APSIM simulation. Genetic coefficient generated from this study was used for subsequent model validation. The data on water use, N uptake, grain yield and soil organic C from an ongoing long- term experiment was used for validation purpose. Three nutrient treatments, viz., control (no nutrient), inorganic (recommended rate) and FYM (8 t ha−1 to soybean and 16 t ha−1 to wheat) were used to validate the APSIM model. For organic treatments, we simulated N management using the FYM as the source of plant available N under field condition. The model was parameterized by specifying the N mineralized from the manure in the laboratory incubation. The model predicted successfully grain yield and N uptake under FYM treatments in soybean and wheat. For other treatments, model prediction was satisfactory in most of the cases in simulating water and organic carbon, grain yield and N uptake by both the crops. The discrepancy observed between the observed and predicted yield in the control under soybean was due to the P limiting condition of the treatment rather than the model. The predicted variability of crop yield was also due to the variation of weather during soybean growing season and amount of irrigation and N used during wheat growing season. Therefore, this APSIM simulation study can satisfactorily be used to make appropriate management decisions to provide farmers and others with alternative options for nutrient management for soybean–wheat cropping systems.
Predicting N mineralization from organic manures like farmyard manure (FYM) is more difficult than... more Predicting N mineralization from organic manures like farmyard manure (FYM) is more difficult than from fresh organic materials like crop residues, as the manures vary greatly in composition. A laboratory incubation experiment was carried out for 98 days at 30◦C under aerobic conditions to study the effects on N dynamics of Gliricidia (Gliricidia sepium, Jacquin) and FYM application to soil at 5 and 10gkg−1. ApplicationofGliricidiainducedNmineralizationfromthestartofincubationperiod,withtheamountofN mineralizedincreasingwithrateofapplication.Incontrast,applicationofFYMresultedinimmobilization of mineral N in soil, irrespective of the rate of application. The initial net immobilization from FYM was limited by availability of N in the soil for the higher rate of application. We used the APSIM SoilN module to simulate these contrasting patterns of mineralization of N from Gliricidia and from FYM. The prediction of N mineralized from Gliricidia was better than FYM. The default model parameters specify that the fresh organic matter pools (FPOOL1, FPOOL2 and FPOOL3) have the same C:N ratio and this assumption was ineffective in predicting N mineralized from FYM. The predictive ability of the model improved when this default assumption was modified based on the size of the individual pools (FPOOL1, FPOOL2 and FPOOL3), and the pool’s C:N ratios. The modelling efficiency, a measure of goodness of fit between the simulated and observed data, improved markedly for the modified model. The discrepancy between the modelled and observed data was a tendency for the model to underestimate the rate of re-mineralization at the lower rate of application of FYM in the later part of incubation. Unfortunately the appropriate modification to the size and C:N ratios of the FPOOLs could not be determined on the basis of chemical analysis alone. Thus, a true predictive application of the model to a new FYM material is not yet possible.
A laboratory incubation experiment was carried out for 98 days at 30ºC under aerobic conditions ... more A laboratory incubation experiment was carried out for 98 days at 30ºC under aerobic conditions to study the effects of rice (Oryza sativa, L.) and wheat (Triticum aestivum, L.) straw applied at 5 and 10 g kg-1 in the presence or absence of additional N (as urea). The study showed an interactive effect between the rate of appli- cation of the residues and additional N. Without additional N, the mineral N in soil was completely immobilized within two weeks irrespective of the rate of application; initial net immobilization was limited by the availability of N and was independent of residue rate. When additional N was supplied, initial net immobilization was dependent on the rate of application of the residue. We used the APSIM SoilN module to simulate N mineralization from high C:N ratio crop residues, and compared the predictions with the observed data from our incubation study. Model performance was generally satisfactory, and the model was able to simulate the observed interaction between rate of application of residue and added N. The modelling efficiency, a measure of goodness of fit between the simulation and observed data, was 0.82 for the treatments in the incubation study. The major discrepancy between the model and the observed data was a tendency for the model to underestimate the initial rate of immobilization.
Tillage and residue management practices are known to affect seedling emergence and growth. Howev... more Tillage and residue management practices are known to affect seedling emergence and growth. However, information on direct seeded rice (Oryza sativa L.) in rice–wheat (Triticum spp.) cropping system is lacking. Thus a study was undertaken under different tillage (conventional and zero tillage) and residue (residue-retained and removed) management options on rice seedling emergence and growth in rice–wheat system on a Vertisol of Central India. Seedling emergence was greater in residue removed plots compared to residue-retained one. Prediction of rice seedling emergence with the France and Thornley [Mathematical Models in Agriculture and Related Sciences, Butterworths, London, 1984] model and growth by the Logistic and Gompertz model, and Monomolecular model were also attempted. Emergence indicators showed that seedling emergence of rice was favored more by conventional tillage than zero tillage in wheat. Of the three models tested, the Gompertz model gave the best fit. The effect of tillage and residue of wheat on the estimated parameters of the models were also studied.
Uploads
Papers by Dr. M. Mohanty
important to study rooting behaviour of crops to soil compaction that are imparted on it naturally or artificially. The
objective of this study was to determine the effect of soil compaction levels by varying the soil bulk density (BD) on
rooting parameters and to model the root growth to understand the dynamics of rooting behaviour of chickpea (Cicer
arietinum L.). Compaction level treatments, i.e. BDs were (i) 1.2, (ii) 1.4, (iii) 1.5 and (iv) 1.6 Mg/m3. When BD was
increased from 1.2 Mg/m3 to 1.6 Mg/m3, there was 58% and 44% reduction in plant height of JG 11 and JG 130,
respectively. There was 59% and 45% reduction in root length of JG 11 and JG 130, with increase in BD from 1.2 Mg/
m3 to 1.6 Mg/m3. On an average, an increase in BD by 0.1 unit resulted in 19.34 and 19.11% decrease in root main
axis length of JG 11 and JG 130, respectively. There was a negative correlation between root penetration rate and soil
BD (R2 = 0.88). The critical growth limiting BD for chickpea was found to be 1.89 Mg/m3 in our study. The logistic
growth model was fitted well with the observed dataset obtained from study with R2 of 0.98** (P < 0.01). In this
study, the chickpea variety JG 130 proved to be better than JG 11 while selecting chickpea cultivars for highly
compacted soils.
and plant growth processes in Vertisols. Despite their importance, studies on characterising cracks in Vertisols of India are
limited. This study attempts to evaluate the influence of different tillage practices, nutrient management and cropping systems
on cracking behaviour of aVertisol in central India. The length, depth, width, area and volume of cracks were recorded after the
harvest of the wet season crops, i.e. soybean (Glycine max L.) and rice (Oryza sativa L.) from three ongoing tillage experiments
with three different cropping systems, i.e. soybean–wheat (Triticum aestivum L.), soybean–linseed (Linum usitatissimum L.)
and rice–wheat. The results revealed that all the crack parameters were significantly negatively correlated with the water
content of the 0–15 cm soil layer and, crack width and crack volume were significantly positively correlated with the bulk
density of the 0–15 cm soil layer. Gravimetric water content and bulk density of the 0–15 cm soil layer together explained
79% variation in the crack volume. The crack volume was significantly negatively correlated (r = 0.86, P = 0.01) with the
root length density of the previous soybean crop. Rice grown under puddled condition significantly enhanced different crack
parameters viz., length, depth, width, surface area and volume of the cracks over nonpuddled direct seeded rice. Sub-soiling
practised in soybean under the soybean–linseed system significantly reduced the width, depth, length and surface area of
cracks by 12.5, 10, 5 and 12%, respectively, over conventional tillage. No tillage practised in soybean under soybean–wheat
system resulted in significant increase in width, depth and volume of the cracks but decrease in length and surface area of
cracks over conventional tillage and mould board tillage practice. Application of manure reduced the magnitude of different
crack parameters in soybean–linseed cropping system. Thus cracking in Vertisols can be favourably managed by the selection
of proper tillage practice, cropping system and organic manure amendments.
season oilseed cash crops in central India. Despite its phenomenal growth
in this agro-climatic zone, the average productivity of soybean has
remained more or less at 1 t ha
1 due to several abiotic, biotic and
socio-economic factors. The climate change (increase in temperature,
CO2 concentration and rainfall) will affect this rainfed crop in the future.
So, proper management practices which include crop management (use of
nutrients, planting time and plant population) will play a major role in
future productivity in these regions. Simulation models with demonstrated
accuracy and reliability provide an alternative method of investigating
both short- and long-term agricultural practices with less time
requirements and low cost. They have been evaluated and used as a
research tool to study risks associated with various management strategies
and to assist in decision-making. Hence, the present study aims at using
the APSIM model in the decision-making process to evaluate the impact
of climate change on soybean yield.
For the simulation study, the optimum date of sowing was chosen
based on the literature available for this region. A well-calibrated and
validated APSIM model was used for a long-term simulation study on the
impact of rainfall pattern on soybean yield. The long-term prediction
revealed that there was an interannual variation in soybean yield due to
the variation in rainfall pattern. The distribution of rainfall rather than the
amount during the soybean growing season is important for soybean yield.
There was a significant decrease in soybean yield (as high as 96 %) when
the rainfall receded during the initiation of flowering to maximum pod
stage. The yield reduction was 56 % when a drought spell of around
2 weeks occurs during mid-vegetative stage. There was a significant decrease in yield (37 %) from the maximum when the drought spell occurs
at some parts of the growing season. The validated APSIMmodel was also
used to simulate the impact of climate change on soybean production in
central India. The projected temperature scenarios for the Indian subcontinent
as reported by IPCC have been used in the present study. There was
a decrease (ranging between 20 and 35 %) in soybean yield when the
effect of the rise in surface air temperature during soybean growing season
was considered. The simulation results obtained on the mitigatory option
for reducing the negative impacts of temperature increases indicate that
delaying the sowing dates would be favourable for increased soybean
yields for this region. This will help in recommending a better alternative
management options to improve the productivity of soybean in the region.
nutrients during its preparation and low nutrient content of inputs. Earlier studies showed that the
groundwater collected from habitation areas contained higher concentration of nitrates than those of field
areas which was attributed to movement of nutrients from FYM pits to nearby water sources. But little
quantitative data exist on nutrient mass balances or their losses via leaching. To address these shortcomings,
a study was conducted on a representative, traditional FYM pit in Geelakhedi village, Madhya Pradesh.
Cattle dung was the main component of FYM (67%) followed by cattle shed waste (20%); ash, household
sweepings, and vegetable waste were minor components. A total of 3700 kg of FYM was produced from
the 5760 kg of materials that were put into the pit. Importantly, 39% of the N, 20% of the P and 32% of the
K inputs were lost during the preparation of FYM. Nutrients capture on exchange resin cores showed that
at least 27% of the N, 30% of the P and 50% of the K were lost through leaching. Further studies are
needed to improve accuracy and to determine losses through other mechanisms. Despite nutrient losses,
FYM is an important resource that could be even more valuable with reduced nutrient losses.
permanent wilting point (θPWP, -1500 kPa) were developed under three soil categories (<20%, 20-40%
and >40% clay) through linear, log-linear and stepwise-regression (SR) approach, using particle size
distribution and bulk density data. Under <20% clay, the log-linear model was better than other models
in predicting θFC, whereas SR model was better for predicting θPWP. Under 20-40% clay category, all the
three approaches predicted θFC with equal efficiency, while SR was superior for θPWP. The log-linear
models performed better in predicting both the θFC and θPWP with >40% soil clay.
out to investigate alternative management practices to
increase grain yields of soybean and wheat by optimizing
sowing dates, nitrogen (N) and water requirements, along
with complimenting farmyard manure (FYM) as a N source
in the soybean–wheat cropping system of Madhya Pradesh.
The APSIM simulation study showed that the mean soybean
yield ranged from 1.0 to 1.6 t ha-1 for the different
dates of sowing. The average wheat grain yield was
3.2–3.9 t ha-1, whereas, the crop sown on 15 November
gave the highest yield. In this region, there is a potential to
increase soybean and wheat yields by 0.6 and 2.2 t ha-1,
respectively. Among the various irrigation practices simulated,
five irrigations of 60 mm at 20 days interval was
the best option for wheat. Application of 16 t FYM ha-1 to
soybean produced 50 % higher wheat yield than the same
amount of FYM applied to wheat. The wheat yield
obtained from inorganic application of N was at par with that obtained from the application of integrated and organic
sources. However, the amount of N loss from the integrated
use of fertilizer N was lower than that from the current
recommended practice for the region. Application of FYM
alone or in combination with inorganic fertilizer maintained
higher soil organic carbon concentration as compared
to the application of inorganic fertilizer alone. Thus,
the model provided a mean of evaluating alternative crop N
and water management options for effectively managing
the soybean–wheat cropping system.
recent
years,
nutrient
management
of
soybean–wheat
systems
in
central
India
has
become
a
cause
for
concern
because
of
stagnation
of
grain
yields
of
soybean
and
wheat.
The
reduction
in
grain
yield
was
mainly
attributed
to
a
suboptimal
supply
of
nutrients
to
both
the
crops,
use
of
poor
quality
farmyard
manures
and
erratic
distribution
of
rainfall
during
soybean’s
growing
season
and
unavailability
of
irri-
gation
water
during
wheat
season.
In
this
connection,
the
crop
growth
simulation
models
are
handy
in
identifying
the
constraints
to
yield
and
recommending
appropriate
management
practices
to
optimize
the
productivity
of
soybean–wheat
system.
To
achieve
this,
the
APSIM
model
was
parameterized
and
validated
for
soybean
and
wheat
crop
of
subtropical
central
India.
Independent
data
set
was
used
to
parameterize
soybean
cultivar
(JS
335)
and
wheat
cultivar
(Sujata)
to
be
used
for
APSIM
simulation.
Genetic
coefficient
generated
from
this
study
was
used
for
subsequent
model
validation.
The
data
on
water
use,
N
uptake,
grain
yield
and
soil
organic
C
from
an
ongoing
long-
term
experiment
was
used
for
validation
purpose.
Three
nutrient
treatments,
viz.,
control
(no
nutrient),
inorganic
(recommended
rate)
and
FYM
(8
t
ha−1 to
soybean
and
16
t
ha−1 to
wheat)
were
used
to
validate
the
APSIM
model.
For
organic
treatments,
we
simulated
N
management
using
the
FYM
as
the
source
of
plant
available
N
under
field
condition.
The
model
was
parameterized
by
specifying
the
N
mineralized
from
the
manure
in
the
laboratory
incubation.
The
model
predicted
successfully
grain
yield
and
N
uptake
under
FYM
treatments
in
soybean
and
wheat.
For
other
treatments,
model
prediction
was
satisfactory
in
most
of
the
cases
in
simulating
water
and
organic
carbon,
grain
yield
and
N
uptake
by
both
the
crops.
The
discrepancy
observed
between
the
observed
and
predicted
yield
in
the
control
under
soybean
was
due
to
the
P
limiting
condition
of
the
treatment
rather
than
the
model.
The
predicted
variability
of
crop
yield
was
also
due
to
the
variation
of
weather
during
soybean
growing
season
and
amount
of
irrigation
and
N
used
during
wheat
growing
season.
Therefore,
this
APSIM
simulation
study
can
satisfactorily
be
used
to
make
appropriate
management
decisions
to
provide
farmers
and
others
with
alternative
options
for
nutrient
management
for
soybean–wheat
cropping
systems.
important to study rooting behaviour of crops to soil compaction that are imparted on it naturally or artificially. The
objective of this study was to determine the effect of soil compaction levels by varying the soil bulk density (BD) on
rooting parameters and to model the root growth to understand the dynamics of rooting behaviour of chickpea (Cicer
arietinum L.). Compaction level treatments, i.e. BDs were (i) 1.2, (ii) 1.4, (iii) 1.5 and (iv) 1.6 Mg/m3. When BD was
increased from 1.2 Mg/m3 to 1.6 Mg/m3, there was 58% and 44% reduction in plant height of JG 11 and JG 130,
respectively. There was 59% and 45% reduction in root length of JG 11 and JG 130, with increase in BD from 1.2 Mg/
m3 to 1.6 Mg/m3. On an average, an increase in BD by 0.1 unit resulted in 19.34 and 19.11% decrease in root main
axis length of JG 11 and JG 130, respectively. There was a negative correlation between root penetration rate and soil
BD (R2 = 0.88). The critical growth limiting BD for chickpea was found to be 1.89 Mg/m3 in our study. The logistic
growth model was fitted well with the observed dataset obtained from study with R2 of 0.98** (P < 0.01). In this
study, the chickpea variety JG 130 proved to be better than JG 11 while selecting chickpea cultivars for highly
compacted soils.
and plant growth processes in Vertisols. Despite their importance, studies on characterising cracks in Vertisols of India are
limited. This study attempts to evaluate the influence of different tillage practices, nutrient management and cropping systems
on cracking behaviour of aVertisol in central India. The length, depth, width, area and volume of cracks were recorded after the
harvest of the wet season crops, i.e. soybean (Glycine max L.) and rice (Oryza sativa L.) from three ongoing tillage experiments
with three different cropping systems, i.e. soybean–wheat (Triticum aestivum L.), soybean–linseed (Linum usitatissimum L.)
and rice–wheat. The results revealed that all the crack parameters were significantly negatively correlated with the water
content of the 0–15 cm soil layer and, crack width and crack volume were significantly positively correlated with the bulk
density of the 0–15 cm soil layer. Gravimetric water content and bulk density of the 0–15 cm soil layer together explained
79% variation in the crack volume. The crack volume was significantly negatively correlated (r = 0.86, P = 0.01) with the
root length density of the previous soybean crop. Rice grown under puddled condition significantly enhanced different crack
parameters viz., length, depth, width, surface area and volume of the cracks over nonpuddled direct seeded rice. Sub-soiling
practised in soybean under the soybean–linseed system significantly reduced the width, depth, length and surface area of
cracks by 12.5, 10, 5 and 12%, respectively, over conventional tillage. No tillage practised in soybean under soybean–wheat
system resulted in significant increase in width, depth and volume of the cracks but decrease in length and surface area of
cracks over conventional tillage and mould board tillage practice. Application of manure reduced the magnitude of different
crack parameters in soybean–linseed cropping system. Thus cracking in Vertisols can be favourably managed by the selection
of proper tillage practice, cropping system and organic manure amendments.
season oilseed cash crops in central India. Despite its phenomenal growth
in this agro-climatic zone, the average productivity of soybean has
remained more or less at 1 t ha
1 due to several abiotic, biotic and
socio-economic factors. The climate change (increase in temperature,
CO2 concentration and rainfall) will affect this rainfed crop in the future.
So, proper management practices which include crop management (use of
nutrients, planting time and plant population) will play a major role in
future productivity in these regions. Simulation models with demonstrated
accuracy and reliability provide an alternative method of investigating
both short- and long-term agricultural practices with less time
requirements and low cost. They have been evaluated and used as a
research tool to study risks associated with various management strategies
and to assist in decision-making. Hence, the present study aims at using
the APSIM model in the decision-making process to evaluate the impact
of climate change on soybean yield.
For the simulation study, the optimum date of sowing was chosen
based on the literature available for this region. A well-calibrated and
validated APSIM model was used for a long-term simulation study on the
impact of rainfall pattern on soybean yield. The long-term prediction
revealed that there was an interannual variation in soybean yield due to
the variation in rainfall pattern. The distribution of rainfall rather than the
amount during the soybean growing season is important for soybean yield.
There was a significant decrease in soybean yield (as high as 96 %) when
the rainfall receded during the initiation of flowering to maximum pod
stage. The yield reduction was 56 % when a drought spell of around
2 weeks occurs during mid-vegetative stage. There was a significant decrease in yield (37 %) from the maximum when the drought spell occurs
at some parts of the growing season. The validated APSIMmodel was also
used to simulate the impact of climate change on soybean production in
central India. The projected temperature scenarios for the Indian subcontinent
as reported by IPCC have been used in the present study. There was
a decrease (ranging between 20 and 35 %) in soybean yield when the
effect of the rise in surface air temperature during soybean growing season
was considered. The simulation results obtained on the mitigatory option
for reducing the negative impacts of temperature increases indicate that
delaying the sowing dates would be favourable for increased soybean
yields for this region. This will help in recommending a better alternative
management options to improve the productivity of soybean in the region.
nutrients during its preparation and low nutrient content of inputs. Earlier studies showed that the
groundwater collected from habitation areas contained higher concentration of nitrates than those of field
areas which was attributed to movement of nutrients from FYM pits to nearby water sources. But little
quantitative data exist on nutrient mass balances or their losses via leaching. To address these shortcomings,
a study was conducted on a representative, traditional FYM pit in Geelakhedi village, Madhya Pradesh.
Cattle dung was the main component of FYM (67%) followed by cattle shed waste (20%); ash, household
sweepings, and vegetable waste were minor components. A total of 3700 kg of FYM was produced from
the 5760 kg of materials that were put into the pit. Importantly, 39% of the N, 20% of the P and 32% of the
K inputs were lost during the preparation of FYM. Nutrients capture on exchange resin cores showed that
at least 27% of the N, 30% of the P and 50% of the K were lost through leaching. Further studies are
needed to improve accuracy and to determine losses through other mechanisms. Despite nutrient losses,
FYM is an important resource that could be even more valuable with reduced nutrient losses.
permanent wilting point (θPWP, -1500 kPa) were developed under three soil categories (<20%, 20-40%
and >40% clay) through linear, log-linear and stepwise-regression (SR) approach, using particle size
distribution and bulk density data. Under <20% clay, the log-linear model was better than other models
in predicting θFC, whereas SR model was better for predicting θPWP. Under 20-40% clay category, all the
three approaches predicted θFC with equal efficiency, while SR was superior for θPWP. The log-linear
models performed better in predicting both the θFC and θPWP with >40% soil clay.
out to investigate alternative management practices to
increase grain yields of soybean and wheat by optimizing
sowing dates, nitrogen (N) and water requirements, along
with complimenting farmyard manure (FYM) as a N source
in the soybean–wheat cropping system of Madhya Pradesh.
The APSIM simulation study showed that the mean soybean
yield ranged from 1.0 to 1.6 t ha-1 for the different
dates of sowing. The average wheat grain yield was
3.2–3.9 t ha-1, whereas, the crop sown on 15 November
gave the highest yield. In this region, there is a potential to
increase soybean and wheat yields by 0.6 and 2.2 t ha-1,
respectively. Among the various irrigation practices simulated,
five irrigations of 60 mm at 20 days interval was
the best option for wheat. Application of 16 t FYM ha-1 to
soybean produced 50 % higher wheat yield than the same
amount of FYM applied to wheat. The wheat yield
obtained from inorganic application of N was at par with that obtained from the application of integrated and organic
sources. However, the amount of N loss from the integrated
use of fertilizer N was lower than that from the current
recommended practice for the region. Application of FYM
alone or in combination with inorganic fertilizer maintained
higher soil organic carbon concentration as compared
to the application of inorganic fertilizer alone. Thus,
the model provided a mean of evaluating alternative crop N
and water management options for effectively managing
the soybean–wheat cropping system.
recent
years,
nutrient
management
of
soybean–wheat
systems
in
central
India
has
become
a
cause
for
concern
because
of
stagnation
of
grain
yields
of
soybean
and
wheat.
The
reduction
in
grain
yield
was
mainly
attributed
to
a
suboptimal
supply
of
nutrients
to
both
the
crops,
use
of
poor
quality
farmyard
manures
and
erratic
distribution
of
rainfall
during
soybean’s
growing
season
and
unavailability
of
irri-
gation
water
during
wheat
season.
In
this
connection,
the
crop
growth
simulation
models
are
handy
in
identifying
the
constraints
to
yield
and
recommending
appropriate
management
practices
to
optimize
the
productivity
of
soybean–wheat
system.
To
achieve
this,
the
APSIM
model
was
parameterized
and
validated
for
soybean
and
wheat
crop
of
subtropical
central
India.
Independent
data
set
was
used
to
parameterize
soybean
cultivar
(JS
335)
and
wheat
cultivar
(Sujata)
to
be
used
for
APSIM
simulation.
Genetic
coefficient
generated
from
this
study
was
used
for
subsequent
model
validation.
The
data
on
water
use,
N
uptake,
grain
yield
and
soil
organic
C
from
an
ongoing
long-
term
experiment
was
used
for
validation
purpose.
Three
nutrient
treatments,
viz.,
control
(no
nutrient),
inorganic
(recommended
rate)
and
FYM
(8
t
ha−1 to
soybean
and
16
t
ha−1 to
wheat)
were
used
to
validate
the
APSIM
model.
For
organic
treatments,
we
simulated
N
management
using
the
FYM
as
the
source
of
plant
available
N
under
field
condition.
The
model
was
parameterized
by
specifying
the
N
mineralized
from
the
manure
in
the
laboratory
incubation.
The
model
predicted
successfully
grain
yield
and
N
uptake
under
FYM
treatments
in
soybean
and
wheat.
For
other
treatments,
model
prediction
was
satisfactory
in
most
of
the
cases
in
simulating
water
and
organic
carbon,
grain
yield
and
N
uptake
by
both
the
crops.
The
discrepancy
observed
between
the
observed
and
predicted
yield
in
the
control
under
soybean
was
due
to
the
P
limiting
condition
of
the
treatment
rather
than
the
model.
The
predicted
variability
of
crop
yield
was
also
due
to
the
variation
of
weather
during
soybean
growing
season
and
amount
of
irrigation
and
N
used
during
wheat
growing
season.
Therefore,
this
APSIM
simulation
study
can
satisfactorily
be
used
to
make
appropriate
management
decisions
to
provide
farmers
and
others
with
alternative
options
for
nutrient
management
for
soybean–wheat
cropping
systems.