Greengram Based Cropping Sequence for Sustainability under Changing Climate in Semi-arid Part of Karnataka, India

The state of Karnataka in India with a total cultivated land of 12.16 m ha is located between 11.50° to 18.50° N latitudes and 74.25° to 78.50° E longitudes. Out of 12.16 m ha of total cultivated area, 8.60 m ha is under rainfed cultivation (70.72%) and it ranks second in terms of rainfed agricultural area only next to arid stateof Rajasthan in India (Anonymous, 2018). Nearly 55 per cent of total food grain production and 74 per cent of oilseeds production come from rainfed agriculture in Karnataka. Karnataka state is predominantly semi-arid and being situated in tropics, rainfall and temperature dominate all other climate parameters vis-a-vis crop growth and yield. South West Monsoon (SWM; June-September) accounts for 70 to 75 per cent of total annual rainfall of the Northern Interior Karnataka (NIK) covering 12 drought prone districts, hence spatial and temporal variation in rainfall during this period which greatly influences crop yield. The long-term average rainfall variability (CV in %) during SWM season in NIK is much higher (21%) than that of Karnataka state (15%) and India (11%) as a whole (Venkatesh et al., 2016). Whereas, Northern Transition Zone (NTZ) coming under NIK has sub-humid, hot and dry climate and the long term annual rainfall average is 728 mm. About 430 mm of rainfall (60 %; June-September) is received in the kharif, 130 mm in the summer (18%; March-May) and 168 mm in the rabi (22%; October-December). Because of this bimodal rainfall pattern double cropping is possible in NTZ. However, in recent decades the monsoon has become even more erratic in its spatial and temporal distribution, thus increasing the risks of crop failures. Under these circumstances, farmers are uncertain of choosing right cropping sequences. In this context, greengram crop assumes importance due to short duration and being a leguminous crop. It is more adaptive and comes up well under low inputmanagement. It has the ability to fix the nitrogen to an extent of 58-109 kg N per ha-1in symbiotic association with rhizobia, which not only enables it to meet its own nitrogen requirement, but also benefits the succeeding crops hence well suited in sequence with rabi crops (Singh and Singh, 2011). In NTZ of Karnataka various greengram based cropping sequences are grown viz., greengram-sorghum, greengram-wheat and greengram-chickpea to meet both grain and fodder requirements. Traditional agronomic research efforts are being done to identify economically profitable and sustainable cropping sequences and in this effort crop modeling comes as handy and efficient tool to test and identify large number of crops/cropping sequences across soils and climate in a very limited time. However, most of the modeling studies in India have focused the work only on individual crops and their management,and very limited research work is being done using models on cropping systems. Therefore, this study was taken up to test and identify sustainable and remunerative greengram based cropping sequences for current climatesin NTZ under rainfed condition. For this work a DSSAT model (Jones et al., 2003) based study was taken up to identify the most reliable and economically profitable greengram based cropping sequence for NTZ of Karnataka.

The experimental data required to calibrate, validate and run DSSAT crop simulation model for seasonal analysis were collected from the four chosen crops grown in respective All India Co-ordinated Research Projects (AICRP) during rabi season of 2017-18 (sorghum, wheat and chickpea) and kharif season of 2018 (greengram) under rainfed condition on deep black soils at Main Agricultural Research Station of University of Agricultural Sciences, Dharwad, India located at 15°26¢ N latitude, 75°07¢ E longitude and altitude of 678 m above mean sea level which comes under Northern Transition Zone-8 of Karnataka. In addition to the crop data collected from field experiments during rabi 2017-18 and kharif  2018, additional crop data were collected from the AICRPs from previous years (2015 and 2016) for model calibration and validation of the DSSAT model.
 
Model calibration and validation
 
The DSSAT-CERES (version 4.7) for sorghum and wheat and DSSAT-CROPGRO for greengram and chickpea were calibrated using GenCalc (Hunt et al., 1993), a semi-automated program embedded within DSSAT to optimize genetic coefficients, followed by manual method i.e., alteration in the genetic coefficients in cultivar file within acceptable range of difference. Then the model was validated using the data collected from AICRP experiments during kharif 2015 and rabi 2016 for four chosen crops (greengram, chickpea, wheat and sorghum). The details on selected cultivars and optimized genotypic coefficients for each crop used in the project are presented in the Table 1 and 2.
 

 

 
Sequential analysis
 
The model calibrated and validated model before used to run sequential analysis for three cropping sequences i.e., greengram-sorghum, greengram-wheat and greengram-chickpea by creating four X-files with as per the recommended package of practice of UAS, Dharwad (Table 3) and these were linked with the past weather data from 1985 to 2016 (32 years) and representative deep black soil profile of MARS, Dharwad. The purpose of using past weather data of 32 years (1985-2016) period was to expose the crop and each cropping sequence to mean changes and naturally observed variability of weather, as well as extremes experienced during these 32 years. This study helps in identifying most consistently performing crops and cropping sequence under current climate. Later, the required simulated yearly outputs were extracted viz., grain yield and total biomass for each crop and were averaged for 32 years for presentation.
 

 
Identification of sustainable and profitable green gram based cropping sequence
 
This was done by running each cropping sequence for 32 years for yield and the current market price was considered for estimation of gross return, cost of cultivation, net returns (Rs. ha^-1), B:C ratio and based on model outputs on how many number of years crop failed in only kharif season and in only rabi season and both in kharif and rabi seasons were calculated for three cropping sequences. Taking into both B: C ratio and frequency of crop failure over 32 years period, the profitable and sustainable cropping sequence was identified.

Sequential analysis and crop yields
 
The sequential analysis for all the three cropping sequences were exposed to 32 years historic weather condition, the phenology, yield and yield attributes varied with year to year depending on the climatic condition prevailed each year of 32 years period and is represented in Table 4.
 

       
The simulated mean seed yield of greengram crop was found to be 869 kg ha^-1 and it varied from 456 to 1244 kg ha^-1 over 32 years. Sorghum simulated mean yield was 3654 kg ha^-1 with a range from 2876 to 4487 kg ha^-1. When it comes to wheat average simulated yield was 2468 kg ha^-1 with the slowest and highest being 2288 to 3257 kg ha^-1, respectively. Similarly for chickpea the model simulated yield was found to be 2062 kg ha^-1 with a range from 1324 to 2520 kg ha^-1. Similar average yield patterns and range was simulated for total biomass as well.
       
The crops grown during kharif season affect the succeeding crop in relation to nutrient and water uptake, this lead to variation in yields of rabi/following crops. Laberge et al., (2011) using labelled 15^N techniques at a site in the Sudan savannah reported that 40 per cent of the N in cowpea residues remaining in the field could be retrieved in the top 30 cm of the soil at the beginning of the next planting season and 10 percent of the residual N was taken up by a subsequent millet. Sanginga et al., (2002) found that, at a site in the Guinea savannah, 17 to 33 per cent of the N in soybean residues is taken up by a subsequent maize crop, depending on maize cultivar. Das et al., (1982) reported that sorghum yield was increased when sown after cowpea, green gram and groundnut in shallow red soils of Hyderabad.The nutrient uptake and soil moisture extraction pattern different from crop to crop.
 
Identification of profitable and sustainable cropping system
 
The B:C ratio of each sequence averaged over 32 years and number of years crop failed during kharif and rabi seasons were considered as criteria to identify the most reliable and profitable cropping sequence (Table 5). Out of 32 years greengram crop failed only once whereas wheat crop failed 7 years in greengram-wheat cropping sequence and lowest number of crops failed during rabi was 5 years for chickpea in greengram-chickpea cropping sequence of 32 years. The highest number of years crop failed during rabi season was with wheat i.e.7 years and lowest number of years crop failed during kharif season was greengram i.e., only one year. The number of years’ crop failed in rabi season varied from five to seven. Based on historical weather data of 32 years (1985-2016), out of total annual rainfall, more than half of it was received during kharif season (June-September) (Fig 1) and it follows the trend of annual rainfall (Fig 2). The crops grown in kharif season receive precipitation throughout the season with favorable mild temperature. So, it leads to the availability of sufficient soil moisture to the crop during entire growing period; hence the probability of crop failure during kharif season is very less as compared to rabi season crops. The only season greengram failed was in 2003 due to late onset of monsoon.
 

 

 

The important crops grown in rabi season in NTZ are sorghum, wheat and chickpea and these crops experience both moisture and heat stress during their life cycle. The average rainfall received during rabi season is very less (22% of total) compared to kharif season (60 per cent) and this results in the low moisture availability to the crops grown during the rabi season under much hotter and drier weather and these crops mainly complete their life cycle using residual soil moisture. Therefore, the probability of crop failure is much higher than the kharif crops and also the crops give lower yields.
       
The average B:C ratio of greengram-chickpea sequence (2.38) was the highest closely followed by greengram-sorghum (2.25) and the least was with greengram-wheat (1.76). Further, out of 32 years, the probability of crop failure with chickpea is much less than sorghum and wheat. Hence, this study showed that greengram-chickpea sequence is more consistent, reliable and profitable under current climates in NTZ of Karnataka to sustain farmers’ income.

The DSSAT-CERES and DSSAT-CROPGRO model’s genetic coefficients for cultivars of one kharif crop (greengram) and three rabi crops (sorghum, wheat and chickpea) were optimized satisfactorily through calibration and validation process using GenCalc and the data collected from the experiments from 2015 to 2018. Sequential analysis tool of DSSAT model was run for 32 years’ weather from 1985 to 2016 for three cropping sequences; greengram-sorghum, greengram-wheat and greengram-chickpea under standard production practices recommended for rainfed conditions on deep black soils. 
       
The simulated average grain yield and total biomass of 32 years in greengram crop was 869 kg ha^-1, whereas for sorghum, wheat and chickpea it was 3654, 2468 and 2062 kg ha^-1, respectively. Out of 32 years, greengram crop failed only once during kharif season of 2003 whereas, during rabi season the highest number of years crop failed was noticed in wheat (7 years) followed by sorghum (6 years) and chickpea (5 years). Among the three cropping sequences, the greengram-chickpea sequence recorded the highest B:C ratio of 2.38 followed by greengram-sorghum sequence (2.25) and the least was found for greengram-wheat sequence (1.76). Considering number of years crop failed and B:C ratio it was found that greengram-chickpea sequence was the most consistent and remunerative sequence under rainfed condition of Karnataka.