Deciphering most productive cropping systems for sustainable farming in middle Gangetic plains of Indian subcontinent

Deciphering most productive cropping systems for sustainable farming in middle Gangetic plains of Indian subcontinent | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Deciphering most productive cropping systems for sustainable farming in middle Gangetic plains of Indian subcontinent Sameer Shrivastava, Ratnesh Kumar Jha, Biswajit Pramanik, Chandra Bhushan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6170120/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The field experiments were conducted during 2020– 2021 at the Dr Rajendra Prasad Central Agricultural University, Samastipur, Bihar, India. The main aim of the study was to find out a suitable cropping system to give higher productivity and profitability. Ten cropping systems, viz . Rice–Wheat, Rice–Wheat–Greengram, Rice–Potato+maize, Rice–Mustard–Greengram, Rice–Lentil–Maize, Maize–Mustard–Greengram, Finger millet–Wheat–Greengram, Soybean–Potato–Sunflower, Rice–Pea–Wheat–Greengram, Rice–Mustard–Maize+Greengram were evaluated in a randomized complete block design with three replications. Results suggested that the highest system productivity was obtained from the Rice–Potato+maize (24 t/ha) cropping system followed by soybean-potato-sunflower (22 t/ha) than all other cropping systems, however, these were at par. Water productivity calculated on net return basis was found highest in rice-poato+maize (29 Rs/m 3 water applied) and was followed by soybean-potato-sunflower (25 Rs/m 3 water applied) cropping system and was statistically at par. Rice-potato+maize cropping system resulted in maximum net return (3,07,889 Rs/ha) in comparison to all other cropping systems followed by soybean-potato-sunflower (2,66,370 Rs/ha) cropping system. Rice-potato+maize cropping system gave highest B-C ratio (3.0) followed by soybean-potato-sunflower (2.8) and finger millet-wheat-green gram (2.8) cropping systems. Rice equivalent yield Nutrient use productivity water use productivity Introduction Rice–wheat cropping system is the most dominant double–cropping system in subtropical Asian countries, including China, Pakistan, Nepal, Bangladesh and India. In the Indo–Gangetic Plains (IGP), this system covers approximately 10 million hectares (m ha) in India, 2 m ha in Pakistan, and 0.5 m ha each in Nepal and Bangladesh [ 1 ]. In India’s IGP alone, the rice–wheat cropping system spans an area of 10.5 million hectares. However, this system has caused significant challenges in recent years, primarily due to the overexploitation of underground water resources to meet the high water demands of rice cultivation, resulting in a declining water table in many areas. Cropping system research focuses on growing crops in a specific sequence and studying their interactions with farm resources and technologies. It has been shown that including pulses, oilseeds, and vegetables in the system is more beneficial than continuous cereal cultivation. Such diversification not only improves soil health but also positively alters the economic dynamics of cropping systems [ 2 ]. In the state of Bihar, agriculture is also largely dominated by the rice–wheat cropping system, which occupies about 72% of the gross cropped area and contributes to around 82% of the state's total food production. While rice is a necessity in the rainy season due to the midland and lowland conditions, the unpredictability of monsoon rains limits the scope for growing other crops during this period. During the winter season, wheat is the preferred crop due to its high productivity, stability, and resistance to major pests and diseases. Additionally, in medium land areas, Zaid (summer)crops such as maize, urd bean, mung bean, Zaid (summer)vegetables, and sunflowers are grown on a smaller scale after the rice–wheat rotation. In response to climate change, upland crops are increasingly being shifted to midlands, and midland crops to lowlands, primarily due to reduced rainfall. However, these areas face risks of inundation and flash floods during the crop growth period because of the monsoon's unpredictability. To address these climatic challenges, cultivating crops in a systematic approach rather than in isolation offers better sustainability and profitability. An efficient cropping system is one that maximizes output while minimizing input requirements, ensuring both economic and environmental resilience. Method and Materials 2.1 Study location The field experiment was conducted at the Crop Research Farm, Pusa, Bihar for one year in 2019–2020 during all the three seasons: Rabi 2019–20, Zaid (summer) 2020 and Kharif 2020. The experimental plot, selected for this experiment, was a true representative of medium land where rice crop can be taken with/without supplemental irrigation but at the same time, it was also considered, while selecting the experimental plot, where rice crop can be replaced by suitable alternative crops like maize, finger millet and soybean, seeing the recent climatic stresses of drought might be due to late onset of monsoon, midseason dry spells or lesser rainfall. In Rabi 2019–2020 and Zaid (summer) 2020 usual crops were taken to see the compatibility of different cropping systems under the existing climatic stresses. The field was well connected to irrigation system for timely and assured irrigation. The experimental plots were having fairly uniform topography with homogenous fertility and soil characteristics suitable for medium land crop cultivation. 2.3 Climate and weather Dr. Rajendra Prasad Central Agriculture University, Pusa, Bihar situated at Samastipur city on 25º59’ N latitude and 85º48’ E longitude on the bank of Budhi Gandak River. The average temperature of Pusa is 19 to 34ºC, the minimum temperature is recorded in January is 8.8ºC and maximum in 36.0ºC to 37.1ºC during April. Pusa is coming under subtropical and sub humid type climate. The average annual rainfall of this place is approximately 1234.7mm and more than 87 per cent of total rainfall is received from month of June to September. 2.4 Treatments and experimental details The experiment was conducted from October 2019 (starting of Rabi season) to October 2020 (end of Kharif season) with 10 treatments combination consisting of ten cropping system with three replications, which are as follows: Table No. 1 Treatments details Treatment details of different cropping system T 1 : R–W Rice—wheat T 2 : R–W–Gg Rice—wheat —Greengram T 3 : R–P +M Rice—potato+ maize T 4 : R–Mu–Gg Rice—mustard—Greengram T 5 : R–Le–M Rice—lentil —maize T 6 : M–Mu–Gg Maize—mustard—Greengram T 7 : Fm–W–Gg Finger millet—wheat —Greengram T 8 : Sb–P–Sf Soybean—potato—sunflower T 9 : R–Pg–W–Gg Rice—pea—wheat—Greengram T 10 : R–Mu–M+Gg Rice—mustard—maize +Greengram The investigation plot's soil was calcareous in nature with an initial pH of 8.2, Electrical conductivity of 0.35 dS/m, low organic carbon 0.38 percent, low available nitrogen 237 kg/ha, medium available phosphorus 12.23 kg/ha, and medium available potassium 131 kg/ha. The experiment was laid out in randomized complete block design (RCBD) with 10 treatments of cropping system viz . Rice–Wheat, Rice–Wheat–Greengram, Rice–Potato+Maize, Rice–Mustard–Greengram, Rice–Lentil–Maize, Maize–Mustard–Greengram, Finger millet–Wheat–Greengram, Soybean–Potato–Sunflower, Rice–Pea–Wheat–Greengram, Rice–Mustard–Maize+Greengram in three replications. The gross plot size was 5m x 5m and the net plot size was 4m x 4m were separated by 1m irrigation channel and 0.5–meter path. The experiment was started from Rabi –2019–20 and ended in Kharif –2020. In Rabi season wheat, potato, maize, lentil, mustard, pea was grown. After harvest of these crops in Zaid (summer) season Greengram, maize and sunflower were grown. In Kharif season, after the harvest of Zaid (summer) season crops rice, maize, soybean and finger millets were grown. The crops were grown with the recommended package and practices and recommended doses of all the inputs were applied for crops. 2.5 Soil analysis To assess soil health, one composite soil sample (0–15 cm) was collected with the help of auger before the initiation of the experiment from 20 locations of the experimental area as per the standard procedure. The 30 composite soil samples (five places of each plot) after completion of two years of the experiment were collected from each treatment with their all three replications. The samples were analysed for pH, electrical conductivity (EC), organic carbon (OC), available nitrogen (N), phosphorus (P) and potassium (K), particle density and porosity. Soil samples for bulk density were taken from 0 to 15 cm soil depth with the help of core sampler at initiation and after completion of two years field trial as per the standard procedure. 2.6 Crop sampling Crops were harvested manually from the net plot area and sun–dried. After that, the produce was threshed, cleaned, winnowed and weighed to obtain grain/seed yield of rice, wheat and mustard. However, in the case of potato, cabbage, berseem fodder, maize fodder, sudan grass fodder and cowpea fodder, fresh weight of economic produce was recorded. In Greengram, one or two pickings were done at a certain interval and produce was sun–dried. Further, sun–dried produce was threshed manually, cleaned and weighed. Table No 2: Details of crops, varieties and cultural operations followed in different cropping system during 2019–2020 SI. No. Operations Kharif Rabi Zaid (summer) 1 Crops and varieties Rice: Rajendra Bhagwati Maize: Shaktiman–5 Finger millet: Rajendra Madua–1 Soybean: B S–1 Wheat: HD 2967 Potato: Kufri Arun Maize: Shaktiman–5 Mustard: Rajendra Sufalam Lentil: Pant L–406 Pea: Azad Pea–3 Greengram: HUM–16 Maize: Shaktiman–5 Sunflower: Surya 2 Spacing ( R X P ) in cm Rice: 20 x 15 Maize: 60 x 20 Finger millet: 22 x 10 Soybean: 30 x 45 Wheat: 22.5 Potato: 60 x 20 Maize: 60 x 20 Mustard:30 x 15 Lentil: 30 x 10 Pea: 60 x 10 Greengram: 30 x 10 Maize: 60 x 20 Sunflower: 45 x 20 3 Sowing date Rice: 16/06/2020 Maize: 16/07/2020 Finger millet: 22/06/2020 Soybean: 03/07/2020 Wheat: 20/11/2019, Maize: 06/11/2019 Wheat (Late): 20/12/2019, Lentil: 06/11/2019 Potato: 06/11/2019, Pea: 14/10/2019 Mustard: 06/11/2019 Greengram: 12/04/2020 Maize: 20/03/2020 Sunflower: 03/03/2020 4 Fertilizer applied N–P2O5–K2O (Kg/ha) Rice: 120:60:40 Maize: 100:60:80 Finger millet: 40:30:30 Soybean: 20:60:40 Wheat: 120:60:40 Wheat (Late): 80:40:20 Potato: 150:90:100 Mustard: 80:40:40 Lentil: 20:40:40 Pea: 20:40;40 Greengram: 20:45:20 Maize: 80:40:30 Sunflower: 30:80:40 5 Seed rate (kg/ha) Rice:30 Maize: 20 Finger millet: 10 Soybean: 75 Wheat (timely): 100, Maize: 20 Wheat (late) 125, Mustard: 5 Potato: 2000, Lentil: 30 Pea: 90 Greengram: 35 Maize:20 Sunflower: 6 6 Sowing method Rice: Transplanting Maize: Ridge and Furrow method Finger millet: Transplanting Soybean: Ridge and Furrow method Wheat: line sowing Potato: Ridge and Furrow method Maize: Ridge and Furrow method Mustard: line sowing Lentil: line sowing Pea: line sowing Greengram: line sowing Maize: Ridge and Furrow Sunflower: line sowing 7 Herbicides applied and inter–cultivations Rice: Pretilachlor Maize: Atrazine Soybean: Imazethapyr Wheat: Sulphosulfuron Lentil: Pendimethalin Maize: Atrazine Sunflower: Pendimethalin 8 Plant protections Rice: Folidal Maize: Carbofuran Soybean: Chlorpyriphos Potato: Indofil M 45 Maize: carbofuran Mustard: Imidacloprid Greengram: monochrotophos Maize: carbofuran Sunflower: Phorate 10G 9 Harvesting date Rice: 10/10/2020 (116 DAT) Maize: 20/10/2020 (96 DAS) Finger millet: 24/10/2020 (124 DAS) Soybean: 13/10/2020 (102 DAS) Wheat: 5/04/2020 (137 DAS) Wheat (Late): 10/04/2020(112DAS) Potato: 12/02/2020 (98 DAS) Lentil: 15/03/2020 (130 DAS) Pea: 18/12/2019 (65 DAS) Mustard: 09/03/2020 (124 DAS) Maize: 22/04/2020 (168 DAS) Greengram: 13/06/2020 (62 DAS) Maize: 29/06/2020 (101 DAS) Sunflower: 15/06/2020 (104 DAS) 2.7 Economic study For the economic analysis, the price of individual input and output was assumed to be stable during both the years of experimentation. The total number of labours required for various agronomic practices used for different cropping sequences were noted plot–wise, and the total requirement of labour per hectare for each sequence was worked out. The economics was calculated as per current year input cost and economic value of different crop production in the local market . 2.8 Cropping system analysis 2.8.1 Crop Productivity: Yield per unit area (kg/ha). Crop productivity= Yield of a crop/ Area of a crop 2.8.2 System Productivity: Equivalent yield of system= Yield of crop A + Crop A equivalent yield of crop B Similarly if there are thee crops A, B and C in the system then equivalent yield of system (in crop A equivalent yield) =Yield of crop A + Crop A equivalent yield of crop B + Crop A equivalent yield of crop C. 2.8.3 Rice Equivalent Yield: REY = yield of crop a (Kg) x Price of crop a (Rs.) / Price of rice (Rs.) 2.8.4 Land Use Efficiency (%): Land used during the agricultural year. LUE = Total duration of crop in cropping system/365 x 100 2.8.5 Apparent water use productivity (kg. grain/ha–mm): Apparent water productivity is calculated by dividing equivalent yield of the system per ha. divided by total quantity of water used in ha. of land in mm. AWP = yield (kg) / irrigation water (ha–mm) 2.8.6 Nutrient use productivity (kg grain/kg nutrient used): Nutrient use productivity is calculated by dividing equivalent yield of the system/ha divided by total quantity of nutrients used per ha. 2.9 Statistical analysis The raw data after collecting from field and after chemical analysis were analysed statistically in order to reduce error and to find out best treatment. The data obtained for different parameter were analysed using method given by Gomez and Gomez (1984). Result and Discussion System productivity of cropping system (Kg REY/ha): In the present study, 10 different cropping systems suitable for medium land situations were tested and it was found that rice–poato+maize cropping system gave significantly higher rice equivalent yield (24.7t/ha) than other treatments except soybean–potato–sunflower (22.4t/ha) which was found to be at par. Soybean–potato–sunflower cropping system (22.4t/ha) was found to be the second most productive system with significantly higher Rice equivalent yield than rest of the cropping systems except rice–potato+maize. Rice–mustard–maize+Greengram (14.8t/ha) was found third most productive system with significantly higher rice equivalent yield than rice–wheat (7.8t/ha), rice–mustard–Greengram (10.8t/ha), maize–mustard–Greengram (11.5t/ha), however, this system was at par with rice–wheat–Greengram (12.4t/ha), rice–lentil–maize (12.5t/ha) finger millet–wheat–Greengram (12.5t/ha) and rice–pea–wheat–Greengram (14.4t/ha). Rice–wheat cropping system was found to have the lowest rice equivalent yield (7.8 t/ha) in comparison to all other cropping system, however, it was at par with rice–mustard–Greengram (10.8 t/ha). So, the result revealed that rice–potato+maize (24.7t/ha) cropping system having better performance in terms of rice equivalent yield in the existing climate. These findings are consistent with those of Singh et al. [3] who identified rice-pea-okra as the most productive sequence in eastern Uttar Pradesh, followed by rice-pea-onion, India. Choudhary et al. [4] found increased system productivity when wheat was replaced with vegetables like radish and potato in a rice– wheat system. Production efficiency (Kg/ha/day): In production efficiency analysis, rice–potato+maize cropping system was found to have the highest production efficiency (86.9 kg/ha/day) in comparison to all other cropping systems. Soybean–potato–sunflower cropping system was found second highest production efficiency (76.7 kg/ha/day) which was significantly higher in comparison to all other cropping system except rice–potato+maize. Rice–mustard–maize+Greengram (43.5 kg/ha/day) cropping system was found third highest production efficiency which was significantly higher in comparison– to rice–wheat cropping system (30.9 kg/ha/day) except rice–potato+maize and soybean–potato–sunflower , and this cropping system was found to be at par with rice–wheat–Greengram (39.4 kg/ha/day), rice–mustard–Greengram (35.9 kg/ha/day), rice–lentil–maize (36.1 kg/ha/day), maize–mustard–Greengram (40.8 kg/ha/day), finger millet–wheat–Greengram (38.6 kg/ha/day) and rice–pea–wheat–Greengram (40.7 kg/ha/day). The traditional cropping system rice–wheat gave lowest production efficiency (30.9kg/ha/day) in comparison to all other cropping systems. According to Sharma et al. [5], crop intensification by include vegetables and leguminous crops boosted production efficiency. Bhargavi et al. [6] discovered that the bottle gourd-onion cropping system had the best system productivity, resulting in the highest production efficiency. Relative production efficiency (%) Rice–potato+maize cropping system was found significantly highest relative production efficiency (316%) in comparison to rice–wheat (100%) cropping system. Soybean–potato–sunflower cropping system was found second highest production efficiency (289%) which was significantly higher in comparison to other cropping systems except rice–potato+maize cropping system. Rice–mustard–maize+Greengram cropping system (191%) was found having third highest production efficiency which was significantly higher in comparison to rice–wheat (100%), rice–mustard–Greengram (138%), maize–mustard–Greengram (147%) cropping systems except rice–potato+maize and soybean–potato–sunflower, and this cropping system was at par with rice–wheat–Greengram (158%), rice–lentil–maize (160%), finger millet–wheat–Greengram (161%) and rice–pea–wheat–Greengram (185%) whereas rice–wheat cropping system resulted in lowest production efficiency (100%). Land use efficiency (%) Land use efficiency was maximum in rice–pea–wheat–Greengram cropping system (97%) followed by rice–lentil–maize (95%), rice–mustard–maize+Greengram (93%) and finger millet–wheat–Greengram. Lowest land use efficiency was found in rice–wheat cropping system which was 69% among all other cropping system. The findings are in consistent with those of Prasad et al [7]. The existing rice–wheat system had the lowest land-use efficiency, as the land sat fallow for more than two months each year. According to Sharma et al. [5], crop intensification by include vegetables and leguminous crops boosted production and land-use efficiency. Nutrient use productivity (kg REY/kg nutrient applied) In statistical analysis rice–poato+maize cropping system was found having significantly higher nutrient use productivity (44.1Kg REY/kg nutrient applied) in comparison to all other cropping system. Soybean–potato–sunflower cropping system was found second highest production efficiency (35.5 kg REY/ kg nutrient applied) which was significantly higher in comparison to other cropping system except rice–potato+maize cropping system. Rice–mustard–maize+Greengram (28.0 kg REY/kg nutrient applied) was found third cropping system having highest production efficiency which was significantly higher in comparison to rice–wheat cropping system (23.6 kg REY/kg nutrient applied ) except rice–potato+maize and soybean–potato–sunflower, and this cropping system was found at par with rice–wheat–Greengram (23.6 kg REY/kg nutrient applied), rice–mustard–Greengram (23.3 kg REY/kg nutrient applied), rice–lentil–maize (27.5 kg REY/kg nutrient applied), maize–mustard–Greengram (23.7 kg REY/kg nutrient applied), finger millet–wheat–Greengram (30.1 kg REY/kg nutrient applied) and rice–pea–wheat–Greengram (26.0 kg REY/kg nutrient applied) cropping system. The traditional cropping system rice–wheat was found lowest production efficiency (17.8 kg REY/kg nutrient applied) which was at par with rice–mustard–Greengram cropping system. Bhargavi et al. [6] found the similar result that bottle gourd-onion cropping system have highest system productivity due to high production potential crops and the relative production efficiency was also high in this system due to the production potential of crops. Table No. 3: System productivity, production efficiency , relative production efficiency, land use efficiency , nutrient use productivity of different cropping system Treatments System productivity (kg/ha) Production efficiency (kg/ha/day) Relative production efficiency (%) Land use efficiency (%) Nutrient use productivity (kg REY/kg nutrient applied) T 1 : R–W 7817 30.9 100 69 17.8 T 2 : R–W–Gg 12399 39.4 158 86 23.6 T 3 : R–P +M 24684 86.9 316 78 44.1 T 4 : R–Mu–Gg 10843 35.9 138 83 23.3 T 5 : R–Le–M 12520 36.1 160 95 27.5 T 6 : M–Mu–Gg 11497 40.8 147 77 23.7 T 7 : Fm–W–Gg 12481 38.6 161 88 30.1 T 8 : Sb–P–Sf 22360 73.6 289 83 35.5 T 9 : R–Pg–W–Gg 14433 40.7 185 97 26.0 T 10 : R–Mu–M+Gg 14829 43.5 191 93 28.0 SEm ± 1044 3.4 15 - 1.9 CD (p=0.05) 3102 10.2 43 - 5.7 Economics of different treatments Cost of cultivation (Rs./ha) The data on cost of cultivation revealed that rice–potato+maize cropping system incurred maximum cost of cultivation among all other cropping systems. It might be due to high input cost in terms of seed, labour, land preparation, high volume of potato seed tubers and high requirement of fertilizers in potato. The next in order was soybean–potato–sunflower cropping system due to the high cost and high requirement of potato tubers for sowing and high fertilizer requirement of potato. Higher seed cost of soybean was also fund to affect the cost of cultivation. The result is in confirmation with Walia et al. [8] who reported highest cost of cultivation due to inclusion of potato and onion in the cropping systems having high demand of human labour and fertilizer requirement. The lowest cost of cultivation in rice–wheat cropping system can be attributed to low seed cost of rice and wheat and low labour requirement in comparison to other cropping systems. Gross return (Rs./ha) The data of gross return revealed that rice–potato+maize was having the highest gross return than all other cropping systems. This might be due to higher tonnage of Rabi maize and potato and high market price. The REY of this system is highest among all other treatments, so the gross return is also highest in this system. The next system in the order was soybean–potato–sunflower having second highest gross return. This is attributed to higher REY of this cropping system in comparison to others. The next system in order was rice–pea–wheat–Greengram which gave third highest gross return than others, it might be due to high REY of this system because pea and wheat two crops was grown in one season. Fourth highest gross return producing cropping system was rice–mustard–maize+Greengram than other cropping systems. It can be attributed because maize is high yield producing crop, so the REY of this system was high which directly affected the gross return of this system. Walia et al. [8] also found the same result that inclusion of high yielding crops such as potato and maize give higher gross return because of higher value of produce. Net return (Rs./ha) The data of net return showed that significantly higher net return was realized from rice–potato+maize cropping system. It could be because the addition of potato and maize intercropping in the system, in addition to increasing system productivity due to their higher yield, also fetched a decent price, resulting in a larger net return. The next in order was soybean–potato–sunflower cropping system which gave second highest net return. Since the price of crops taken in the system is generally high, so the system productivity is high thereby increasing net return. Rice–mustard–maize+greengram was third most remunerative system in terms of net return. It was attributed due to inclusion of Zaid (summer)maize+greengram intercropping in cropping system that improved the system productivity of this system by production of high tonnage, fetched good price thereby, enhancing the net returns. Kumar et al., 2008 found that including vegetable crops such as potato, onion, cabbage, garlic, coriander, cowpea, and okra in cropping systems increased system productivity while also raising market prices, resulting in higher net returns. Kumar. et al., [9] found that incorporating vegetable crops within rice–based crop sequences increased net returns. Rice–wheat cropping system gave lowest net return, it might be due to low system productivity thereby, low net return. B: C ratio The data of net return showed that significantly higher benefit: cost ratio was realized from rice–potato+maize cropping system. It might be due to high net return in this system. Potato and maize intercropping in the system, besides enhancing the system productivity due to their higher yield, fetched good price thereby, increasing net return and B: C ration also. The next in order was soybean–potato–sunflower cropping system that gave second highest benefit: cost ratio. It can be due to high price crops grown in this system, so the system productivity is high thereby, increasing net return. So the B: C ratio is also high. Rice–mustard–maize+Greengram was third most remunerative system in terms of B: C ratio. It was attributed due to inclusion of Zaid (summer)maize+ Greengram intercropping in cropping system, it improved the system productivity of this system by production of high tonnage, fetched good price thereby, increasing net return. So, the B: C ratio is also high. Rice–wheat cropping system gave lowest net return, it might be due to low system productivity and low net return of this system. Table 4.11 Economics of different cropping systems: Treatment Cost of cultivation Gross return Net return B: C ratio T 1 : R–W 74897 166862 91964 2.2 T 2 : R–W–Gg 101223 253478 152254 2.5 T 3 : R–P +M 155693 463583 307889 3.0 T 4 : R–Mu–Gg 92403 205029 112626 2.2 T 5 : R–Le–M 94347 236194 141847 2.5 T 6 : M–Mu–Gg 82923 214763 131839 2.6 T 7 : Fm–W–Gg 91755 253715 161959 2.8 T 8 : Sb–P–Sf 151319 417689 266370 2.8 T 9 : R–Pg–W–Gg 126483 290662 164178 2.3 T 10 : R–Mu–M+Gg 111542 279445 167903 2.5 SEm ± – 19545 19545 - CD (p=0.05) – 58061 58061 - Conclusion System productivity analysis found that Rice–potato + maize cropping system gave significantly higher rice equivalent yield (24.7 t/ha) than other treatments except soybean–potato–sunflower (22.4 t/ha) which was found to be at par. In production efficiency analysis, rice–potato + maize cropping system was found to have the highest production efficiency (86.9 kg/ha/day) in comparison to all other cropping systems. Soybean–potato–sunflower cropping system was found second highest production efficiency (76.7 kg/ha/day). Rice–poato + maize cropping system was found having significantly higher nutrient use productivity (44.1 Kg REY/kg nutrient applied) in comparison to all other cropping system. Soybean–potato–sunflower cropping system was found having second highest production efficiency (35.5 kg REY/ kg nutrient applied). Rice–potato + maize cropping system was found significantly highest relative production efficiency (316%) in comparison to rice–wheat (100%) cropping system. Soybean–potato–sunflower cropping system was found second highest production efficiency (289%). Land use efficiency was maximum in rice–pea–wheat–Greengram cropping system (97%) followed by rice–lentil–maize (95%) and rice–mustard–maize + Greengram (93%). Rice–potato + maize (1,55,693 Rs/ha) was having maximum cost of cultivation among all cropping systems followed by, soybean–potato–sunflower (1,51,319 Rs/ha). Rice–potato + maize cropping system gave significantly higher gross return (4,63,583 Rs/ha) in comparison with all other cropping system which was at par with soybean–potato–sunflower (4,17,689 Rs/ha) cropping system. Rice–potato + maize cropping system gave maximum net return (3,07,889 Rs/ha) in comparison with all other cropping systems except soybean–potato–sunflower (2,66,370 Rs/ha) cropping system which was at par with rice–potato + maize cropping system. Rice–potato + maize cropping system gave highest B:C ratio (3.0) in comparison to other cropping system which was at par with soybean–potato–sunflower (2.8), finger millet–wheat–Greengram (2.8), maize–mustard–Greengram (2.6), rice–wheat–Greengram (2.5), rice–lentil–maize (2.5), rice–mustard–maize + Greengram (2.5) cropping systems. There was little increase in nutrient content of soil in terms of available nitrogen, available phosphorus and available potassium over the initial value in those cropping systems where legume crops were grown but this could not reach the level of significance. The Rice–Potato + maize cropping system emerges as the most efficient and productive system overall, delivering the highest yield, nutrient use efficiency, and production efficiency, making it an ideal choice for maximizing resource use. The Soybean–Potato–Sunflower system, while second, also demonstrates strong performance, particularly in production efficiency and nutrient use. For systems focused on land use, Rice–Pea–Wheat–Greengram offers the best potential. The rice–potatoes–maize cropping system was discovered to have the highest gross, net, and B:C ratios. Declarations Acknowledgements Not applicable. Clinical trial number Not Applicable. Author contributions Conceptualization, S.S., R.K.J. and B.P.; methodology and visualization, S.S., R.K.J., B.P. and S.K.V.; software, S.S., R.K.J. and B.P.; validation, S.S., R.K.J., B.P., S.K.V., C.B. and M.V.; formal analysis, S.S., R.K.J. and B.P.; investigation, S.S., R.K.J., B.P., S.K.V., C.B. and M.V.; resources, S.S., R.K.J., B.P. and S.K.V.; data curation, R.K.J., S.S. and B.P.; writing—original draft preparation, S.S., R.K.J. and B.P; writing—review and editing, S.S., R.K.J. B.P., S.K.V., C.B. and M.V. All authors reviewed the manuscript. Funding Not applicable. Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request (corresponding author: [email protected] ). Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Mangaldeep D, Singh M, Sharma A, Kumar R, Yadav AK. Productivity, profitability and sustainability of rice–wheat cropping system in Indo–Gangetic Plains of India. Agric Res. 2018;7(2):123–36. Gangwar B, Katyal V, Anand KV. Stability and efficiency of cropping systems in Chhattisgarh and Madhya Pradesh. Indian J Agric Sci. 2004;74(10):521–8. Singh P, Singh JP, Gill MS, Singh Y. Alternate cropping systems to sugarcane-ratoon-wheat in peri-urban areas of Meerut. In: Extended Summaries of the 3rd National Symposium on Integrated Farming Systems; 2007 Oct 26–28. Chaudhary VP, Gangwar B, Pandey DK. Auditing of energy use and output of different cropping systems in India. Agric Eng Int: CIGR J; 2006. Sharma RP, Pathak SK, Haque M, Raman KR. Diversification of traditional rice ( Oryza sativa )-based cropping system for sustainable production in South Bihar alluvial plains. Indian J Agron. 2004;49(4):218–22. Bhargavi B, Behera UK, Rana KS, Singh R. Productivity, resource-use efficiency and profitability of high-value crops embedded diversified cropping systems. Indian J Agric Sci. 2019;89(5):821–7. Prasad D, Yadava MS, Singh CS. Diversification of rice ( Oryza sativa )-based cropping systems for higher productivity, profitability and resource-use efficiency under irrigated ecosystem of Jharkhand. Indian J Agron. 2013;58(3):264–70. Walia SS, Gill MS, Bhushan B, Phutela RP, Aulakh CS. Alternate cropping systems to rice ( Oryza sativa )-wheat ( Triticum aestivum ) for Punjab. Indian J Agron. 2011;56(1):20–7. Kumar A, Tripathi HP, Yadav RA, Yadav DS. Diversification of rice ( Oryza sativa )–wheat ( Triticum aestivum ) cropping system for sustainable production in eastern Uttar Pradesh. Indian J Agron. 2008;53(1):18–21. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6170120","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":425553663,"identity":"85bcf31c-44a5-4549-8dc2-a28f71233a8d","order_by":0,"name":"Sameer Shrivastava","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYHAD5mPMEAZjA7Fa2NJI1sJjxkyUOvn204kPPu6xs9ve3vPtcWEbgzx/A3PbA3xaDM7kbjac8Sw5ec6Zs9uNZ7YxGM44wNhugFcLQ+42aZ4DzMkSEkAGbxsD4wYGxjYJvA7rf7v9958D9UAtOc9AWuwJamG4kbuNmeHAYTugFjaQlkSCWgxuvN0s2XPgeIIEzzFzY55zEskzDhN0WO7GDz8OVNtLsDc/e8xTZmPb397+DL/DoCCxAUIDFRMXOwwM9kSqGwWjYBSMgpEIAKUWRbnGHo1SAAAAAElFTkSuQmCC","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":true,"prefix":"","firstName":"Sameer","middleName":"","lastName":"Shrivastava","suffix":""},{"id":425553665,"identity":"03daf58c-0c99-426d-b5a8-8c488d39c3f2","order_by":1,"name":"Ratnesh Kumar Jha","email":"","orcid":"","institution":"Dr. Rajendra Prasad Central Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Ratnesh","middleName":"Kumar","lastName":"Jha","suffix":""},{"id":425553666,"identity":"e66906cd-6598-49a1-919e-d34d921b633a","order_by":2,"name":"Biswajit Pramanik","email":"","orcid":"","institution":"Dr. Rajendra Prasad Central Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Biswajit","middleName":"","lastName":"Pramanik","suffix":""},{"id":425553667,"identity":"10c3f9d1-aa99-42f7-b028-9ecc5009bac5","order_by":3,"name":"Chandra Bhushan","email":"","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":false,"prefix":"","firstName":"Chandra","middleName":"","lastName":"Bhushan","suffix":""},{"id":425553668,"identity":"92e8b162-cc50-47ab-aa5a-2b8a32ea09cd","order_by":4,"name":"Sunil Kumar Verma","email":"","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":false,"prefix":"","firstName":"Sunil","middleName":"Kumar","lastName":"Verma","suffix":""},{"id":425553669,"identity":"3c0427d6-81ef-4d74-9955-cff3a1df3845","order_by":5,"name":"Mohammad Vaheed","email":"","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Vaheed","suffix":""}],"badges":[],"createdAt":"2025-03-06 11:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6170120/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6170120/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78221955,"identity":"62cac6cb-b6a9-47a2-95e1-52e741bbd0ef","added_by":"auto","created_at":"2025-03-11 06:20:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1171661,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6170120/v1/cb02dfa9-c003-4993-a4ed-3dcc41c2ecb7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Deciphering most productive cropping systems for sustainable farming in middle Gangetic plains of Indian subcontinent","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRice\u0026ndash;wheat cropping system is the most dominant double\u0026ndash;cropping system in subtropical Asian countries, including China, Pakistan, Nepal, Bangladesh and India. In the Indo\u0026ndash;Gangetic Plains (IGP), this system covers approximately 10\u0026nbsp;million hectares (m ha) in India, 2 m ha in Pakistan, and 0.5 m ha each in Nepal and Bangladesh [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In India\u0026rsquo;s IGP alone, the rice\u0026ndash;wheat cropping system spans an area of 10.5\u0026nbsp;million hectares. However, this system has caused significant challenges in recent years, primarily due to the overexploitation of underground water resources to meet the high water demands of rice cultivation, resulting in a declining water table in many areas. Cropping system research focuses on growing crops in a specific sequence and studying their interactions with farm resources and technologies. It has been shown that including pulses, oilseeds, and vegetables in the system is more beneficial than continuous cereal cultivation. Such diversification not only improves soil health but also positively alters the economic dynamics of cropping systems [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In the state of Bihar, agriculture is also largely dominated by the rice\u0026ndash;wheat cropping system, which occupies about 72% of the gross cropped area and contributes to around 82% of the state's total food production. While rice is a necessity in the rainy season due to the midland and lowland conditions, the unpredictability of monsoon rains limits the scope for growing other crops during this period. During the winter season, wheat is the preferred crop due to its high productivity, stability, and resistance to major pests and diseases. Additionally, in medium land areas, \u003cem\u003eZaid\u003c/em\u003e (summer)crops such as maize, urd bean, mung bean, \u003cem\u003eZaid\u003c/em\u003e (summer)vegetables, and sunflowers are grown on a smaller scale after the rice\u0026ndash;wheat rotation. In response to climate change, upland crops are increasingly being shifted to midlands, and midland crops to lowlands, primarily due to reduced rainfall. However, these areas face risks of inundation and flash floods during the crop growth period because of the monsoon's unpredictability. To address these climatic challenges, cultivating crops in a systematic approach rather than in isolation offers better sustainability and profitability. An efficient cropping system is one that maximizes output while minimizing input requirements, ensuring both economic and environmental resilience.\u003c/p\u003e"},{"header":"Method and Materials","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study location\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe field experiment was conducted at the Crop Research Farm, Pusa, Bihar for one year in 2019\u0026ndash;2020 during all the three seasons: \u003cem\u003eRabi\u003c/em\u003e 2019\u0026ndash;20, \u003cem\u003eZaid\u0026nbsp;\u003c/em\u003e(summer) 2020 and \u003cem\u003eKharif\u003c/em\u003e 2020. The experimental plot, selected for this experiment, was a true representative of medium land where rice crop can be taken with/without supplemental irrigation but at the same time, it was also considered, while selecting the experimental plot, where rice crop can be replaced by suitable alternative crops like maize, finger millet and soybean, seeing the recent climatic stresses of drought might be due to late onset of monsoon, midseason dry spells or lesser rainfall. In \u003cem\u003eRabi\u003c/em\u003e 2019\u0026ndash;2020 and \u003cem\u003eZaid\u0026nbsp;\u003c/em\u003e(summer) 2020 usual crops were taken to see the compatibility of different cropping systems under the existing climatic stresses. The field was well connected to irrigation system for timely and assured irrigation. The experimental plots were having fairly uniform topography with homogenous fertility and soil characteristics suitable for medium land crop cultivation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Climate and weather\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr. Rajendra Prasad Central Agriculture University, Pusa, Bihar situated at Samastipur city on 25\u0026ordm;59\u0026rsquo; N latitude and 85\u0026ordm;48\u0026rsquo; E longitude on the bank of Budhi Gandak River. The average temperature of Pusa is 19 to 34\u0026ordm;C, the minimum temperature is recorded in January is 8.8\u0026ordm;C and maximum in 36.0\u0026ordm;C to 37.1\u0026ordm;C during April. Pusa is coming under subtropical and sub humid type climate. The average annual rainfall of this place is approximately 1234.7mm and more than 87 per cent of total rainfall is received from month of June to September.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Treatments and experimental details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experiment was conducted from October 2019 (starting of \u003cem\u003eRabi\u003c/em\u003e season) to October 2020 (end of \u003cem\u003eKharif\u003c/em\u003e season) with 10 treatments combination consisting of ten cropping system with three replications, which are as follows:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable No. 1 Treatments details\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment details of different cropping system\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e: R\u0026ndash;W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eRice\u0026mdash;wheat\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e2\u003c/sub\u003e: R\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eRice\u0026mdash;wheat \u0026mdash;Greengram\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e3\u003c/sub\u003e: R\u0026ndash;P +M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eRice\u0026mdash;potato+ maize\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e4\u003c/sub\u003e: R\u0026ndash;Mu\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eRice\u0026mdash;mustard\u0026mdash;Greengram\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e5\u003c/sub\u003e: R\u0026ndash;Le\u0026ndash;M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eRice\u0026mdash;lentil \u0026mdash;maize\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e6\u003c/sub\u003e: M\u0026ndash;Mu\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eMaize\u0026mdash;mustard\u0026mdash;Greengram\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e7\u003c/sub\u003e: Fm\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eFinger millet\u0026mdash;wheat \u0026mdash;Greengram\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e8\u003c/sub\u003e: Sb\u0026ndash;P\u0026ndash;Sf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eSoybean\u0026mdash;potato\u0026mdash;sunflower\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e9\u003c/sub\u003e: R\u0026ndash;Pg\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eRice\u0026mdash;pea\u0026mdash;wheat\u0026mdash;Greengram\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eT\u003csub\u003e10\u003c/sub\u003e: R\u0026ndash;Mu\u0026ndash;M+Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003eRice\u0026mdash;mustard\u0026mdash;maize +Greengram\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe investigation plot\u0026apos;s soil was calcareous in nature with an initial pH of 8.2, Electrical conductivity of 0.35 dS/m, low organic carbon 0.38 percent, low available nitrogen 237 kg/ha, medium available phosphorus 12.23 kg/ha, and medium available potassium 131 kg/ha. The experiment was laid out in randomized complete block design (RCBD) with 10 treatments of cropping system \u003cem\u003eviz\u003c/em\u003e. Rice\u0026ndash;Wheat, Rice\u0026ndash;Wheat\u0026ndash;Greengram, Rice\u0026ndash;Potato+Maize, Rice\u0026ndash;Mustard\u0026ndash;Greengram, Rice\u0026ndash;Lentil\u0026ndash;Maize, Maize\u0026ndash;Mustard\u0026ndash;Greengram, Finger millet\u0026ndash;Wheat\u0026ndash;Greengram, Soybean\u0026ndash;Potato\u0026ndash;Sunflower, Rice\u0026ndash;Pea\u0026ndash;Wheat\u0026ndash;Greengram, Rice\u0026ndash;Mustard\u0026ndash;Maize+Greengram in three replications. The gross plot size was 5m x 5m and the net plot size was 4m x 4m were separated by 1m irrigation channel and 0.5\u0026ndash;meter path. The experiment was started from \u003cem\u003eRabi\u003c/em\u003e\u0026ndash;2019\u0026ndash;20 and ended in \u003cem\u003eKharif\u003c/em\u003e\u0026ndash;2020. In \u003cem\u003eRabi\u0026nbsp;\u003c/em\u003eseason wheat, potato, maize, lentil, mustard, pea was grown. After harvest of these crops in \u003cem\u003eZaid\u0026nbsp;\u003c/em\u003e(summer) season Greengram, maize and sunflower were grown. In \u003cem\u003eKharif\u0026nbsp;\u003c/em\u003eseason, after the harvest of \u003cem\u003eZaid\u0026nbsp;\u003c/em\u003e(summer) season crops rice, maize, soybean and finger millets were grown. The crops were grown with the recommended package and practices and recommended doses of all the inputs were applied for crops.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Soil analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess soil health, one composite soil sample (0\u0026ndash;15 cm) was collected with the help of auger before the initiation of the experiment from 20 locations of the experimental area as per the standard procedure. The 30 composite soil samples (five places of each plot) after completion of two years of the experiment were collected from each treatment with their all three replications. The samples were analysed for pH, electrical conductivity (EC), organic carbon (OC), available nitrogen (N), phosphorus (P) and potassium (K), particle density and porosity. Soil samples for bulk density were taken from 0 to 15 cm soil depth with the help of core sampler at initiation and after completion of two years field trial as per the standard procedure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Crop sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCrops were harvested manually from the net plot area and sun\u0026ndash;dried. After that, the produce was threshed, cleaned, winnowed and weighed to obtain grain/seed yield of rice, wheat and mustard. However, in the case of potato, cabbage, berseem fodder, maize fodder, sudan grass fodder and cowpea fodder, fresh weight of economic produce was recorded. In Greengram, one or two pickings were done at a certain interval and produce was sun\u0026ndash;dried. Further, sun\u0026ndash;dried produce was threshed manually, cleaned and weighed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable No 2: Details of crops, varieties and cultural operations followed in different cropping system during 2019\u0026ndash;2020\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSI. No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOperations\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eKharif\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eRabi\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eZaid\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e(summer)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eCrops and varieties\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice: Rajendra Bhagwati\u003c/p\u003e\n \u003cp\u003eMaize: Shaktiman\u0026ndash;5\u003c/p\u003e\n \u003cp\u003eFinger millet: Rajendra Madua\u0026ndash;1\u003c/p\u003e\n \u003cp\u003eSoybean: B S\u0026ndash;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWheat: HD 2967\u003c/p\u003e\n \u003cp\u003ePotato: Kufri Arun\u003c/p\u003e\n \u003cp\u003eMaize: Shaktiman\u0026ndash;5\u003c/p\u003e\n \u003cp\u003eMustard: Rajendra Sufalam\u003c/p\u003e\n \u003cp\u003eLentil: Pant L\u0026ndash;406\u003c/p\u003e\n \u003cp\u003ePea: Azad Pea\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGreengram: HUM\u0026ndash;16\u003c/p\u003e\n \u003cp\u003eMaize: Shaktiman\u0026ndash;5\u003c/p\u003e\n \u003cp\u003eSunflower: Surya\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eSpacing\u003c/p\u003e\n \u003cp\u003e( R X P ) in cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice: 20 x 15\u003c/p\u003e\n \u003cp\u003eMaize: 60 x 20\u003c/p\u003e\n \u003cp\u003eFinger millet: 22 x 10\u003c/p\u003e\n \u003cp\u003eSoybean: 30 x 45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWheat: 22.5\u003c/p\u003e\n \u003cp\u003ePotato: 60 x 20\u003c/p\u003e\n \u003cp\u003eMaize: 60 x 20\u003c/p\u003e\n \u003cp\u003eMustard:30 x 15\u003c/p\u003e\n \u003cp\u003eLentil: 30 x 10\u003c/p\u003e\n \u003cp\u003ePea: 60 x 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGreengram: 30 x 10\u003c/p\u003e\n \u003cp\u003eMaize: 60 x 20\u003c/p\u003e\n \u003cp\u003eSunflower: 45 x 20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eSowing date\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice: 16/06/2020\u003c/p\u003e\n \u003cp\u003eMaize: 16/07/2020\u003c/p\u003e\n \u003cp\u003eFinger millet: 22/06/2020\u003c/p\u003e\n \u003cp\u003eSoybean: 03/07/2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWheat: 20/11/2019, Maize: 06/11/2019\u003c/p\u003e\n \u003cp\u003eWheat (Late): 20/12/2019, Lentil: 06/11/2019\u003c/p\u003e\n \u003cp\u003ePotato: 06/11/2019,\u003c/p\u003e\n \u003cp\u003ePea: 14/10/2019\u003c/p\u003e\n \u003cp\u003eMustard: 06/11/2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGreengram: 12/04/2020\u003c/p\u003e\n \u003cp\u003eMaize: 20/03/2020\u003c/p\u003e\n \u003cp\u003eSunflower: 03/03/2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eFertilizer applied\u003c/p\u003e\n \u003cp\u003eN\u0026ndash;P2O5\u0026ndash;K2O (Kg/ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice: 120:60:40\u003c/p\u003e\n \u003cp\u003eMaize: 100:60:80\u003c/p\u003e\n \u003cp\u003eFinger millet: 40:30:30\u003c/p\u003e\n \u003cp\u003eSoybean: 20:60:40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWheat: 120:60:40\u003c/p\u003e\n \u003cp\u003eWheat (Late): 80:40:20\u003c/p\u003e\n \u003cp\u003ePotato: 150:90:100\u003c/p\u003e\n \u003cp\u003eMustard: 80:40:40\u003c/p\u003e\n \u003cp\u003eLentil: 20:40:40\u003c/p\u003e\n \u003cp\u003ePea: 20:40;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGreengram: 20:45:20\u003c/p\u003e\n \u003cp\u003eMaize: 80:40:30\u003c/p\u003e\n \u003cp\u003eSunflower: 30:80:40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eSeed rate (kg/ha)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice:30\u003c/p\u003e\n \u003cp\u003eMaize: 20\u003c/p\u003e\n \u003cp\u003eFinger millet: 10\u003c/p\u003e\n \u003cp\u003eSoybean: 75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWheat (timely): 100, Maize: 20\u003c/p\u003e\n \u003cp\u003eWheat (late) 125, Mustard: 5\u003c/p\u003e\n \u003cp\u003ePotato: 2000, Lentil: 30\u003c/p\u003e\n \u003cp\u003ePea: 90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGreengram: 35\u003c/p\u003e\n \u003cp\u003eMaize:20\u003c/p\u003e\n \u003cp\u003eSunflower: 6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eSowing method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice: Transplanting\u003c/p\u003e\n \u003cp\u003eMaize: Ridge and Furrow method\u003c/p\u003e\n \u003cp\u003eFinger millet: Transplanting\u003c/p\u003e\n \u003cp\u003eSoybean: Ridge and Furrow method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWheat: line sowing\u003c/p\u003e\n \u003cp\u003ePotato: Ridge and Furrow method\u003c/p\u003e\n \u003cp\u003eMaize: Ridge and Furrow method\u003c/p\u003e\n \u003cp\u003eMustard: line sowing\u003c/p\u003e\n \u003cp\u003eLentil: line sowing\u003c/p\u003e\n \u003cp\u003ePea: line sowing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGreengram: line sowing\u003c/p\u003e\n \u003cp\u003eMaize: Ridge and Furrow\u003c/p\u003e\n \u003cp\u003eSunflower: line sowing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eHerbicides applied and inter\u0026ndash;cultivations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice: Pretilachlor\u003c/p\u003e\n \u003cp\u003eMaize: Atrazine\u003c/p\u003e\n \u003cp\u003eSoybean: Imazethapyr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWheat: Sulphosulfuron\u003c/p\u003e\n \u003cp\u003eLentil: Pendimethalin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eMaize: Atrazine\u003c/p\u003e\n \u003cp\u003eSunflower: Pendimethalin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003ePlant protections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice: Folidal\u003c/p\u003e\n \u003cp\u003eMaize: Carbofuran\u003c/p\u003e\n \u003cp\u003eSoybean: Chlorpyriphos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003ePotato: Indofil M 45\u003c/p\u003e\n \u003cp\u003eMaize: carbofuran\u003c/p\u003e\n \u003cp\u003eMustard: Imidacloprid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGreengram: monochrotophos\u003c/p\u003e\n \u003cp\u003eMaize: carbofuran\u003c/p\u003e\n \u003cp\u003eSunflower: Phorate 10G\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eHarvesting date\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRice: 10/10/2020 (116 DAT)\u003c/p\u003e\n \u003cp\u003eMaize: 20/10/2020 (96 DAS)\u003c/p\u003e\n \u003cp\u003eFinger millet: 24/10/2020 (124 DAS)\u003c/p\u003e\n \u003cp\u003eSoybean: 13/10/2020 (102 DAS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eWheat: 5/04/2020 (137 DAS)\u003c/p\u003e\n \u003cp\u003eWheat (Late): 10/04/2020(112DAS)\u003c/p\u003e\n \u003cp\u003ePotato: 12/02/2020 (98 DAS)\u003c/p\u003e\n \u003cp\u003eLentil: 15/03/2020 (130 DAS)\u003c/p\u003e\n \u003cp\u003ePea: 18/12/2019 (65 DAS)\u003c/p\u003e\n \u003cp\u003eMustard: 09/03/2020 (124 DAS)\u003c/p\u003e\n \u003cp\u003eMaize: 22/04/2020 (168 DAS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGreengram: 13/06/2020 (62 DAS)\u003c/p\u003e\n \u003cp\u003eMaize: 29/06/2020 (101 DAS)\u003c/p\u003e\n \u003cp\u003eSunflower: 15/06/2020 (104 DAS)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Economic study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the economic analysis, the price of individual input and output was assumed to be stable during both the years of experimentation. The total number of labours required for various agronomic practices used for different cropping sequences were noted plot\u0026ndash;wise, and the total requirement of labour per hectare for each sequence was worked out. The economics was calculated as per current year input cost and economic value of different crop production in the local market\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8 Cropping system analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8.1 Crop Productivity:\u0026nbsp;\u003c/strong\u003eYield per unit area (kg/ha).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCrop productivity=\u003c/strong\u003eYield of a crop/ Area of a crop\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8.2 System Productivity:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquivalent yield of system=\u003c/strong\u003eYield of crop A + Crop A equivalent yield of crop B Similarly if there are thee crops A, B and C in the system then equivalent yield of system (in crop A equivalent yield) =Yield of crop A + Crop A equivalent yield of crop B + Crop A equivalent yield of crop C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8.3 Rice Equivalent Yield:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eREY =\u0026nbsp;\u003c/strong\u003eyield of crop a (Kg) x Price of crop a (Rs.) / Price of rice (Rs.)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8.4 Land Use Efficiency (%):\u0026nbsp;\u003c/strong\u003eLand used during the agricultural year.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLUE =\u0026nbsp;\u003c/strong\u003eTotal duration of crop in cropping system/365 x 100\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8.5 Apparent water use productivity (kg. grain/ha\u0026ndash;mm):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApparent water productivity is calculated by dividing equivalent yield of the system per ha. divided by total quantity of water used in ha. of land in mm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAWP\u0026nbsp;\u003c/strong\u003e= yield (kg) / irrigation water (ha\u0026ndash;mm)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8.6 Nutrient use productivity (kg grain/kg nutrient used):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNutrient use productivity is calculated by dividing equivalent yield of the system/ha divided by total quantity of nutrients used per ha.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.9 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data after collecting from field and after chemical analysis were analysed statistically in order to reduce error and to find out best treatment. The data obtained for different parameter were analysed using method given by Gomez and Gomez (1984).\u003c/p\u003e"},{"header":"Result and Discussion","content":"\u003cp\u003e\u003cstrong\u003eSystem productivity of cropping system (Kg REY/ha):\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study, 10 different cropping systems suitable for medium land situations were tested and it was found that rice\u0026ndash;poato+maize cropping system gave significantly higher rice equivalent yield (24.7t/ha) than other treatments except soybean\u0026ndash;potato\u0026ndash;sunflower (22.4t/ha) which was found to be at par. Soybean\u0026ndash;potato\u0026ndash;sunflower cropping system (22.4t/ha) was found to be the second most productive system with significantly higher Rice equivalent yield than rest of the cropping systems except rice\u0026ndash;potato+maize. Rice\u0026ndash;mustard\u0026ndash;maize+Greengram (14.8t/ha) was found third most productive system with significantly higher rice equivalent yield than rice\u0026ndash;wheat (7.8t/ha), rice\u0026ndash;mustard\u0026ndash;Greengram (10.8t/ha), maize\u0026ndash;mustard\u0026ndash;Greengram (11.5t/ha), however, this system was at par with rice\u0026ndash;wheat\u0026ndash;Greengram (12.4t/ha), rice\u0026ndash;lentil\u0026ndash;maize (12.5t/ha) finger millet\u0026ndash;wheat\u0026ndash;Greengram (12.5t/ha) and rice\u0026ndash;pea\u0026ndash;wheat\u0026ndash;Greengram (14.4t/ha). Rice\u0026ndash;wheat cropping system was found to have the lowest rice equivalent yield (7.8 t/ha) in comparison to all other cropping system, however, it was at par with rice\u0026ndash;mustard\u0026ndash;Greengram (10.8 t/ha). So, the result revealed that rice\u0026ndash;potato+maize (24.7t/ha) cropping system having better performance in terms of rice equivalent yield in the existing climate.\u0026nbsp;These findings are consistent with those of Singh et al.\u003cem\u003e\u0026nbsp;\u003c/em\u003e[3] who identified rice-pea-okra as the most productive sequence in eastern Uttar Pradesh, followed by rice-pea-onion, India. Choudhary et al. [4] found increased system productivity when wheat was replaced with vegetables like radish and potato in a rice\u0026ndash; wheat system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProduction efficiency (Kg/ha/day):\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn production efficiency analysis, rice\u0026ndash;potato+maize cropping system was found to have the highest production efficiency (86.9 kg/ha/day) in comparison to all other cropping systems. Soybean\u0026ndash;potato\u0026ndash;sunflower cropping system was found second highest production efficiency (76.7 kg/ha/day) which was significantly higher in comparison to all other cropping system except rice\u0026ndash;potato+maize. Rice\u0026ndash;mustard\u0026ndash;maize+Greengram (43.5 kg/ha/day) cropping system was found third highest production efficiency which was significantly higher in comparison\u0026ndash; to rice\u0026ndash;wheat cropping system (30.9 kg/ha/day) except rice\u0026ndash;potato+maize and soybean\u0026ndash;potato\u0026ndash;sunflower\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eand this cropping system was found to be at par with rice\u0026ndash;wheat\u0026ndash;Greengram (39.4 kg/ha/day), rice\u0026ndash;mustard\u0026ndash;Greengram (35.9 kg/ha/day), rice\u0026ndash;lentil\u0026ndash;maize (36.1 kg/ha/day), maize\u0026ndash;mustard\u0026ndash;Greengram (40.8 kg/ha/day), finger millet\u0026ndash;wheat\u0026ndash;Greengram (38.6 kg/ha/day) and rice\u0026ndash;pea\u0026ndash;wheat\u0026ndash;Greengram (40.7 kg/ha/day). The traditional cropping system rice\u0026ndash;wheat gave lowest production efficiency (30.9kg/ha/day) in comparison to all other cropping systems. According to Sharma et al. [5], crop intensification by include vegetables and leguminous crops boosted production efficiency. Bhargavi et al. [6] discovered that the bottle gourd-onion cropping system had the best system productivity, resulting in the highest production efficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelative production efficiency (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRice\u0026ndash;potato+maize cropping system was found significantly highest relative production efficiency (316%) in comparison to rice\u0026ndash;wheat (100%) cropping system. Soybean\u0026ndash;potato\u0026ndash;sunflower cropping system was found second highest production efficiency (289%) which was significantly higher in comparison to other cropping systems except rice\u0026ndash;potato+maize cropping system. Rice\u0026ndash;mustard\u0026ndash;maize+Greengram cropping system (191%) was found having third highest production efficiency which was significantly higher in comparison to rice\u0026ndash;wheat (100%), rice\u0026ndash;mustard\u0026ndash;Greengram (138%), maize\u0026ndash;mustard\u0026ndash;Greengram (147%) cropping systems except rice\u0026ndash;potato+maize and soybean\u0026ndash;potato\u0026ndash;sunflower, and this cropping system was at par with rice\u0026ndash;wheat\u0026ndash;Greengram (158%), rice\u0026ndash;lentil\u0026ndash;maize (160%), finger millet\u0026ndash;wheat\u0026ndash;Greengram (161%) and rice\u0026ndash;pea\u0026ndash;wheat\u0026ndash;Greengram (185%) whereas rice\u0026ndash;wheat cropping system resulted in lowest production efficiency (100%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLand use efficiency (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLand use efficiency was maximum in rice\u0026ndash;pea\u0026ndash;wheat\u0026ndash;Greengram cropping system (97%) followed by rice\u0026ndash;lentil\u0026ndash;maize (95%), rice\u0026ndash;mustard\u0026ndash;maize+Greengram (93%) and finger millet\u0026ndash;wheat\u0026ndash;Greengram. Lowest land use efficiency was found in rice\u0026ndash;wheat cropping system which was 69% among all other cropping system. The findings are in consistent with those of Prasad et al [7]. The existing rice\u0026ndash;wheat system had the lowest land-use efficiency, as the land sat fallow for more than two months each year.\u0026nbsp;According to Sharma et al. [5], crop intensification by include vegetables and leguminous crops boosted production and land-use efficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNutrient use productivity (kg REY/kg nutrient applied)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn statistical analysis rice\u0026ndash;poato+maize cropping system was found having significantly higher nutrient use productivity (44.1Kg REY/kg nutrient applied) in comparison to all other cropping system. Soybean\u0026ndash;potato\u0026ndash;sunflower cropping system was found second highest production efficiency (35.5 kg REY/ kg nutrient applied) which was significantly higher in comparison to other cropping system except rice\u0026ndash;potato+maize cropping system. Rice\u0026ndash;mustard\u0026ndash;maize+Greengram (28.0 kg REY/kg nutrient applied) was found third cropping system having highest production efficiency which was significantly higher in comparison to rice\u0026ndash;wheat cropping system (23.6 kg REY/kg nutrient applied ) except rice\u0026ndash;potato+maize and soybean\u0026ndash;potato\u0026ndash;sunflower, and this cropping system was found at par with rice\u0026ndash;wheat\u0026ndash;Greengram (23.6 kg REY/kg nutrient applied), rice\u0026ndash;mustard\u0026ndash;Greengram (23.3 kg REY/kg nutrient applied), rice\u0026ndash;lentil\u0026ndash;maize (27.5 kg REY/kg nutrient applied), maize\u0026ndash;mustard\u0026ndash;Greengram (23.7 kg REY/kg nutrient applied), finger millet\u0026ndash;wheat\u0026ndash;Greengram (30.1 kg REY/kg nutrient applied) and rice\u0026ndash;pea\u0026ndash;wheat\u0026ndash;Greengram (26.0 kg REY/kg nutrient applied) cropping system. The traditional cropping system rice\u0026ndash;wheat was found lowest production efficiency (17.8 kg REY/kg nutrient applied) which was at par with rice\u0026ndash;mustard\u0026ndash;Greengram cropping system. Bhargavi et al. [6] found the similar result that bottle gourd-onion cropping system have highest system productivity due to high production potential crops and the relative production efficiency was also high in this system due to the production potential of crops.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable No. 3: System productivity, production efficiency\u003c/strong\u003e\u003cstrong\u003e, relative production efficiency, land use efficiency\u003c/strong\u003e\u003cstrong\u003e, nutrient use productivity of different cropping system\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"629\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSystem productivity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(kg/ha)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProduction efficiency\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(kg/ha/day)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRelative production\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eefficiency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLand use efficiency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNutrient use productivity (kg REY/kg nutrient applied)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e: R\u0026ndash;W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e7817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e30.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e17.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e2\u003c/sub\u003e: R\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e12399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e39.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e23.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e3\u003c/sub\u003e: R\u0026ndash;P +M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e24684\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e86.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e44.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e4\u003c/sub\u003e: R\u0026ndash;Mu\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e10843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e35.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e5\u003c/sub\u003e: R\u0026ndash;Le\u0026ndash;M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e12520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e6\u003c/sub\u003e: M\u0026ndash;Mu\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e11497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e40.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e7\u003c/sub\u003e: Fm\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e12481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e38.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e30.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e8\u003c/sub\u003e: Sb\u0026ndash;P\u0026ndash;Sf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e22360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e73.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e35.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e9\u003c/sub\u003e: R\u0026ndash;Pg\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e14433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e40.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e26.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eT\u003csub\u003e10\u003c/sub\u003e: R\u0026ndash;Mu\u0026ndash;M+Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e14829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e43.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e28.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eSEm \u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003eCD (p=0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e3102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEconomics of different treatments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCost of cultivation (Rs./ha)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data on cost of cultivation revealed that rice\u0026ndash;potato+maize cropping system incurred maximum cost of cultivation among all other cropping systems. It might be due to high input cost in terms of seed, labour, land preparation, high volume of potato seed tubers and high requirement of fertilizers in potato. The next in order was soybean\u0026ndash;potato\u0026ndash;sunflower cropping system due to the high cost and high requirement of potato tubers for sowing and high fertilizer requirement of potato. Higher seed cost of soybean was also fund to affect the cost of cultivation. The result is in confirmation with Walia et al. [8] who reported highest cost of cultivation due to inclusion of potato and onion in the cropping systems having high demand of human labour and fertilizer requirement. The lowest cost of cultivation in rice\u0026ndash;wheat cropping system can be attributed to low seed cost of rice and wheat and low labour requirement in comparison to other cropping systems.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGross return (Rs./ha)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data of gross return revealed that rice\u0026ndash;potato+maize was having the highest gross return than all other cropping systems. This might be due to higher tonnage of \u003cem\u003eRabi\u003c/em\u003e maize and potato and high market price. The REY of this system is highest among all other treatments, so the gross return is also highest in this system. The next system in the order was soybean\u0026ndash;potato\u0026ndash;sunflower having second highest gross return. This is attributed to higher REY of this cropping system in comparison to others. The next system in order was rice\u0026ndash;pea\u0026ndash;wheat\u0026ndash;Greengram which gave third highest gross return than others, it might be due to high REY of this system because pea and wheat two crops was grown in one season. Fourth highest gross return producing cropping system was rice\u0026ndash;mustard\u0026ndash;maize+Greengram than other cropping systems. It can be attributed because maize is high yield producing crop, so the REY of this system was high which directly affected the gross return of this system. Walia et al. [8] also found the same result that inclusion of high yielding crops such as potato and maize give higher gross return because of higher value of produce.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNet return (Rs./ha)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data of net return showed that significantly higher net return was realized from rice\u0026ndash;potato+maize cropping system. It could be because the addition of potato and maize intercropping in the system, in addition to increasing system productivity due to their higher yield, also fetched a decent price, resulting in a larger net return. The next in order was soybean\u0026ndash;potato\u0026ndash;sunflower cropping system which gave second highest net return. Since the price of crops taken in the system is generally high, so the system productivity is high thereby increasing net return. Rice\u0026ndash;mustard\u0026ndash;maize+greengram was third most remunerative system in terms of net return. It was attributed due to inclusion of \u003cem\u003eZaid\u0026nbsp;\u003c/em\u003e(summer)maize+greengram intercropping in cropping system that improved the system productivity of this system by production of high tonnage, fetched good price thereby, enhancing the net returns. Kumar et al., 2008 found that including vegetable crops such as potato, onion, cabbage, garlic, coriander, cowpea, and okra in cropping systems increased system productivity while also raising market prices, resulting in higher net returns. Kumar. et al., [9] found that incorporating vegetable crops within rice\u0026ndash;based crop sequences increased net returns. Rice\u0026ndash;wheat cropping system gave lowest net return, it might be due to low system productivity thereby, low net return.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB: C ratio\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data of net return showed that significantly higher benefit: cost ratio was realized from rice\u0026ndash;potato+maize cropping system. It might be due to high net return in this system. Potato and maize intercropping in the system, besides enhancing the system productivity due to their higher yield, fetched good price thereby, increasing net return and B: C ration also.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe next in order was soybean\u0026ndash;potato\u0026ndash;sunflower cropping system that gave second highest benefit: cost ratio. It can be due to high price crops grown in this system, so the system productivity is high thereby, increasing net return. So the B: C ratio is also high. Rice\u0026ndash;mustard\u0026ndash;maize+Greengram was third most remunerative system in terms of B: C ratio. It was attributed due to inclusion of \u003cem\u003eZaid\u0026nbsp;\u003c/em\u003e(summer)maize+ Greengram intercropping in cropping system, it improved the system productivity of this system by production of high tonnage, fetched good price thereby, increasing net return. So, the B: C ratio is also high. Rice\u0026ndash;wheat cropping system gave lowest net return, it might be due to low system productivity and low net return of this system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.11 Economics of different cropping systems:\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"102%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost of cultivation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGross return\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNet return\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB: C ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e1\u003c/sub\u003e: R\u0026ndash;W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e74897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e166862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e91964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e2\u003c/sub\u003e: R\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e101223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e253478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e152254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e3\u003c/sub\u003e: R\u0026ndash;P +M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e155693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e463583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e307889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e4\u003c/sub\u003e: R\u0026ndash;Mu\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e92403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e205029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e112626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e5\u003c/sub\u003e: R\u0026ndash;Le\u0026ndash;M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e94347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e236194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e141847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e6\u003c/sub\u003e: M\u0026ndash;Mu\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e82923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e214763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e131839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e7\u003c/sub\u003e: Fm\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e91755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e253715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e161959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e8\u003c/sub\u003e: Sb\u0026ndash;P\u0026ndash;Sf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e151319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e417689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e266370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e9\u003c/sub\u003e: R\u0026ndash;Pg\u0026ndash;W\u0026ndash;Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e126483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e290662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e164178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eT\u003csub\u003e10\u003c/sub\u003e: R\u0026ndash;Mu\u0026ndash;M+Gg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e111542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e279445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e167903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eSEm \u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e19545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e19545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 34px;\"\u003e\n \u003cp\u003eCD (p=0.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e58061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e58061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSystem productivity analysis found that Rice\u0026ndash;potato\u0026thinsp;+\u0026thinsp;maize cropping system gave significantly higher rice equivalent yield (24.7 t/ha) than other treatments except soybean\u0026ndash;potato\u0026ndash;sunflower (22.4 t/ha) which was found to be at par. In production efficiency analysis, rice\u0026ndash;potato\u0026thinsp;+\u0026thinsp;maize cropping system was found to have the highest production efficiency (86.9 kg/ha/day) in comparison to all other cropping systems. Soybean\u0026ndash;potato\u0026ndash;sunflower cropping system was found second highest production efficiency (76.7 kg/ha/day). Rice\u0026ndash;poato\u0026thinsp;+\u0026thinsp;maize cropping system was found having significantly higher nutrient use productivity (44.1 Kg REY/kg nutrient applied) in comparison to all other cropping system. Soybean\u0026ndash;potato\u0026ndash;sunflower cropping system was found having second highest production efficiency (35.5 kg REY/ kg nutrient applied). Rice\u0026ndash;potato\u0026thinsp;+\u0026thinsp;maize cropping system was found significantly highest relative production efficiency (316%) in comparison to rice\u0026ndash;wheat (100%) cropping system. Soybean\u0026ndash;potato\u0026ndash;sunflower cropping system was found second highest production efficiency (289%). Land use efficiency was maximum in rice\u0026ndash;pea\u0026ndash;wheat\u0026ndash;Greengram cropping system (97%) followed by rice\u0026ndash;lentil\u0026ndash;maize (95%) and rice\u0026ndash;mustard\u0026ndash;maize\u0026thinsp;+\u0026thinsp;Greengram (93%).\u003c/p\u003e \u003cp\u003eRice\u0026ndash;potato\u0026thinsp;+\u0026thinsp;maize (1,55,693 Rs/ha) was having maximum cost of cultivation among all cropping systems followed by, soybean\u0026ndash;potato\u0026ndash;sunflower (1,51,319 Rs/ha). Rice\u0026ndash;potato\u0026thinsp;+\u0026thinsp;maize cropping system gave significantly higher gross return (4,63,583 Rs/ha) in comparison with all other cropping system which was at par with soybean\u0026ndash;potato\u0026ndash;sunflower (4,17,689 Rs/ha) cropping system. Rice\u0026ndash;potato\u0026thinsp;+\u0026thinsp;maize cropping system gave maximum net return (3,07,889 Rs/ha) in comparison with all other cropping systems except soybean\u0026ndash;potato\u0026ndash;sunflower (2,66,370 Rs/ha) cropping system which was at par with rice\u0026ndash;potato\u0026thinsp;+\u0026thinsp;maize cropping system. Rice\u0026ndash;potato\u0026thinsp;+\u0026thinsp;maize cropping system gave highest B:C ratio (3.0) in comparison to other cropping system which was at par with soybean\u0026ndash;potato\u0026ndash;sunflower (2.8), finger millet\u0026ndash;wheat\u0026ndash;Greengram (2.8), maize\u0026ndash;mustard\u0026ndash;Greengram (2.6), rice\u0026ndash;wheat\u0026ndash;Greengram (2.5), rice\u0026ndash;lentil\u0026ndash;maize (2.5), rice\u0026ndash;mustard\u0026ndash;maize\u0026thinsp;+\u0026thinsp;Greengram (2.5) cropping systems. There was little increase in nutrient content of soil in terms of available nitrogen, available phosphorus and available potassium over the initial value in those cropping systems where legume crops were grown but this could not reach the level of significance.\u003c/p\u003e \u003cp\u003eThe Rice\u0026ndash;Potato\u0026thinsp;+\u0026thinsp;maize cropping system emerges as the most efficient and productive system overall, delivering the highest yield, nutrient use efficiency, and production efficiency, making it an ideal choice for maximizing resource use. The Soybean\u0026ndash;Potato\u0026ndash;Sunflower system, while second, also demonstrates strong performance, particularly in production efficiency and nutrient use. For systems focused on land use, Rice\u0026ndash;Pea\u0026ndash;Wheat\u0026ndash;Greengram offers the best potential. The rice\u0026ndash;potatoes\u0026ndash;maize cropping system was discovered to have the highest gross, net, and B:C ratios.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, S.S., R.K.J. and B.P.; methodology and visualization, S.S., R.K.J., B.P. and S.K.V.; software, S.S., R.K.J. and B.P.; \u0026nbsp;validation, S.S., R.K.J., B.P., S.K.V., C.B. and M.V.; formal analysis, S.S., R.K.J. and B.P.; investigation, S.S., R.K.J., B.P., S.K.V., C.B. and M.V.; resources, S.S., R.K.J., B.P. and S.K.V.; data curation, R.K.J., S.S. and B.P.; writing\u0026mdash;original draft preparation, S.S., R.K.J. and B.P; writing\u0026mdash;review and editing, S.S., R.K.J. B.P., S.K.V., C.B. and M.V. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request (corresponding author: [email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMangaldeep D, Singh M, Sharma A, Kumar R, Yadav AK. Productivity, profitability and sustainability of rice\u0026ndash;wheat cropping system in Indo\u0026ndash;Gangetic Plains of India. Agric Res. 2018;7(2):123\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGangwar B, Katyal V, Anand KV. Stability and efficiency of cropping systems in Chhattisgarh and Madhya Pradesh. Indian J Agric Sci. 2004;74(10):521\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh P, Singh JP, Gill MS, Singh Y. Alternate cropping systems to sugarcane-ratoon-wheat in peri-urban areas of Meerut. In: Extended Summaries of the 3rd National Symposium on Integrated Farming Systems; 2007 Oct 26\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChaudhary VP, Gangwar B, Pandey DK. Auditing of energy use and output of different cropping systems in India. Agric Eng Int: CIGR J; 2006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma RP, Pathak SK, Haque M, Raman KR. Diversification of traditional rice (\u003cem\u003eOryza sativa\u003c/em\u003e)-based cropping system for sustainable production in South Bihar alluvial plains. Indian J Agron. 2004;49(4):218\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhargavi B, Behera UK, Rana KS, Singh R. Productivity, resource-use efficiency and profitability of high-value crops embedded diversified cropping systems. Indian J Agric Sci. 2019;89(5):821\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrasad D, Yadava MS, Singh CS. Diversification of rice (\u003cem\u003eOryza sativa\u003c/em\u003e)-based cropping systems for higher productivity, profitability and resource-use efficiency under irrigated ecosystem of Jharkhand. Indian J Agron. 2013;58(3):264\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalia SS, Gill MS, Bhushan B, Phutela RP, Aulakh CS. Alternate cropping systems to rice (\u003cem\u003eOryza sativa\u003c/em\u003e)-wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e) for Punjab. Indian J Agron. 2011;56(1):20\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar A, Tripathi HP, Yadav RA, Yadav DS. Diversification of rice (\u003cem\u003eOryza sativa\u003c/em\u003e)\u0026ndash;wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e) cropping system for sustainable production in eastern Uttar Pradesh. Indian J Agron. 2008;53(1):18\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Rice equivalent yield, Nutrient use productivity, water use productivity","lastPublishedDoi":"10.21203/rs.3.rs-6170120/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6170120/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe field experiments were conducted during 2020– 2021 at the Dr Rajendra Prasad Central Agricultural University, Samastipur, Bihar, India. The main aim of the study was to find out a suitable cropping system to give higher productivity and profitability. Ten cropping systems, \u003cem\u003eviz\u003c/em\u003e. Rice–Wheat, Rice–Wheat–Greengram, Rice–Potato+maize, Rice–Mustard–Greengram, Rice–Lentil–Maize, Maize–Mustard–Greengram, Finger millet–Wheat–Greengram, Soybean–Potato–Sunflower, Rice–Pea–Wheat–Greengram, Rice–Mustard–Maize+Greengram were evaluated in a randomized complete block design with three replications. Results suggested that the highest system productivity was obtained from the Rice–Potato+maize (24 t/ha) cropping system followed by soybean-potato-sunflower (22 t/ha) than all other cropping systems, however, these were at par. Water productivity calculated on net return basis was found highest in rice-poato+maize (29 Rs/m\u003csup\u003e3\u003c/sup\u003e water applied) and was followed by soybean-potato-sunflower (25 Rs/m\u003csup\u003e3\u003c/sup\u003e water applied) cropping system and was statistically at par. Rice-potato+maize cropping system resulted in maximum net return (3,07,889 Rs/ha) in comparison to all other cropping systems followed by soybean-potato-sunflower (2,66,370 Rs/ha) cropping system.\u003cstrong\u003e \u003c/strong\u003eRice-potato+maize cropping system gave highest B-C ratio (3.0) followed by soybean-potato-sunflower (2.8) and finger millet-wheat-green gram (2.8) cropping systems.\u003c/p\u003e","manuscriptTitle":"Deciphering most productive cropping systems for sustainable farming in middle Gangetic plains of Indian subcontinent","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-11 06:04:27","doi":"10.21203/rs.3.rs-6170120/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b793a299-62e3-49a4-a24e-bcc3d154ef4b","owner":[],"postedDate":"March 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-11T06:04:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-11 06:04:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6170120","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6170120","identity":"rs-6170120","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}