The conventional tillage based rice-wheat system (RWS) in Indo-genetic plains (IGP) of South Asia is facing diverse challenges like increase in production cost and erratic climatic events. This results in stagnated crop productivity and declined farm profitability with increased emission of greenhouse gases. Therefore, 3-year multi-location farmer’s participatory research trial was conducted to assess the impact of crop establishment and residue management techniques on crop productivity, economic profitability and environmental footprints in RWS. The aim of this study was to analyze the effect of combinations of improved agronomic technologies compared to farmer’s practices (FP) on crop productivity, profitability, resource use efficiency and environmental footprints. The experiment had six scenarios that is, S1-Farmer’s practice; Conventional tillage (CT) without residue; S2-CT with residue, S3- Reduced tillage (RT) with residue + Recommended dose of fertilizer (RDF); S4-RT/zero tillage (ZT) with residue + RDF, S5-ZT with residue + RDF + green seeker + tensiometer + information & communication technology + crop insurance and S6- S5 + site specific nutrient management. Climate smart agriculture practices (CSAPs; mean of S4, S5 and S6) increase system productivity and farm profitability by 10.5% and 29.4% (on 3 yrs’ mean basis), whereas, improved farmers practices (mean of S2 and S3) resulted in only 3.2% and 5.3% increments compared to farmer’s practice (S1), respectively. On an average, CSAPs saved 39.3% of irrigation water and enhanced the irrigation and total water productivity by 53.9% and 18.4% than FP, respectively. In all the 3-years, CSAPs with high adaptive measures enhanced the energy-use-efficiency (EUE) and energy productivity (EP) by 43%–54% and 44%–61%, respectively than FP. In our study, global warming potential (GWP), GHG emission due to consumption energy and greenhouse gas intensity were recorded lower by 43%, 56% and 59% in Climate Smart Agriculture (CSA) with high adaptive measures than farmers practices (3652.7 kg CO₂ eq. ha⁻¹ yr⁻¹, 722.2 kg CO₂ eq. ha⁻¹ yr⁻¹ and 718.7 Mg kg⁻¹ CO₂ eq. ha⁻¹ yr⁻¹). The findings of the present study revealed that CSA with adaption of innovative measures (S6) improved 3-year mean system productivity by 10.5%, profitability by 29.4%, water productivity and energy productivity by 18.3% and 48.9%, respectively than FP. Thus, the results of our 3-year farmer’s participatory study suggest that in a RW system, climate smart agriculture practices have better adaptive capacity and could be a feasible option for attaining higher yields, farm profitability, energy-use efficiency and water productivity with sustained/improved environmental quality in smallholder production systems of Eastern IGP of India and other similar agro-ecologies of South Asia. Finally, the adoption of these CSAPs should be promoted in the RW rotation of IGP to ensure food security, restoration of soil health and to mitigate climate change, the key sustainable development goals (SDGs).

Intensive tillage-based production systems coupled with inefficient fertilizer management practices have led to increased production costs, sub-optimal productivity, and significant environmental externalities. Conservation agriculture (CA) is being increasingly advocated as a management strategy to overcome these issues but precision nutrient management under the CA-based maize-wheat system is rarely studied. Two year’s (2014–2015 and 2015–2016) research was conducted at the research farm of BISA, Pusa, Bihar, India to develop precision nutrient management practices for CA-based management in the maize-wheat system. Seven treatment combinations involving (i) tillage (conventional tillage; CT & permanent beds; PB) and (ii) nutrient management rates, application methods (farmers’ fertilizer practices; FFP, state recommended dose of fertilizer; SR and precision nutrient management using Nutrient Expert tool; NE and GreenSeeker; (GS), applied using two methods; broadcasting (B) and drilling (D)) were investigated for multiple parameters. The results showed that NE, NE+GS, and SR-based nutrient management tactics with drilling improved crop yields, nutrient-use efficiency (NUE), and economic profitability relative to NE-broadcasting, SR broadcasting, and FFP broadcasting methods. Maize-wheat system productivity and net returns under NE+GS-drilling on PB were significantly higher by 31.2%, 49.7% compared to FFP-broadcasting method, respectively. Total global warming potential (GWP) was lower in the PB-based maize-wheat system coupled with precision nutrient management compared to CT-based maize-wheat system with FFP. Higher (15.2%) carbon sustainability index (CSI) was recorded with NE-drilling compared to FFP-broadcasting method. Results suggests that PB-based maize-wheat system together with precision nutrient management approaches (NE+GS+drilling) can significantly increase crop yields, NUE, and profitability while reducing the emission of greenhouse gases (GHGs) from maize-wheat systems in eastern Indo Gangetic Plains (IGP).

Zero tillage is an important pathway to sustainable intensification and low-emission agriculture. However, quantifying the extent of zero tillage adoption at the field scale has been challenging, especially in smallholder systems where field sizes are small and there is limited ground data on zero tillage adoption. Remote sensing offers the ability to map tillage practices at large spatio-temporal scales, yet to date no studies have used satellite data to map zero tillage adoption in smallholder agricultural systems. In this study, we use Sentinel-2 satellite data, random forest classifiers, and Google Earth Engine to map tillage practices across India’s main grain producing region, the Indo-Gangetic Plains. We find that tillage practices can be classified with moderate accuracy (an overall accuracy of 75%), particularly in regions with relatively large field sizes and homogenous crop management practices. We find that models that use satellite data from only the first half of the growing season perform as well as models that use data throughout the growing season, allowing for the creation of within-season tillage maps. Finally, we find that our model can generalize well through time in the western IGP, with reductions in accuracy of only 5–10%. Our results highlight the ability of Sentinel-2 satellite data to map tillage practices at scale, even in smallholder systems where field sizes are small and cropping practices are heterogeneous.