Designing resource efficient integrated crop management modules for direct seeded rice-zero till wheat rotation of north western India: Impacts on system productivity, energy-nutrient-carbon dynamics

ABSTRACT Eight integrated crop management (ICM) practices were evaluated for six years consecutively, which are ICM1&2: ‘business-as-usual’ (conventional transplanted rice fb flatbed wheat), ICM3&4: conventional direct seeded rice (DSR) fb furrow irrigated raised-bed wheat without residues, ICM5&6: conservation agriculture (CA)-based zero-tilled (ZT) DSR fb ZT wheat with the wheat and rice residues and ICM7&8: CA-based ZTDSR fb ZT wheat with the wheat, mungbean and rice residues. ICM7-8 produced 9.6–16.4% and 9.4–9.9% greater system rice equivalent yield (REY) than the ICM1-4 and ICM5-6, respectively. Residue-retained CA-based ICM5-8 had 23.2% and 58.5% greater N and P balance, respectively, than the residue removed (ICM1-4); subsequently, negative K balance (–53 to –115.5 kg ha−1) was recorded in ICM1-4. ICM5-8 consumed ~60-78% of total energy and produced the highest energy output (E o ) in rice (11.5–12.6%)/wheat (7.3–13%) than ICM1-4. In contrast, ICM1-4 had a greater energy use efficiency (EUE) compared to ICM5-8 due to lesser energy input (E I ) through indirect renewable sources. At a soil depth of 0.0–0.45 m, the ICM5-8 contributed 7.9% and 20.2% greater active and passive OC pools over the ICM1-4. Thus, CA-based ICM in rice-wheat rotation (RWR) could be a possible substitute for the positive nutrient balance, system yields and energy and carbon dynamics.


Introduction
In South Asian agro-ecologies, rice-wheat rotation (RWR) is the major production system and significant contributor to the daily dietary needs, digestible energy and protein intake (Timsina and Connor 2001;Ladha et al. 2003). In India, RWR is important for the livelihood security and has a major share to the national food basket . It is more energy-intensive and nutrientexhaustive; however, efficiencies have not been intensified over the time . Indeed, energy and nutrient dynamics are crucial for achieving the potential yield in crop production. Energy use in agriculture accounted 5% of the global energy usage (Li et al. 2018), owing to the manpower shortages and global warming and to meet the demand of food commodities (Yadav et al. 2020). Being an important production input, energy is essential for harnessing the maximum economic benefits, sustainable consumption and production of food and agriculture (Babu et al. 2020). Minimal dependence on non-renewable sources seeks out higher energy use efficiency (E U E) and long-term sustainability of RWR (Soni et al. 2018). Parihar et al. (2017) reported that energy sources such as crop residues (retained/incorporated) were not considered for energy auditing, although it harnesses a larger portion of clean energy contributed from various renewable and non-renewable sources.
Imbalanced use of available internal/external nutrient sources coupled with in situ residue burning in RWR further aggravates the soil nutrient mining and multi-nutrient deficiencies that eventually affect overall soil health (Ladha et al. 2003;Pooniya et al. 2021). Continuous depletion of native potassium (K) reserves not only minimizes crops yield but also escalates the production cost (Madar et al. 2020). Globally, ~30% of cultivated soils suffer from the phosphorus (P) stress and the world P reserves are being depleted, thus making the cost of P and K very high. Therefore, recycling crop residues is compelling for the strategic nutrient management (Pooniya et al. 2020). Annually, India produces ~686 million tonnes gross residue biomass (GOI 2016) wherein the surplus residues can possibly be recycled back to the field after being used as feed and fuel (Parihar et al. 2017). Residue recycling would refrain stubble burning, which impairs the air quality in northern India, besides posing health hazards (Abdurrahman et al. 2020).
Recently, the Food and Agriculture Organization (FAO) has recognized significance of the integrated crop management (ICM) and its relevance in the contemporary agriculture (FAO 2013). The ICM approaches could minimize production costs (Hawes et al. 2018) and significantly enhance the farm income with an additional yield gain ranging from 20 to 30% over the farmer's practices (Suhas et al. 2017). In Nepal, Regmi and Ladha (2006) reported the 6.4% and 17 to 19% higher rice yield and nitrogen agronomic efficiency (AE N ) with the adoption of ICM practices. The superiority of ICM with respect to economic yields had also been reported in China (Wang et al. 2017). The ICM is a holistic, regional-specific and alternative system of crop production that incorporates reasonable and best agronomic practices to enhance and conserve the natural resources while producing quality food on a sustainable foundation (Kumar and Shivay 2008).
Thus, ICM modules coupled with variants of conservation agriculture (CA), such as direct seeded rice (DSR) and ZT wheat facilitate the in situ crops residue management in the existing RWR. It will largely contribute to the different soil carbon pools and improve the soil properties (Pooniya et al. 2012) besides reducing the energy footprint due to less fuel consumption than the CT practices . The relative performance of the ICM modules under long-term field conditions has not yet been evaluated. Thus, the present study evaluated eight ICM modules with the following objectives: (i) CA-based ICM practices would improve the system yields and conserve soil carbon over the CT-based practices and (ii) to assess the effect of ICM practices on energy-nutrient dynamics of rice-wheat rotation.

Details of the experimental field
Six-year long-term field experiment on integrated crop management (ICM) was established in 2015 and continued till 2021 at the ICAR-Indian Agricultural Research Institute (28°35′ N latitude, 77°12′ E longitude, 229 m MSL), New Delhi, India. In 2014 (before initiation of the study), winter wheat was grown to ensure a uniform fertility gradient across the blocks. In April 2015, initial soil samples (0.0 to 0.30 m depth) were taken and processed for the chemical analysis. The experimental soil had a pH of 7.9 (1:2.5 soil and water ratio ;Piper 1950), soil organic C of 4.8 g kg −1 (Walkley and Black 1934), KMnO 4 -oxidizable N of 169.5 kg ha −1 (Subbiah and Asija 1956), NaHCO 3 -extractable P of 11.5 kg ha −1 (Olsen et al. 1954) and NH 4 OAc-extractable K of 275.3 kg ha −1 (Hanway and Heidel 1952).

Description of ICM modules
Eight ICM modules, consisting of four conventional tillage (CT)-based (ICM 1-4 ) and four conservation agriculture (CA)-based (ICM 5-8 ), were constructed with a dimension of 50 m 2 (12.5 m × 4 m) and replicated thrice in a randomized block design (Table 1). Under CT-based rice and wheat modules (ICM 1-4 ), entire residues were removed, while in ICM 5-8 modules, in situ wheat (~3 Mg ha −1 on dry weight basis) and rice residues (~5 Mg ha −1 on dry weight basis) were retained during each season (footnote of Table 1). After wheat harvest, during summer fallow (April-June) of each year, mungbean (Vigna radiata L.) crop was grown in ICM 7-8 modules. The mungbean foliage was knocked down at the flowering stage (45-50 d) using a non-selective zero-persistence herbicide (paraquat at 0.5 kg ha −1 ), and in situ residue of about ~2.5-3 Mg ha −1 (on dry weight basis) was retained.
In CT-based rice modules (ICM 1-4 ), field preparation was performed by deep ploughing using the disc plough, cultivator/rotavator twice and then leveled every year. An extra operation of puddling was performed in ICM1&2, using tractor drawn puddler in the standing water. The CT-based wheat (ICM 1-4 ) received sequential tillage operations with the disc harrow, cultivator, followed by the rotavator. In ICM 3-4 , raised beds of 0.70 m bed width (bed top 0.40 m and furrow 0.30 m) were formed during each cropping cycle using the tractor-mounted bed planter. In the CA-based ICM 5-8 modules of both rice and wheat, tillage was restricted to the crop row-zone only to open a narrow slit for placing the seeds/fertilizers simultaneously.

Cultural and sowing operations in different ICM modules
In ICM 1&2 , 25-d old seedlings of a rice genotype 'Pusa Basmati 1509' were manually transplanted (2-3 seedlings hill −1 ) during the first fortnight of July at 0.20 m × 0.10 m rectangularity, whereas in ICM 3-8 , ~25-30 kg rice seeds ha −1 at a row spacing of 0.20 m were drilled. In order to maintain the uniformity, nursery raising (ICM 1-2 ) and direct seeding (ICM 3-8 ) was accomplished on the same day. Every year, a popular wheat variety 'HD 2967' was sown in the first week of November at a row spacing of 0.20 m using a seed rate of 100 kg ha −1 with the seedcum fertilizer drill (ICM 1-2 ), bed planter (ICM 3-4 ) and zero-till seed drill (ICM 5-8 ). In rice, ICM1&2 were kept ponded with irrigation water up to grain filling, while, in ICM 3-8 , irrigations were applied at critical growth stages or when no rains occurred for 7-8 consecutive days, wheat received 5-7 irrigations per annum. Nitrogen (N), phosphorus (P) and potassium (K) fertilizers were applied as per the modules described in the footnote of Table 1, whereas mungbean was sown on residual soil fertility without fertilizer applications. At sowing/puddling, recommended doses of P and K using diammonium phosphate (DAP) and muriate of potash (MOP), respectively, along with the 1 / 3 rd N through urea, were applied. The remaining N was top-dressed in 2 equal splits after the first irrigation and panicle initiation (PI) stages of rice and after first irrigation and maximum tillering stages of wheat. In ICM 2,4,6,8 modules, seeds/roots of rice and wheat were treated with the NPK liquid biofertilizer (diluted 250 ml formulation in 2.5 liters of water ha −1 ). An arbuscular mycorrhiza at 12 kg ha −1 was applied in the modules receiving ¾ fertilizers. NPK liquid biofertilizer contained the microbial consortia of N-fixer-(Azotobacter chroococcum), P-(Pseudomonas) and K-(Bacillus decolorationis) solubilizing bacteria that could supplement 15-20 kg N, 8-9 kg P and 10-15 kg K ha −1 . Because of aerobic conditions, weeds are the major constraint especially in DSR and reduce the rice yield severely. Hence, different pre-and post-emergence herbicides and their combinations were included in the modules (footnote of Table 1). For management of insect pests and the diseases, the needbased integrated insect-pest and disease management practices were followed uniformly across the ICM modules.

Rice equivalent yields
Every year, during October (rice) and April (wheat), the crops were harvested from the net area (6 m × 3 m, 18 m 2 ) leaving the border rows (0.4 m from all the corners of each plot). Rest of the plots were harvested using the combine harvester. The harvested samples were sun-dried, and biological yields (grain + straw) were recorded. Straw yield was calculated by subtracting the grain yield from the total biomass. Furthermore, system yield in terms of the energy was computed by converting the yield of wheat into rice equivalent considering the energy coefficient (E c ) as described by Yadav et al. 2020), where Yr is the rice grain yield (Mg ha −1 ), Yw is the wheat grain yield (Mg ha −1 ), Wec is the E c of wheat grain and Rec is the E c of rice grain.

Nutrient content, uptake and balance
Each year, plant shoots were sampled (5 samples from each module) by cutting from the roots at the crown at the harvest stage of both rice and wheat crops. Sampled plants were oven dried (60 ± 2°C for 48 h), finely ground and passed through a 40-mesh sieve in a Macro Wiley mill, for nutrient analysis (Pooniya and Shivay 2013). The total N content (grain/straw) was analyzed using the modified Kjeldhal method, and P content through the vanadomolybdophosphoric acid yellow color method, whereas a flame photometer was used for the estimation of K as described by Prasad et al. (2006). Furthermore, the respective nutrient uptake in grain and straw was calculated by multiplying the grain and straw yields with the corresponding nutrient content. The soil nutrient (N, P and K) balances in the respective modules were computed by summing the values of nutrients returned/added through crops residues and applied by external inorganic fertilizers and by subtracting the nutrient removal by the grain and straw (Pooniya et al. 2012). Nutrients input through crops residues was calculated considering the standard values as suggested by Timsina (2018). These values correspond to the nutrient contents of crop residues in the South and South East Asia. However, nutrient uptake in individual crops grain and straw was calculated as per the actual nutrient content. Similarly, systems soil nutrient balance was calculated by adding the balance of both the rice and wheat crops. However, the nutrient mobilization through NPK biofertilizers and AM fungi was not taken into consideration.

Energy auditing
The amount of energy consumed in each treatment for DSR and ZT wheat was first systematically catalogued. The energy sources included human labour, fuel, machinery, seed, residue, irrigation, chemical fertilizers, the plant protection chemicals (herbicide, insecticide and fungicide) etc. For calculating the energy input (E I ) and output (E o ) of the respective modules, the standard conversion energy coefficients (E c ) as suggested by Mittal and Dhawan (1988) and Parihar et al. (2018) were used and are described in Table S1. All the energy input coefficients were summed up to get the total input energy. Accordingly, the various energy indices [energy productivity (E P ), energy use efficiency (E U E), specific energy (S e ) and net energy (N e )] were calculated using the following formula (Soni et al. 2018;Jat et al. 2019;Babu et al. 2020): where I 1 , I 2 . . . Ii are involved in various energy inputs (MJ ha −1 ), where S y is the system biomass yields (grain + straw) in Mg ha −1 and energy coefficient is in Energy productivity ðE p Þ¼S p ðkg ha À 1 Þ�E I ðMJ ha À 1 Þ: Similarly, systems E I , E o and N e were computed by summing the values of the respective crops.

Soil carbon fractions
Triplicate soil samples were collected from each module (0.0-0.15, 0.15-0.30 and 0.30-0.45 m soil layers) using an auger of 0.05 m diameter after the harvest of the sixth rice crop (October 2020). The method described by Chan et al. (2001) was used to classify the total OC into four distinct fractions using the solution containing 5, 10 and 20 ml of concentrated H 2 SO 4 (36 N) and K 2 Cr 2 O 7 , which resulted in three acid-aqueous solution ratios (0.5:1, 1:1 and 2:1) corresponding to 12, 18 and 24 N H 2 SO 4 , respectively. The concentration of C was thus determined through the separation of OC into the following four fractions of decreasing lability: (

Statistical analysis
The GLM procedure of the SAS 9.4 was used for the statistical analysis of all the data obtained from different ICM modules to analyze the variance (ANOVA) under the randomized block design (Gomez and Gomez 1984). Tukey's honest significant difference test was employed to compare the mean effect of the treatments at p = 0.05. The grain/straw yields were subjected to the pooled analysis.

Weather analysis
During the six years of the study, a sizeable fluctuation in the rainfall distribution pattern was observed. In 2016-17, ~1230 mm annual rainfall occurred, whereas ~600-900 mm was received during rest of the years, with the lowest being recorded in 2017-18. In the northwestern Indian ecologies, most rains are received from the south-west monsoon (rice season); however, the western disturbances are responsible for the light and scanty rains during winters, which favours the wheat growth. In winters of 2018-19 and 2019-20, it rained ~142 mm and ~158 mm, respectively. The warmest and the coldest months were May-June and December-January of the different study years, respectively (Source: Agromet. Observatory, Agri. Physics, IARI, New Delhi).

Six-year pooled rice and wheat yields
The ICM 8 modules recorded the maximum mean rice grain yield, being similar to ICM 1-2 and ICM 5-7 . However, ICM 7,8,1 produced similar mean rice straw yield, but significant to other ICM modules. The ICM 7-8 resulted in 12-18.5% and 8.6-17% higher grain and straw yields compared to ICM 2-4 . Similarly, the ICM 7 had the highest mean wheat grain yields, significantly greater than ICM 1-2,4 . However, ICM 5-8 produced the similar pooled wheat straw yield, which was 7.5-11% greater than the ICM 1-4 modules ( Table 2). Multivariate ANOVA was computed considering year as the independent factor with the different ICMs as dependent. In rice, ICM 2-5,7 differ significantly due to years, however, ICM 1,5,7-8 in wheat (Table S2 and Table 3).

Six-year trend of system rice equivalents
Based on the energy, different ICM modules had a significant (p < 0.05) impact on the system rice equivalents (REY). Across the years, the system yield ranged between 7.3 and 10.2 Mg ha −1 . ICM 7 produced the highest yield in 2015-16, 2016-17 and 2019-20, while it was in ICM 8 during 2017-18 and 2018-19. Furthermore, in 2020-21, ICM 7-8 resulted in the highest system REY, which was similar to the ICM 1, but significantly greater than the ICM 2-6 . On average, the ICM 7 and ICM 8 produced 8.4-15.7% and 9.4-16.7%, greater system REY than ICM 1-6 , respectively. In the first 4 years, residueretained CA-based modules (ICM 5-8 ) had statistically similar yields; however, in the subsequent 2 years, ICM 7-8 showed superiority over the ICM 5-6 . In fact, in 2 nd , 3 rd and 4 th years, CT-based module (ICM 1 ) is at par to the CA-based ICM 5-8 modules (Table 3). On the basis of average, the order of system REY was ICM 7-8 > ICM 5-6 > ICM 1-2 and ICM 3-4 .

Nutrient balance of DSR (six-year mean)
The ICM 7 module had the highest N inputs (inorganic fertilizers + crop residues), while the least was under the ICM 2-4 (Figure 1(a)). Subsequently, ICM 7 led to the highest total N uptake (grain + straw), which was significantly greater than the ICM 1-6 , but similar to the ICM 8 (Figure 1(b)). Modules ICM 7-8 had 6-22.5% greater N acquisition over the ICM 1-6 . Indeed, the N balance was the highest under ICM 5 (Figure 2(a)), which was similar to the ICM 7 , but significantly greater than the ICM 1-4,8 by 16.3-51.6%. Similarly, the P inputs were the highest with the ICM 7 , but its uptake was substantially higher in the ICM 8 , which was 7-33% greater than the ICM 1-7 . In contrast, the ICM 7 had the highest P balance, which was 13-69% greater than the ICM 1-6,8 . Furthermore, ICM 7 had the highest K inputs, while the uptake was highest under the ICM 7,8 , which was 4-40% greater than the ICM 1-6 . CT-based residueremoved modules (ICM 1-4 ) had a negative K balance (-4.3 to -46.3 kg ha −1 ), while ICM 5-8 resulted in a positive K balance, and the highest was in the ICM 7 (Figure 2(a)).

Nutrient balance of ZT wheat (six-year mean)
The highest N input was received by the ICM 7 (Figure 1(a)); subsequently, the uptake and the balances were also higher with the ICM 7 , which was significantly greater than the ICM 1-6,8 . P uptake was the highest under ICM 7 , but it was similar to the ICM 8 and significantly greater (8-12.5%) than the ICM 1-6 ( Figure 1(b)). Similarly, the ICM 7 had a greater P balance (17.5-69%) than the ICM 1-6,8 (Figure 2(b)). The ICM 7 had a greater K uptake (3-20%) than the ICM 1-6, 8 . The ICM 1-4 had a negative K balance (-48.6 to -69.1 kg ha −1 ), while positive balance was registered with the ICM 5-8 , and the highest K balance (118.9 kg ha −1 ) was with ICM 7 (Figure 2(b)).

Energy dynamics of DSR (six-year mean)
The ICM 7 had the highest energy input (E I ) (72584 MJ ha −1 ), while the least was recorded under the ICM 4 (13268 MJ ha −1 ). However, ICM 8 produced the highest energy output (E o ), which was significantly greater than the ICM 1-7 to the tune of 5.6-21% (Figure 3(a)). In contrast, the highest net energy produced in the ICM 1 was similar to that produced in the ICM 2 , but significantly greater (14-40.8%) than the ICM 3-8 . Furthermore, energy productivity (E p ) was the highest with the ICM 2 , wherein it was  Figure 1. Six-year mean of N, P and K (kg ha −1 ) added through inorganic fertilizers and crop residues (rice/wheat/mungbean) (a) and nutrient uptake (kg ha −1 ) (grain + straw) (b) under different ICM modules. The vertical bars indicate LSD at p = 0.05. significantly greater (9-80%) than the ICM 1,3-8 (Table 4). Nevertheless, ICM 7 produced the highest specific energy (S e ), being 12-80% greater than the ICM 1-6,8 . The highest E U E was in the ICM 2 , which was 6.4-80% more efficient than the ICM 1,3-8 (Table 4).

Energy dynamics of ZT wheat (six-year mean)
The ICM module had differential E I ranging between 13596 and 72974 MJ ha −1 and was the highest in ICM 7 (Figure 3(a)). But E o was the highest with the ICM 8 , which was similar to the ICM 7 , but significantly greater (7-14%) than the ICM 1-6 . The ICM 3 produced the highest N e although the trend was similar to the ICM 1,2,4 , but significantly greater than the ICM 5-8 to the tune of 11-21%. However, the highest E p was recorded under the ICM 4 , which was 14-78% greater than the ICM 1-3,5-8 (Table 4). The highest S e was with the ICM 7 , which was similar to the ICM 8 , but significantly greater (32-77%) than the ICM 1-6 . Furthermore, the highest EUE was with the ICM 4 and was 15-79% higher efficient than the ICM 1-3,5-8 .  ICM1  ICM2  ICM3  ICM4  ICM5  ICM6  ICM7  ICM8  NPK (kg ha - ICM1  ICM2  ICM3  ICM4  ICM5  ICM6  ICM7  ICM8  In RWR, the different CT-and CA-based modules showed a similar trend for energy indices (Figure 3 (b)). Furthermore, CA-based ICM 5-8 had the greater (63.7-81.6%) indirect renewable E I (crops seed/ residue), but ICM 1-4 consumed a greater (84.5-88.4%) indirect non-renewable energy (Figure 4).

Discussion
The challenges of soil nutrient mining and higher energy consumption in conventional rice-wheat rotation (RWR) rambled the search for resource-efficient alternatives. Hence, integrated crop management (ICMs) along with CA principles greatly reduces energy footprints (Parihar et al. 2018;  ICM1  ICM2  ICM3  ICM4  ICM5  ICM6  ICM7  ICM8 MJ ha -1 Energy input (rice) Energy output (rice) Energy input (wheat) Energy output (wheat) Net energy (rice) Net energy (wheat) Kumar et al. 2021), augmenting native soil nutrient reserve through on-farm residue recycling (Madar et al. 2020) and intensified system yields , and permits timely sowing of the succeeding wheat (Ladha et al. 2003;Biswakarma et al. 2021). Indeed, recycled residues not only sustain the resources for long-term production (Cerd`a et al. 2017) but also change regional growers' perception towards refrain biomass burning in the western IGPs. Averaged across years, ICM 7-8 had increased the REY by 1.25 Mg ha −1 , but ICM 5-6 by 0.32 Mg ha −1 only than ICM 1-4 . Our results reinforce prior findings, as CA practices had a greater cereals yield over the CT in the South Asian ecologies . Residue retention under double (ICM 5-6 )/triple ZT (ICM 7-8 ) might bring a desirable change in the micro-environment by improving soil physico-chemical and biological properties, thereby greater nutrient acquisition system yields (Jat et al. 2019;Biswakarma et al. 2021). Our study confirmed the mining of native potassium reserve under CTbased ICM 1-4 (−89.2 kg K ha −1 ). Contrarily, a positive K balance was maintained in CA-based ICM 5-8 (+241.3 kg K ha −1 ) along with N and P balance, as crop residues are expected to enhanced nutrient  Figure 4. Percent renewable and non-renewable energy inputs in DSR-ZT wheat rotation (six years av.). Direct non-renewable = diesel; direct renewable = human labour; indirect non-renewable = fertilizer's (including biofertilizers), herbicide, fungicide and insecticide; indirect renewable = crop seeds and residues.   recycling and augment the soil NPK pools. Furthermore, application of NPK consortia coupled with the AM fungi might have mineralized and solubilized nutrients by producing organic acids, mucilage and capsular polysaccharides (Madar et al. 2020) and supplemented the chemical fertilizers by 20-25%. The current energy issues in agriculture hinder in achieving Sustainable Development Goals (SDG-12), i.e. responsible consumption and production (Soni et al. 2018;Babu et al. 2020). Hence, identifying promising alternative envisaged a great significance in harnessing the efficient energy use (Parihar et al. 2017(Parihar et al. , 2018. Different ICM modules had a significant impact on energy indices (energy output, net energy, energy productivity, specific energy and EUE). Modules ICM 1-4 had consumed higher direct and indirect non-renewable energy sources due to higher machinery use/ fossil fuel consumption during land preparation that forms a major part of energy use under CT practices . In contrast, CA-based ICM 5-8 modules had consumed more indirect renewable energy sources, which would be owing to higher energy equivalence of retained residues (~3 Mg ha −1 on dry basis each of wheat/mungbean, ~5 Mg ha −1 of rice). CT-based ICM 1-4 had greater net energy, EUE and energy productivity; of course, this is ascribed to zero recycling of residues (clean cultivation) and statistically similar crops yields. The higher energy accumulation and specific energy under CA practices were also reported by Parihar et al. (2017); Pooniya et al. (2020). The ICM 7-8 gave 19-22% greater returns than the ICM 1-2 , because these modules conferred yield benefits, as reflected in the notion of economic net returns.
Averaged across soil layers, ICM 5-8 contributed 20.2% greater to the passive (less labile + nonlabile) pool compared to ICM 1-4 , indicating that residue retained modules contributed greater to NL-OC and L-OC pool's especially in 0.0-0.30 m soil layers. Residue retention under CA promotes regular supply of fresh organic matter, usually greater than the microbe's capacity to act upon decomposition or further mineralization, thereby enhancing the OC lability in soils (Dey et al. 2018;Mondal et al. 2019). It may, therefore, be interesting to understand the changes in soil OC-fractions in CA-based modules, an improvement in NL-OC/L-OC fractions especially in upper soil layers indicating effective C sequestration. In ICM 5-8 , greater labile and non-labile OC-fractions are indicator for greater C-sequestration and nutrients availability. However, VL-OC and LL-OC fractions are comparable in both CA-and CT-based modules. Thus, this study on OC-fractions, energy and nutrient dynamics in dominant RWR assumes great significance in identifying promising resource-effective alternative ICM modules, which have a greater dependency on renewable energy sources besides sustaining soil fertility and crops yields.

Conclusions
Triple ZT residue-retained (ICM 7-8 ) modules could be most appropriate for the RWR, as they do not just built up the native nutrients' balance but also enhanced the energy dynamics, REY and the OCfractions. The six-year mean distinctly indicated the supremacy of the ICM 7-8 , which produced 13% and 9.7% greater REY in terms of the energy than the ICM 1-4 and ICM 1-6 , respectively. ICM 5-8 had 23.2% and 58.5% greater N and P balances, respectively, than the ICM 1-4 . Furthermore, modules (ICM 1-4 ) exhibited a negative K balance (-53 to -115.5 kg ha −1 ), showing unsustainability of these practices. The ICM 7-8 had the highest E o (11.5-12.6% rice and 7.3-13% wheat) than the ICM 1-6 although ICM 5-8 (~8-11 Mg ha −1 yr −1 residue added) consumed ~60-78% of the total energy. Indeed, residue removal (ICM 1-4 ) had greater E U E than the residue retained ICM 5-8 ), owing to less energy consumption. The ICM 5-8 modules contributed a 20.5% (0.0-0.15 m) and 11.8% (0.15-0.30 m) greater active OC pool as compared to the ICM 1-4 , indicating an improvement in the OC status of the ICM modules. Also, the ICM 5-8 added a 20.2% (0.0-0.45 m) greater passive C pool over the ICM 1-4 and made relatively the stable organic mineral complexes, which, thereby, would be slowly decomposed for the long-run benefits. Hence, ICM 7-8 (triple ZT) or ICM 5-6 (double ZT) could be recommended for enhancing the nutrient and energy dynamics, OC-fractions besides environmental sustainability in the north-western India and other adjoining ecologies.