INTRODUCTION
The RWCS, spread over 13.5 m ha in the IGP of India, Bangladesh, Nepal and Pakistan (FAOSTAT, 2010), is fundamental to the employment, income, food security and livelihood for millions, providing staple grains for nearly 42% of the total population of 1.3 billion in South Asia (Jat et al., Reference Jat, Singh, Rai, Chhokar, Sharma and Gupta2005). In India, this cropping system occupies 10.5 m ha and contributes about 40% of the country's total food grain basket (Saharawat et al., Reference Saharawat, Singh, Malik, Ladha, Gathala, Jat and Kumar2010). However, the productivity and sustainability of the system are threatened mainly due to the increasing scarcity of water and labour (Erenstein, Reference Erenstein2011; Gathala et al., Reference Gathala, Ladha, Kumar, Saharawat, Kumar, Sharma, Sharma and Pathak2011). The problem is further intensified by the planners and policymakers favouring highly subsidised power and irrigation water, leading to overuse of these resources (Naresh et al., Reference Naresh, Singh and Kumar2013) and hence drastic fall in ground water levels. Moreover, the degrading soil health in terms of the soil physical environment is further accentuating the problem.
The RWCS with conventional practices has led to continued exploitation of the natural resources (Bhatt and Kukal, Reference Bhatt and Kukal2014; Bhatt and Kukal, Reference Bhatt and Kukal2015; Hira, Reference Hira2004) in the region which has further put extra pressure on energy requirements (Hira, Reference Hira2009). The per capita availability of water in many Asian countries has declined by 40–60% which is further expected to decline further by 15–54% in the coming 35 years (Gleick, Reference Gleick1993). By 2025, 15–20 million ha of rice land is expected to suffer due to some degree of water scarcity (Tuong and Bouman, Reference Tuong, Bouman, Kijne, Barker and Molden2003). This scarcity is expected to be more severe in populous countries like India.
Conventionally, rice is established in puddle (PR) soils with heavy water and labour inputs (Dawe, Reference Dawe2005), while negative effects of puddling through structural degradation on upland crops are of concern (Aggarwal et al., Reference Aggarwal, Sidhu, Sekhon, Sandhu and Sur1995; Kukal and Aggarwal, Reference Kukal and Aggarwal2003a). Repeated puddling of coarse and medium textured soils has led to sub-surface compaction (Kukal and Aggarwal, Reference Kukal and Aggarwal2003a; Sur et al., Reference Sur, Prihar and Jalota1981) which is proving to be detrimental for upland crops like wheat due to aeration stress (Kukal and Aggarwal, Reference Kukal and Aggarwal2003b). The scarcity of labour is becoming a global phenomenon and could threaten the sustainability of conventional RWCS in near future (Kumar and Ladha, Reference Kumar and Ladha2011; Rashid et al., Reference Rashid, Alam, Khan and Ladha2009). Thus, conventional puddle transplanted system of rice cultivation is water-, capital- and energy-intensive. On the other hand, wheat is conventionally grown in upland well-drained soils after complete burning of rice residues (120 million tons) and repeated tillage operations lead to environmental pollution besides depriving the soils of a huge amount of nutrients and organic carbon.
Various RCTs viz. direct drilling of wheat seeds with and without crop residues, DSR, mechanical transplanting of rice in conventional and zero till conditions, etc. are being advocated for increased productivity, sustainability and profitability of RWCS as these primarily focus on conservation tillage and recycling of crop residues (Bhatt and Khera, Reference Bhatt and Khera2006; Hobbs et al., Reference Hobbs, Sayre and Gupta2008; Singh et al., Reference Singh, Humphreys, Eberbach, Katupitiya, Singh and Kukal2011). Isolated studies (Rejesus et al., Reference Rejesus, Palis, Rodriguez, Lampayan and Bouman2011) involving individual crops have indicated improved water productivities, which are seldom based on systematic measurements of water balance components of crops grown with these RCTs (Humphreys et al., Reference Humphreys, Kukal, Christen, Hira, Singh, Yadav and Sharma2010; Kukal et al., Reference Kukal, Singh, Jat and Sidhu2014). The magnitude of the benefits of RCTs tends to be site-and situation-specific and cannot be generalised across the farming systems in different agro-climatic regions (Humphreys et al., Reference Humphreys, Kukal, Christen, Hira, Singh, Yadav and Sharma2010; Yadav et al., Reference Yadav, Gill, Humphreys, Kukal and Walia2011; Yadav et al., Reference Yadav, Evangelista, Faronilo, Humphreys, Henry and Fernandez2014). Moreover, the impact of RCTs with respect to establishment and tillage techniques on land and water productivity of the cropping system as a whole is not well documented in the literature (Devkota et al., Reference Devkota, Lamersb, Manschadic, Devkotad, McDonald and Vlek2015; Jat et al., Reference Jat, Sapkota, Singh, Jat, Kumar and Gupta2014). The use of these RCTs in one crop may affect the performance of other crop in the cropping system and/or negate the impacts in the cropping system as observed in the individual crop. The present study was thus conducted to assess the impact of establishment techniques coupled with conservation tillage in wheat and rice on land and WPI of wheat–rice system in NW IGP of India.
MATERIAL AND METHODS
Site description
The field experiments were carried out at the research farm (30°54′N, 75°98′E, and 247 m above sea level) of Punjab Agricultural University, Ludhiana, India, during 2012–14. The experimental soil was sandy loam (sand 65–68%, clay11–3%), neutral to slightly alkaline, non-saline and medium in soil organic carbon (0.44%) in the surface layer (Table 1). The soil had sub-surface compact layer (bulk density of 1.74 Mg m−3 at 15–30 cm). The available nutrients were in the medium range while moisture content (%, g g−1) on an average decreased to 71.5% from field capacity to permanent wilting point. The depth to the ground water at the site was around 24 m and the quality of water was good for all crops (Table 2). The experimental site was under puddle transplanted rice for the last 20 years except that the field was under direct dry-seeded rice sown under tilled conditions during the immediate previous year (2012). The climate is subtropical with hot and dry summers (March–June), wet monsoon season (late June to mid-September) and a cool dry winter (October–February). The long-term average annual rainfall is 734 mm, 85% of which occurs during a short period of July–September.
Table 1. Basic physico-chemical properties of the studied site.
Table 2. Quality of irrigation water used at the experimental site.
Treatments and experimental design
Twelve combinations of different tillage and establishment methods were tested in the rice–wheat cropping sequence (Table 3). The treatments consisted of zero- (direct-drilling of wheat in standing residues of the previous rice crop, ZTW) and conventional-tillage (disked twice followed by two passes of tractor-drawn cultivator and one planking, CTW) for wheat in main plots (13.8 m × 25.1 m) with three replications in randomised block design. In the following rice crop, the main plots were split into two subplots for differential rice establishment viz. DSR and MTR. These subplots were further split into three sub-sub plots of 49.7 m2 (13.8 m × 3.6 m) for differential tillage treatments in rice viz. puddle (PR), dry (CTR) and zero-till (ZTR), each plot separated from the other by 1-m wide buffer strips so as to check the movement of water within differentially irrigated plots. The tillage treatments in rice were randomly allocated in subplots of both DSR and MTR (Table 3).
Table 3. Abbreviations and details of tillage, crop establishment and residue management under the experiment.
Crop management
Wheat
The field was laser levelled prior to establishment of the experiment and a pre-sowing irrigation (PSI) was applied. The wheat was directly drilled into standing residues (4.4 t ha−1) of the previous rice crop using Happy Seeder (a zero-till drill machine which cuts the standing rice residues on its way and sows the seeds in a single operation) (Singh et al., Reference Singh, Humphreys, Kukal, Singh, Kaur, Thaman, Prashar, Yadav, Kaur, Dhillon, Smith, Timsina and Gajri2009). The crop was sown at field capacity soil moisture in the first fortnight of November during both the years. For conventional tillage, the plots were disked twice with tractor-drawn disks to chop the stubbles followed by two passes of tractor-drawn cultivator at field capacity moisture content. Thereafter, the soil was planked with a wooden plank to create a fine layer of soil at the surface. The wheat cultivar PBW 621 was sown at a seed rate of 112 kg ha−1 at row spacing of 20 cm. The diammonium phosphate (DAP) and muriate of potash (MOP) was applied @ 138 and 50 kg ha−1, respectively, before cultivation in conventionally tilled plots and placed by the side of the seed while drilling in zero-till plots. The nitrogen was applied as urea in two splits @ 113 kg ha−1 at sowing and 30 days after sowing (DAS). The crop was harvested in the third week of April during both the years.
Rice
The rice crop was established as puddle (PR), dry-till (CTR) and zero-till (ZTR) under both the establishment methods viz. direct-seeded and mechanical transplanting. The plots were puddled after dry pre-puddling tillage as done in case of wheat. The puddling comprised of two passes of hand-driven power tiller in ponded water. For direct seeding of rice in puddle soil, pre-germinated seeds were sown using drum seeder @ 40 kg ha−1 at row spacing of 20 cm. The direct seeding of rice in CTR and ZTR plots was carried out in the same way as done in case of wheat. For mechanical transplanting, the 30-days old seedlings (sown at the same date as in DSR) were transplanted using mechanical transplanter at 30 cm × 17 cm spacing. All the plots were applied with 10 kg ZnSO4 at the time of field preparation. The nitrogen was applied as urea in four splits in DSR (14, 28, 49 and 70 DAS) and three splits in MTR (5, 30 and 51 DAT). To manage iron deficiency, the crop was sprayed thrice at weekly interval with 1% FeSO4 solution at 30 DAS/DAT.
Irrigation management
After a PSI, the first common irrigation was applied to wheat at 28 DAS. Further irrigations were applied on the basis of soil matric potential of -35 kPa at 35 cm depth (S S Kukal, Personal Communication), measured by tensiometres installed in each plot. The individual plots were irrigated as and when the tensiometre indicated soil matric potential of -35 ± 5 kPa. The last irrigation to wheat crop was applied 15–20 days before the crop harvest.
In rice crop, the puddled plots were irrigated till 15 DAT to ensure ponded water conditions and thereafter, these were irrigated on the basis of soil matric potential of -15 kPa at 15–20 cm depth (Kukal et al., Reference Kukal, Hira and Sidhu2005) measured by tensiometres installed in each plot. The individual plots were irrigated as and when the tensiometre indicated soil matric potential of -15 ± 3 kPa. In dry till (CTR) and zero till (ZTR) plots of DSR, the irrigations were applied every alternate day till the establishment of the crop (25–30 DAS) and thereafter, the plots were irrigated on the basis of soil matric potential as mentioned above. In CTR and ZTR plots of mechanical transplanting, the irrigations were applied every alternate day till 12–15 DAT for ensuring the efficacy of the applied herbicides and thereafter, the crop was irrigated on the basis of soil matric potential as mentioned above. The amount of irrigation water applied to each plot was measured using digital flow meter installed at the mouth of each plot.
Weed and insect-pest management
In ZTW wheat plots, the weeds were managed prior to seeding by spraying glyphosate @ 1 l ha−1 while no herbicide was used in CTW plots before seeding. The metsulfuron methyl 20% WG @ 20 g ha−1 and clodinafop 15% WP @ 400 g ha−1 were sprayed at 52 and 53 DAS, respectively in all the treatments. The DSR plots were sprayed with pre-emergence herbicide (pendimethline 30EC @ 2.5 l ha−1) immediately after sowing. The crop was sprayed with post-emergence herbicide (bispyribac sodium 10% SC @ 250 g ha−1) at 23 DAS. The weeds surviving these treatments were removed manually as and when these appeared. In puddle plots of DSR and MTR, the weeds were controlled by applying post-emergence herbicide butachlor @ 150 g ha−1 at 15 DAT. The crop was protected against insect-pests by spraying choloropyriphos @ of 2.5 l ha−1 at 57 DAS in all the treatments. However, monocrotophos @ 50.4 g ha−1 and propiconazole @ 62.5 g ha−1 was used to control insects and diseases in rice season.
Observations
Periodic tiller density (number m−2) was measured in 0.5-m row length at four fixed places in each plot. The crop biomass accumulation was measured every fortnight in 1-m row length at two places in each plot, the sub-samples of which were dried at 60 °C for 72 h and weighed. Periodic leaf area index (LAI) was measured using a Delta-T Sunscan probe. Measurements were made across five rows, with the probe parallel to the rows every time at a fixed location in each plot.
For recording the grain yield, an area of 10 m2 was harvested from the centre of each plot, thrashed manually for rice and by mechanical thrasher for wheat. The moisture content of the grains was recorded using moisture meter and the crop yield was determined at 12% moisture for wheat and 14% for rice. The straw yield of both the crops was adjusted to 0% moisture content. Harvest index was calculated as the ratio of grain yield and total biological yield (grain + straw). The average grain weight was determined as average weight of 1000 fresh grains and expressed at 14 and 12% moisture contents for rice and wheat, respectively. The grains per panicle in wheat were recorded in 10 panicles selected randomly for each plot. The floret fertility percentage in rice was measured in 10 panicles selected randomly from each plot at harvest. The filled and unfilled florets per panicle were counted and fertility percentage calculated as the ratio of filled and total florets from each panicle. The weeds were removed and weighed after sun drying for 3–4 days to record weed biomass.
The irrigation water amounts were measured using digital flow meter (AVFM 5.0) fixed at the inlet point of each plot. The WPI was calculated as the ratio of the recorded grain yield to the total amount of irrigation water, whereas total input water productivity (WPI+R) was calculated as the ratio of grain yield to the total input (irrigation + rainwater).
Weather data
Daily maximum and minimum temperature and pan evaporation were measured at the PAU meteorological station, about 1.5 km from the experimental site. Rainfall was measured using an automatic rain gauge installed at the experimental site.
Statistical analyses
The data so obtained was analysed by analysis of variance (ANOVA) using GenStat V.10.3 software. The treatment means were compared by least significant difference (LSD) at 5% level of probability.
RESULTS
Weather
The maximum temperature during the months of March–May was slightly higher in 2012–13 than in 2013–14 and the long-term average maximum temperature. It reversed during June–October being lower in 2012–13 than in 2013–14 and the long-term average. However, the minimum temperature was almost similar in the 2 years, being slightly higher than the long-term average during June–July and October (Figure 1a). The pan evaporation was similar during November–April in the 2 years of study. However, it was higher during June–September in 2013–14 than in 2012–13 and the long-term average (Figure 1b). The total amount of rainfall was higher (891.6 mm) in 2012–13 than in 2013–14 (582.3 mm) (Figure 1c), but the rains were better distributed during 2013–14 (42 rainy days) than during 2012–13 (31 rainy days). The month of June recorded abnormally higher rainfall (296.4 mm) during 2012–13 compared to 30.3 mm during 2013–14 (Figure 1d).
Figure 1. Mean monthly maximum and minimum temperatures (a), pan evaporation (b), cumulative rainfall (c) and monthly rainfall distribution (d) during the study period (2012–14).
Crop performance
Wheat
Growth parameters: The crop stand and growth in all the plots was generally good in both the years as indicated by the coefficient of variation of biomass production within the treatments which ranged from 2.1 to 27.4% during 2012–13 and 2.5 to 31% during 2013–14. The wheat biomass in ZTW plots during 2012–13 was slightly lower than that in CTW plots till 110 DAS but later on the biomass was higher in ZTW plots than in the CTW plots (Figure 2a). It was 11% higher at 131 DAS and the difference decreased to 6% at 156 DAS. During 2013–14, the wheat biomass was similar in ZTW and CTW plots throughout the crop season (Figure 3a). The residual effect of the rice establishment method on wheat biomass was not observed at all the observed growth (Figure 3b).
Figure 2. Effect of tillage in wheat on biomass accumulation (a), tillers density (b) and leaf area index (c) of wheat during 2012–13.
Figure 3. Effect of tillage in wheat, rice establishment methods and tillage in rice on biomass accumulation (a–c), tiller density (d–f) and leaf area index (g–i) of wheat during 2013–14 (Bars indicate LSD (0.05) values).
The tiller density of wheat was initially higher in CTW plots than in ZTW plots during both the years (Figures 2b, 3d), but it was similar during the later growth stages with respect to tillage in wheat and rice and rice establishment method (Figure 3e–f). The LAI of wheat was higher in CTW than in ZTW plots at all the crop stages during both the years (Figures 2c, 3g). It was statistically similar with respect to establishment method (Figure 3h) and tillage in rice (Figure 3i).
Yield parameters: The yield attributes viz. grains per panicle, average grain weight and harvest index of wheat were not affected significantly by tillage in wheat, establishment method and tillage in rice (Tables 4–6).
Table 4. Interactive effect of tillage and establishment methods on grain panicle−1 and floret fertility percentage of wheat and rice during 2012–2014.
LSD (0.05) for EM(R) × T(R) = 1.18 (Rice-2013) and 3.9 (Rice-2014).
Table 5. Interactive effect of tillage and establishment methods in wheat and rice on average grain weight (mg) of wheat and rice during 2012–2014.
LSD (0.05) for T(W) × T(R)= 0.58 (Rice-2014).
Table 6. Interactive effect of tillage and establishment methods on harvest index of wheat and rice during 2012–2014.
LSD (0.05) for EM(R) × T(R) = 0.03 (Rice-2014).
Grain yield: In general, the grain yield of wheat was higher in 2013–14 than in 2012–13. This could be due to the higher maximum and minimum temperatures during February–April in 2012–13 than in 2013–14. The grain yield of wheat was similar in CTW and ZTW plots during both the years. The establishment method and tillage in rice did not affect the wheat grain yield significantly during 2013–14 (Table 7).
Rice
Growth parameters: The biomass of rice was higher in CTW than in ZTW plots during 2013 (Figure 4a) but it was similar in the two treatments during 2014 (Figure 5a). The establishment method of rice significantly affected the crop biomass, being higher in DSR than in the MTR plots during both the years of study (Figures 4b, 5b), the differences being higher during 2014. The average crop biomass was significantly lower in zero-till rice than in puddle CTR plots (Figures 4c, 5c), irrespective of the establishment method during both the years.
Figure 4. Effect of tillage in wheat, rice establishment methods and tillage in rice on biomass accumulation (a–c), tiller density (d–f) and leaf area index (g–i) of rice during 2013 (Bars indicate LSD (0.05) values).
Figure 5. Effect of tillage in wheat (a–c), rice establishment methods (d–f) and tillage in rice (g–i) on biomass accumulation, tillers density and leaf area index of rice during 2014 (Bars indicate LSD (0.05) values).
The tiller density was not affected significantly by tillage in wheat during both the years (Figures 4d, 5d). It was initially higher in DSR plots but at later stages (130 DAS onwards), the MTR plots recorded higher tiller density than DSR plots during 2013 (Figure 4e). In 2014, the tiller density though being higher initially in DSR plots was statistically similar to that in MTR plots during later stages (Figure 5e). The effective tillers were similar with respect to tillage in rice during both the years (Figures 4f, 5f).
The LAI was slightly higher in CTW than in ZTW plots throughout the growing season during 2013 and 2014 (Figures 4g, 5g). It was significantly higher at 117 DAS in former than in later plots during 2013 (Figure 4g). The establishment method significantly affected the LAI throughout the crop growth during both the years (Figures 4h, 5h), being higher by 50% at all the crop growth stages in DSR plots than in MTR plots in 2013 and the difference increased to 115% during 2014. The tillage in rice did not affect LAI in 2013 (Figure 4i). However, it was significantly higher in puddle than in CTR and ZTR plots at 106 DAS during 2014 (Figure 5i).
Yield parameters: The floret fertility percentage was not affected by tillage in wheat during both the years of study (Table 4). The DSR plots on an average had 10.1 and 15.9% higher floret fertility during 2013 and 2014 respectively, than in MTR plots, the difference being significant at 5% level of significance. The fertility percentage was highest in puddle followed by CTR plots and lowest in ZTR plots, the differences being significant in 2013. In 2014, the puddle and CTR plots had similar fertility percentage which was significantly higher than that in ZTR plots.
The average wheat grain weight was significantly higher in CTW than in ZTW plots during 2014, while in 2013 it was similar in the two treatments (Table 5). The DSR and MTR plots had similar average rice grain weight during both the years. The tillage in rice significantly affected the average grain weight of rice, being highest in puddle, followed by CTR plots and lowest in ZTR plots both under DSR and MTR. The average grain weight in 2014 was higher in puddle and CTR plots of DSR as compared to MTR plots, whereas in ZTR plots, the establishment method did not affect the average grain weight. The HI was not affected by tillage in wheat during 2013 but in 2014 it was significantly higher in CTW than in ZTW plots (Table 6). It was highest in puddle plots, followed by CTR and lowest in ZTR plots under both the methods of establishment. The HI was significantly higher in ZTR plots of MTR than in DSR.
Grain yield: The grain yield of rice was higher in CTW than in ZTW plots during both the years, the differences being statistically significant during 2014. The grain yield of DSR was similar to that of MTR during 2013 but the difference became statistically significant during 2014, being higher in DSR. The tillage in rice significantly affected the grain yield in the order puddle > dry tilled > zero till plots during both the years. The average grain yield decreased by 17.2% in 2013 and 27.7% in 2014 in CTR plots from that in puddle plots. It further decreased by 24.4 and 28.4% in ZTR plots, respectively (Table 7). The grain yield in 2014 was significantly higher in puddle and ZTR plots of DSR than the MTR. The trend was similar in 2013 but the differences were statistically non-significant (Table 7).
Table 7. Interactive effect of tillage and establishment method on grain yield (Mg ha−1) of wheat and rice during 2012–2014.
LSD (0.05) for EM(R) × T(R) = 0.20 (Rice-2014).
Irrigation water productivity
Wheat
The WPI of wheat was significantly lower in ZTW (1.81 g kg−1) than in the CTW plots (2.16 g kg−1) during 2012–13. However, it was similar in the two treatments during 2013–14 (Table 8). The establishment method and tillage in rice had no significant effect on WPI during 2013–14. The average WPI of wheat was similar in puddled and CTR plots but was significantly higher in ZTR plots. The decrease in WPI of wheat in ZTW plots from that in CTW plots was more pronounced in puddle and CTR than in ZTR plots.
Table 8. Interactive effect of tillage and establishment methods on irrigation water productivity (g kg−1) of wheat and rice during 2012–2014.
LSD (0.05) for T(W) × EM(R)=0.06 (Rice-2013), EM(R) × T(R) = 0.03 (Rice-2014), T(W) × T(R)= 0.32 (Wheat 2013–14).
Rice
The average WPI was higher in CTW than in ZTW plots during both the years, the differences being significant during 2014. The WPI of MTR was 31.1% higher in CTW than in ZTW plots compared to 9.5% during 2013. The mean WPI was 15% higher in CTW than in ZTW plots during 2014. The average WPI of MTR was significantly higher than that of DSR during both the years. The WPI of rice in puddle, CTR and ZTR plots was similar in 2013 but the differences became significant during 2014. It was sufficiently higher in puddle (0.56 g kg−1) plots than in CTR (0.29 g kg−1) and ZTR (0.25 g kg−1) plots. The WPI was higher by 48.9% in puddle plots, 32% in CTR and 38.1% in ZTR plots of MTR than in DSR in 2014.
Cropping system productivity
Land productivity
The land productivity of RWCS was significantly affected by tillage in wheat during both the years. It was 15.8 and 11.3% higher in CTW than in ZTW plots during 2012–13 and 2013–14, respectively (Table 9). The land productivity of wheat–rice was similar in DSR and MTR plots during both the years. The tillage in rice significantly affected total land productivity in both the years, being highest in puddle followed by CTR and lowest in ZTR plots.
Table 9. Interactive effect of tillage and establishment method on land (Mg ha−1) and irrigation water productivity (g kg−1) of rice-wheat system during 2012–14.
LSD (0.05) for EM(R) × T(R) = 0.07 (WP I 2012–13) and 0.05 (WP I 2013–14).
Table 10. Interactive effect of tillage and establishment methods on weed biomass (t ha−1) in wheat and rice during 2012–2014.
LSD (0.05) for T(W) × T(R)= 0.14 (Rice-2013& Rice-2014), EM(R) × T(R) = 0.41, T(W) × T(R) = 0.41 (Wheat 2013–14).
Irrigation water productivity
The WPI of RWCS was significantly higher (16–19.5%) in CTW than in ZTW plots during 2012–14 (Table 9). The establishment method of rice significantly affected the WPI of the cropping system, being higher in MTR (0.81–0.88 g kg−1) than in DSR (0.60–0.77 g kg−1) plots. The tillage in rice significantly affected WPI of the cropping system during both the years. The WPI of RWCS, though similar in CTR (0.76 g kg−1) and ZTR (0.71 g kg−1) plots during 2012–13 was 11.2% lower in ZTR plots during 2013–14. The decrease in system WPI in 2012–13 due to zero tillage in wheat was highest (18.4%) in puddle plots, followed by 15.7% in CTR and lowest (9.8%) in ZTR plots. Similar trend was observed in 2013–14.
DISCUSSION
Weather and crop performance
The wheat grain yield, in general, was higher during 2013–14 than during 2012–13. This could be mainly because of maximum and minimum temperatures (Figure 1a) remaining higher during the months of February–April in 2012–13 than in 2013–14. These were even higher than the long-term average (Figure 1a). Higher temperature during the month of February results in greater respiration leading to shrinkage of grains and hence lowers the average grain weight, which was 34.4 mg during 2012–13 compared to 36.4 mg during 2013–14. Moreover, higher rainfall during February–April in 2012–13 than during 2013–14 (Figure 1c) could have resulted in washing down of pollens leading to lesser number of grains panicle−1 (Table 4). These were 51 in 2012–13 compared to 58.4 during 2013–14. The rice yields were almost similar in 2012–13 and 2013–14 due to similar temperature conditions during the months of July–October.
Crop and cropping system productivity
Wheat
Although every effort was made to remove the weeds in ZTW plots, still the weeds re-emerged time and again, thereby affecting the crop growth. Similar grain yield of wheat in CTW and ZTW plots despite of higher weed biomass in ZTW indicates that zero tillage can result in higher wheat productivity if the weeds are managed efficiently through effective herbicide use (Table 10). In fact, zero tillage results in accumulation of weed seeds on or near to the soil surface after sowing which may encourage higher germination percentage of these seeds due to better availability of sunlight, moisture and nutrients (Singh et al., Reference Singh, Bhullar and Chauhan2015a). The zero tillage gradually increases the mechanical impediment of the surface soil, limiting the distribution of roots in plough layer (Mosaddeghi et al., Reference Mosaddeghi, Mahboubi and Safadoust2009). The root mass density in CTW plots was 37.3% higher than in the ZTW plots in upper 0–15 cm soil layer (data not presented).
The higher biomass during later crop growth stage (Figure 2a) in 2012–13 was not reflected in wheat grain yield, though in 2013–14, it behaved similar to wheat grain yield with respect to tillage in wheat. The wheat growth, yield attributes and grain yield were not affected by tillage and establishment method of rice. The contradictory reports of wheat performance under zero tillage in the literature (Guan et al., Reference Guan, Zhang, Kaisi, Wang, Zhang and Li2015; Singh et al., Reference Singh, Humphreys, Eberbach, Katupitiya, Singh and Kukal2011) are mainly due to the site-specific conditions related to weed intensity and soil edaphic environment affecting root proliferation and water transmission characteristics.
Rice
The zero tillage in wheat affected the rice grain yield, which decreased significantly during second year of study. It could be due mainly to significantly higher weed biomass in ZTW plots during both the years. Interestingly, the weed biomass recorded in ZTW plots was higher (16.7%) in 2014 than in 2013. The DSR performed better than MTR with significant difference in 2014. The grain yield of DSR was better than MTR under all the tillage treatments in rice viz. puddle, CTR and ZTR. It could be due to the transplanting shock to MTR (Kamboj et al., Reference Kamboj, Yadav, Yadav, Goel, Gil, Malik and Chauhan2013) in comparison to DSR. The wider row spacing of MTR seedlings though resulted in higher tiller density (Figures 4e, 5e), but lower fertility percentage, average grain weight and HI lowered the MTR yields. The significantly higher rice grain yield in puddle plots was mainly due to higher fertility percentage, HI and average grain weight as compared to CTR and ZTR plots. These effects were further compounded by higher weed biomass in ZTR plots as also observed by Singh et al. (Reference Singh, Bhullar and Chauhan2015a) and Singh et al. (Reference Singh, Bhullar and Chauhan2015b). The severe iron deficiency in ZTR plots despite of FeSO4 sprays might have lowered the rice grain yields in ZTR plots as also observed by Singh et al. (Reference Singh, Humphreys, Kukal, Singh, Kaur, Thaman, Prashar, Yadav, Kaur, Dhillon, Smith, Timsina and Gajri2009) and Jat et al. (Reference Jat, Gathala, Ladha, Saharawat, Jat, Kumar, Sharma, Kumar and Gupta2009).
Wheat–rice cropping system
The significant reduction in cropping system productivity due to zero tillage in wheat was due to the yield loss both in wheat and rice (Table 9). Jat et al. (Reference Jat, Sapkota, Singh, Jat, Kumar and Gupta2014) observed that zero tillage without mulch yielded poorly as compared to dry till plots. The total land productivity was similar in DSR and MTR plots. The land productivity was highest (11.5 Mg ha−1) in CTW–DSR–PR scenario during 2012–13 and 12.6 Mg ha−1 during 2013–14, followed by CTW–MTR–PR, CTW–DST–CTR and was lowest in ZTW–MTR–ZTR. The establishment method of rice does not seem to affect the productivity of wheat–rice system. Tillage in wheat on the other hand significantly affected the productivity of the cropping system. The tillage in rice played a major role din affecting the productivity of the system increasing it in the order puddle > CTR > ZTR. Puddling might have affected the system productivity through its beneficial effects viz. destroying weed seed, reducing leaching losses (Kumar and Ladha, Reference Kumar and Ladha2011) and improving soil water retention (Kukal and Sidhu, Reference Kukal and Sidhu2004; Kukal and Aggarwal, Reference Kukal and Aggarwal2003b).
Irrigation water productivity
Wheat
The significantly higher (2.16 g kg−1) water productivity (WPI) of wheat during 2012–13 in CTW plots than in the ZTW plots (1.81 g kg−1) despite of the similar irrigation water consumption is mainly due to higher grain yield of wheat in the former plots (Table 8). However, in 2013–14, WPI was statistically similar in two tillage methods due to saving of one irrigation in the ZTW plots. In fact, the poor crop growth including the root biomass (data not presented) in ZTW plots led to lower uptake of water from the root zone for transpiration compared to that in CTW plots. Since the plots were irrigated on the basis of soil matric potential, the lower soil water depletion in ZT plots resulted in saving of one irrigation. The WPI of wheat was not significantly affected by the establishment method. Tillage in rice affected the WPI of wheat 2013–14, being statistically higher in ZTR than in CTR plots. It was similar in puddle and CTR plots. This could again be due to the similar reason as explained above.
Rice
The higher WPI of rice in CTW plots during 2014 was mainly because of higher grain yields with similar irrigation water consumption as compared to that in ZTW plots (Table 8). The significantly higher WPI of MTR compared to the DSR during both the years was mainly due to 23.5–63.5% higher irrigation water consumed in the DSR plots. In fact, the DSR with longer crop duration in the field experiences higher evapo-transpiration losses as compared to the MTR plots, thereby consuming higher irrigation water. The highest WPI in puddle plots was due to the lowest amount of the irrigation water consumption in these plots during both the years, followed by that in ZTR and highest in CTR plots. The lowest irrigation water consumption in puddle plots is due to three times higher infiltration rate of unpuddled as compared to puddle soil (Kukal et al., Reference Kukal, Yadav, Kaur and Singh2009; Kukal et al., Reference Kukal, Singh, Jat and Sidhu2014; Singh et al., Reference Singh, Humphreys, Eberbach, Katupitiya, Singh and Kukal2011). This increases the amount of irrigation water per irrigation in unpuddled plots. Moreover, the higher irrigation water consumption in CTR compared to ZTR plots was mainly due to the lower residence time of moving water in ZTR plots particularly in the absence of any straw retention at the soil surface.
In general, the WPI of rice was higher during 2013 than in 2014. It could be due to higher (39%) and well-distributed rainfall (23 rainy days) during 2013. The higher decrease in WPI from puddle to CTR plots in MTR (50.7%) compared to DSR (44.4%) plots may be due to significantly lower grain yield of former than in later.
Wheat–rice cropping system
The zero tillage in wheat significantly decreased the average WPI of the cropping system during both the years which was due to the lower grain yield of both the crops in zero till plots (Table 9). However, the higher WPI of MTR plots compared to the DSR was due to significantly lower amount of irrigation water consumed in the former plots because of shorter duration of MTR crop in the field than that of DSR crop. The puddling resulted in highest WPI (0.9–1.0 g kg−1) among all the rice tillage treatments due to higher grain yield as well as lower irrigation inputs as explained earlier. The WPI of the cropping system was, however similar in conventional and zero till plots during 2012–13 but during 2013–14, it was significantly higher in zero till plots. It is due to lower irrigation water amount consumed in both wheat and rice crops grown in zero till plots. The WPI of both DSR and MTR was significantly higher in puddle plots than CTR and ZTR plots because of consumption of lower irrigation water amounts and reported higher grain yields.
CONCLUSIONS
The results lead us to the conclusion that the conventional tillage in wheat and rice resulted in higher land and WPI in RWCS. The zero tillage though did not affect the land and WPI of wheat, but it decreased these for the cropping system as a whole. The establishment method of rice had no impact on the land productivity of the cropping system, but the WPI of the system was higher in MTR than in DSR. The land productivity of the RWCS was highest in CTW–DSR–PR scenario and lowest in ZTW–MTR–ZTR scenario while WPI of the system was highest in CTW–MTR–PR scenario and lowest in ZTW–DSR–ZTR scenario.
