Next Article in Journal
A Roof Refurbishment Strategy to Improve the Sustainability of Building Stock: A Case Study
Previous Article in Journal
Experimental Study of a Homogeneous Charge Compression Ignition Engine Using Hydrogen at High-Altitude Conditions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 16
Issue 5
10.3390/su16052027
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Biological and Chemical Vicissitudes in Soil Rhizosphere Arbitrated under Different Tillage, Residues Recycling and Oilseed Brassica-Based Cropping Systems

by
Ram Swaroop Jat
,
Har Vir Singh
,
Mohan Lal Dotaniya
,
Ram Lal Choudhary
,
Mukesh Kumar Meena
and
Pramod Kumar Rai
*
ICAR-Directorate of Rapeseed-Mustard Research, Bharatpur 321 303, India
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(5), 2027; https://doi.org/10.3390/su16052027
Submission received: 19 December 2023 / Revised: 1 February 2024 / Accepted: 20 February 2024 / Published: 29 February 2024
(This article belongs to the Section Sustainable Agriculture)
Review Reports Versions Notes

Abstract

:
In this study, the impacts of long-term soil and crop management practices on crop productivity and soil health in oilseed brassica-based production systems were examined. Different tillage, crop residue recycling and cropping systems (fallow–mustard, cluster bean–mustard, green gram–mustard, maize–mustard, pearl millet–mustard and sesame–mustard) were studied for 5 years at two soil depths (0–15 and 15–30 cm) in a split-plot design with three replications. No-till permanent beds with crop residue (PB + R) noticeably improved soil organic carbon (SOC), microbial biomass carbon (MBC), enzymes (dehydrogenase (DHA) and alkaline phosphatase (AlP)), nitrogen fractions (available and total nitrate) and available phosphorus and potassium content in both soil layers compared to conventional tillage without crop residues. However, the plough soil layer (0–15 cm) showed higher concentrations of soil carbon, enzymes, N fractions and available P than in the subsoil (15–30 cm). The dynamic soil biological and chemical properties also varied with the crop stage, and higher MBC at 30 days, SOC and enzymatic activities at 60 days, and N fractions and available P and K during the harvesting of mustard crop were recorded. Green gram–mustard rotation showed higher values in terms of biological and chemical parameters. Thus, the legume-based mustard crop rotation following no-till permanent beds and residue recycling was found to be holistic in terms of improving soil health and nutrient cycling.

1. Introduction

At present, Indian food grain production has achieved self-sufficiency, even exceeding current requirements (325 mt in 2023) and almost reaching the target set for the middle of the 21st century (333 mt) [1]. However, a shrinking land resource base due to the increasing population and severe degradation of natural resources amid the changing climate scenario have led to reductions in their efficiencies [2]. In conventional agriculture, intensive use of machinery, fertilizers and pesticides has deteriorated soil quality, increased soil compaction, water erosion and salinization and decreased soil organic matter (SOM), nutrient content and biodiversity, which negatively impact soil productivity and sustainability [3]. Conservation agriculture (CA) practices have clear advantages over conventional agricultural practices in terms of improving soil health and the efficient use of natural resources, reducing the environmental impacts of agricultural activities, saving inputs, reducing the cost of production, etc. [4]. It has been demonstrated that conservation agriculture improved soil physico-chemical and biological properties that are crucial for maintaining soil health and increasing agro-ecosystem resilience to global climate change [5]. The components of CA comprise no tillage, residue recycling and cropping system diversification, producing multiple benefits to the soil health [6,7]. It mainly improves the soil organic carbon (SOC) stock and minimizes input use during the cultivation of crops [8].
Soil organic matter is core to soil health. It serves as a soil conditioner, nutrient source, food to soil microbes, preserver of the environment and a major determining factor for sustaining agricultural productivity in a region [9]. In India, the average SOC content in uncultivated soils is from 15 to 20 g/kg, whereas, in cultivated soils, it is less than 5 g/kg due to continuous heavy ploughing, removal of crop residues and other bio-solids that resulted into incessant mining of soil fertility [10]. Over time, the excessive application of tillage, use of heavy machinery, removal of crop residues and low organic matter (OM) turnover are mainly responsible for the deterioration of soil health parameters. The stock of SOC in agro-ecosystems acts as a carbon sink, sequestering ambient carbon and mitigating climate change [11,12]. It also promotes macro-aggregate formation and physically protects organic carbon and, thus, has positive effects on soil quality [13,14].
Studies have shown that CA systems have increased the soil organic matter due to the addition of crop residues that improved the soil reserves of nitrogen [15], phosphorus [16], potassium [17], calcium [18], magnesium [19], zinc [20] and manganese [19]. In addition, reduced tillage practices or no tillage under CA systems decrease the nutrient loss through runoff or adsorption into sediments that are lost due to water erosion [21]. The adoption of CA practices contributes to increasing SOC, macro-aggregates and the soil quality index (SQI) over a period of time. Regardless of the cropping system, CA practices exhibit better aggregation and SQI parameters in the topsoil compared to the subsoil [22]. In the context of crop residue scarcity, green manuring is also a viable option for enhancing the carbon pools, hydrolytic enzymatic activities and ecosystem functions [23]. A CA-based diversified cropping system improves the activity of dehydrogenase and alkaline phosphatase activity in the soil, mediating SOM decomposition, transformation and mineralization rates [24]. It plays a pivotal role in decomposition and nutrient cycling when compared to traditional cropping systems that use conventional tillage. The higher quantity of soil residues under CA systems does not guarantee to higher nutrient availability to crop plants because the nature and management of crop residues has a significant influence on nutrient dynamics in soils. The addition of legume residues results in the faster mineralization due to low C/N ratios, whereas cereal residues temporarily immobilize and impair N availability during the decomposition process due to high C/N ratios [25,26]. Appropriate soil management through crop residue retention under minimum tillage can improve the biological soil quality index and crop productivity [27].
Crop diversification increases soil microbial diversity and population because of numerous root exudates, which ultimately help in nutrient mineralization and availability [28]. Soybean and wheat residues under zero-tillage conditions improved soil organic carbon, microbial biomass carbon (MBC), the physico-chemical and biological properties of the soil and nutrient status in the soil [29]. Cover crops or intercrops with deep-rooted plants reduce nutrient loss and return them to the soil surface [30]. CA practices that use cover crops, diversify crop rotations and reduce tillage reduce 65–70% of NO3-N loss through leaching [31]. In a study in Italy, CA practices had lower NO3-N concentrations below the maximum rooting zone compared to conventional agricultural practices [32]. Soil enzymatic functions change with the nature of crops and the degree of soil disturbance [33]. CA for enhancing productivity and food security while preserving natural resources and mitigating the negative effects of traditional agricultural practices has been documented in several studies [34]. However, the impact of CA systems on soil health has spatial and temporal variations [35]. Thus, ecosystem-specific CA practices need to be developed to realize their benefits in improving soil health and crop productivity [36,37,38].
Indian mustard is an important oilseed crop in India that needs systematic efforts to exploit its genetic potential while protecting environmental resources. Oilseeds are the second largest commodity in the Indian food economy after cereals; they barely meet 50% of the domestic edible oil requirement. Oilseeds are often cultivated using rainfed conditions under limited resources (biophysical and socio-economic), poor soil health and scarcity of irrigation water, resulting in low yield levels [39]. Thus, there is a need to increase oilseed production per unit of inputs without affecting soil and environmental quality. Conservation agriculture-based diversification of traditional mustard cropping system in rainfed areas holds promise to fulfil the edible oil requirement of the country.
In this context, long-term field experiments were conducted for 5 years to see the interactive effects of different tillage practices, crop residue recycling and mustard-based cropping systems on SOC, MBC, soil enzymes, different N fractions and available P and K under semi-arid climates.

2. Material and Methods

2.1. Experimental Site

A field experiment was conducted for 5 years (2016-17–2020-21) at the research farm of the Indian Council of Agricultural Research (ICAR)-Directorate of Rapeseed-Mustard (DRMR) (77°3′ E, 27°15′ N), Bharatpur, India. Climate of the region is semi-arid, characterized by a wide range of temperatures between summer and winter. The maximum temperature during the mustard growing season fluctuated between 20.5 in January and 36.3 °C in October and had a minimum temperature between 7.0 °C January and 27.4 °C in July. Rainfall (75%) mostly occurred during the south–west monsoon season (July–September). The soils of the location were poor in organic carbon (2.4 g kg−1) and available N (126.3 kg ha−1); however, they contained moderate 0.5N NaHCO3-extractable P (17.2 kg ha−1) and 1N NH4OAc-exchangeable K (149.3 kg ha−1). The texture is a sandy clay loam with a bulk density of 1.52 Mg m−3.

2.2. Treatment Details and Agro-Techniques

The conservational agriculture (CA) practices following no/reduced tillage, crop residue retention and cropping systems were evaluated in this experiment. We allocated three-tillage and crop residue recycling practices (permanent beds with residue (PB + R), zero-tillage with residue (ZT + R) and conventional tillage without residue (CT − R)) in the main plots and six-oilseed brassica-based cropping systems (fallow–mustard (F–M), cluster bean (Cyamopsis tetragonoloba L.)–mustard (CB-M), green gram (Vigna radiata L.)–mustard (GG-M), maize (Zea mays L.)–mustard (Mz-M), pearl millet (Pennisetum glaucum (L.) R. Br.)–mustard (PM-M), and sesame (Sesamum indicum L.)–mustard (S-M)) in the sub-plots. A total 18 treatment combinations was allocated in a split-plot design after randomization in three replications (Table S1). The plots were maintained as permanent plots. The best crop management practices were followed in all the treatments. The crops under different cropping systems were nourished with recommended dose of fertilizers. In Indian mustard, additional N (20%) were applied in PB and ZT plots. To control the weeds, glyphosate @ 1.0 kg a.i. ha−1 was applied 7 days before sowing in the PB and ZT plots, whereas pendimethalin @ 1.0 kg ha−1 in Indian mustard, green gram and cluster bean, and alachlor @ 1.5 kg ha−1 in sesame were applied as pre-emergence in all the plots. The crop residues retained under F–M, CB–M, GG–M, Mz–M, PM–M and S–M cropping systems were 2.3, 2.5, 3.8, 4.2, 3.1 and 2.7 Mg ha−1.
In the present study, the collection of plant material, if any, complied with relevant institutional, national and international guidelines and legislation.

2.3. Soil Sampling and Analysis

The soil samples were collected from each plot at 0–15 and 15−30 cm depth using an auger with a 5 cm diameter at 30 and 60 DAS and at the harvest of mustard crop after the completion of the 5 years. The samples were collected from three locations within each plot, and a composite sample was prepared by mixing them. Part of the fresh soil samples were kept in a refrigerator at 4 °C for the analysis of soil biological parameters, viz., microbial biomass carbon (MBC), dehydrogenase activity (DHA) and alkaline phosphatase activity (AlP). The remaining portion of the soil samples were air-dried, sieved with a 2 mm sieve and used for analysis of the soil chemical properties, viz., SOC, available N, nitrate N, total N, available P and available K. The SOC was estimated using the Walkley and Black method [40], and MBC was estimated using the fumigation method [41]. The N fractions were estimated using methods like alkaline potassium permanganate for available N [42], steam distillation for nitrate N [43] and the micro Kjeldahl digestion method for total N [44]. The available P in the soil was determined using a spectrophotometer using 0.5 M NaHCO3 extractant at pH 8.5 [45]. The available K in the soil was determined using a flame photometer using 1 N neutral ammonium acetate extractant [46]. Hydrolytic enzyme dehydrogenase (μg TPF g−1 soil 24 h−1) was estimated using triphenyl tetrazolium chloride substrate [47] and alkaline phosphatase (μg PNP g−1 h−1) using p-nitrophenol [48].

2.4. Statistical Analysis

The data were recorded for different parameters, such as SOC, MBC, DHA, alkaline phosphatases, N fractions and available P and K under different tillage and mustard-based cropping systems, and statistically analyzed using analysis of variance for the split-plot design online data analysis portal [49]. The F-test was used to determine the least significant difference (LSD) at p = 0.05 among the main and sub-plot treatment effects of the tillage systems and cropping systems.

3. Results

3.1. Soil Organic and Microbial Biomass Carbon under Different Managements

The soil organic carbon content increased significantly (p < 0.05) with CA practices (PB + R and ZT + R) compared to CT − R practices in rhizosphere soil (Table 1). PB + R practice improved organic carbon by 19 and 57% in topsoil and 14 and 35% in the subsoil (15–30 cm) at 30 DAS compared to ZT + R and CT − R, respectively. In comparison to the rest of the practices, ZT + R also increased the organic carbon content markedly at 30 DAS over the CT − R by 32% in the topsoil and 19% in the subsoil. PB + R was on par with ZT + R and was recorded as having a markedly higher organic carbon content at 60 DAS, increasing by 14% in the topsoil and 15% in the subsoil over the CT − R. At harvest, the organic carbon content did not have a significant influence (p < 0.05) due to different tillage and residue management practices; however, PB + R practice was recorded as having the highest increment of 11 and 9% in the topsoil and subsoil layers over the CT − R, respectively.
Indian mustard-based cropping systems significantly influenced soil organic carbon content and recorded the highest in the GG–M system in the topsoil and subsoil at all crop stages (30 and 60 DAS and at harvest), as depicted in Table 1. The GG–M cropping system increased the organic carbon content by 52%, 14% and 13% in the topsoil and 36%, 18% and 2% in the subsoil at 30 and 60 DAS and at harvest over the F–M system, respectively. Organic carbon content increased from 30 to 60 DAS in all cropping systems; however, significantly lower values at the harvest stage were recorded.
Soil microbial carbon significantly (p < 0.05) increased with the use of CA practices (PB + R and ZT + R) compared to CT − R practices up to the 30 cm soil depth in the crop season (Table 2). At 30 DAS, PB + R was recorded as having an MBC of 128 mg/kg in the surface soil and 123 mg/kg in the subsoil. These values were higher by 11% and 27% in the topsoil and 12 and 34% in the subsoil over ZT + R and CT − R, respectively. ZT + R also increased MBC at 30 DAS by 14% and 20% in the topsoil and subsoil layer over CT − R, respectively. With a growing crop period of up to 60 DAS, MBC increased by 10% and 26% in the topsoil and 10 and 31% in the subsoil with PB + R over ZT + R and CT − R, respectively. MBC also increased with the use of ZT + R by 14% and 19% in the topsoil and subsoil layer at 60 DAS, respectively. At harvest, PB + R was recorded as having higher MBC by 9% and 18% in the topsoil and 8 and 22% in the subsoil over ZT + R and CT − R, respectively. ZT + R also increased MBC at harvest by 8% in the topsoil and 12% in the subsoil layer over CT − R, respectively. It was also observed that different cropping systems affected the MBC in the soil at different crop stages. The legume-based cropping systems (GG–M and CB–M) were recorded as having higher soil MBC compared to the conventional cropping system (F–M). The GG–M system showed better productivity in terms of microbial count, and an MBC value of 146 mg/kg was recorded in the surface soil and 124 mg/kg was recorded in the subsoil at 30 DAS. However, at further crop stages, a lower amount of MBC was recorded than 30 DAS. MBC content increased by 46%, 30% and 29% in the topsoil, whereas it increased by 31%, 23% and 22% in the subsoil at 30 and 60 DAS and at harvest in the GG–M cropping system over the F–M system, respectively.

3.2. Dehydrogenase (DHA) and Alkaline Phosphatase (AlP) Activity under Different Managements

Dehydrogenase enzyme activity in soil increased significantly under CA practices (PB + R and ZT + R) compared to CT during the crop season up to 30 cm of soil depth (Table 3). PB + R increased DHA at 30 DAS by 23 and 41% in the topsoil and 19 and 36% in the subsoil over the ZT + R and CT − R, respectively. The ZT + R also increased DHA markedly at 30 DAS over the CT − R by 15% in the topsoil and 14% in the subsoil. DHA activity increased with increasing crop duration. At 60 DAS, the PB + R increased DHA over ZT + R and CT − R by 6 and 26% in the topsoil and 23 and 30% in the subsoil, respectively. At 60 DAS, DHA also increased 63% in the surface layer and 53% in the subsoil in ZT + Rplots over CT − R. At harvest, PB + R, on par with ZT + R, significantly enhanced the DHA level of 10% in the topsoil and 15% in the subsoil over the CT − R. ZT + R also increased DHA significantly at harvest by 10% in the topsoil and 13% in the subsoil over the CT − R.
In cropping systems, the secretion of root exudated directly enhanced soil microbial count and population (Table 4). It mediated the DHA activity and plant nutrient kinetics in the soil. In this experiment, legume-based cropping systems significantly (p < 0.05) increased DHA in both soil layers in the crop season compared to the other systems. The highest DHA was recorded in the GG–M system at 30 and 60 DAS and at harvest, which was higher by 45, 80 and 74% in the topsoil and 68, 26 and 65% in the subsoil over the F–M system, respectively.
Alkaline phosphatase enzyme activity in the soil was recorded as being significantly higher in PB + R compared to ZT + R and CT − R (Table 4). PB + R improved alkaline phosphatase activity at 30 DAS over the ZT + R and CT − R by 9 and 20% in the topsoil, whereas it was 25 and 54% in the subsoil, respectively. However, ZT + R also significantly increased alkaline phosphatase by 10% in the topsoil and 23% in the subsoil over CT − R. At 60 DAS, PB + R improved alkaline phosphatase activity over ZT + R and CT − R by 6 and 26% in the topsoil and 15 and 31% in the subsoil, respectively. Alkaline phosphatase activity also increased significantly (p < 0.05) at 60 DAS with ZT + R by 19% in the topsoil and 14% in the subsoil. Similarly, at crop harvest stage, alkaline phosphatase activity increased with PB + R over ZT + R and CT − R by 7 and 20% in the topsoil and 23 and 30% in the subsoil, respectively. ZT + R also improved alkaline phosphatase activity at harvest by 13% in the topsoil and 6% in the subsoil over CT − R. The legume-based cropping system GG–M recorded the highest alkaline phosphatase activity at both soil layers during the crop season compared to the other cropping systems. GG–M improved alkaline phosphatase activity by 67, 82 and 55% in the topsoil and 67, 91 and 34% in the subsoil at 30 and 60 DAS and at harvest, respectively.
Tillage and crop residue management practices markedly influenced soil-available N content at 30 and 60 DAS; however, this effect was not significant (p < 0.05) at the harvest stage (Table 5). At 30 DAS, PB + R increased available N in the soil significantly in the topsoil (0–15 cm) over ZT + R and CT − R by 35%; however, ZT + R showed no significant difference with CT − R. In the subsoil (15–30 cm), PB + R recorded higher available N in the soil compared to ZT + R (12%) and CT − R (31%). ZT + R also increased available N significantly in the subsoil over CT − R (17%) at 30 DAS. At 60 DAS, PB + R increased available N content in the soil over the ZT + R and CT − R by 7 and 69% in the topsoil and 20 and 80% in the subsoil, respectively. At 60 DAS, ZT + R practice also increased available N content in the soil over CT − R by 58% in the topsoil and 50% in the subsoil. However, tillage and residue management practices could not influence available N content at harvest, but the maximum value was recorded in PB + R. Among the different cropping systems, GG–M showed higher available N content during all the crop growth stages at 0–15 and 15–30 cm depth. The GG–M system increased available N content by 23, 95 and 11% in the topsoil and 5, 127 and 9% in the subsoil at 30 and 60 DAS and at harvest, respectively.
The soil nitrate N content improved significantly (p < 0.05) with the use of CA practices (PB + R and ZT + R) in both soil layers during the crop season compared to CT–R practices (Table 6). PB + R increased nitrate N over ZT + R and CT − R at 30 DAS by 9 and 20% in the topsoil and 7 and 19% in the subsoil, respectively. ZT + R also increased nitrate N at 30 DAS by 10 and 12% in topsoil and subsoil, respectively. At 60 DAS, PB + R accumulated soil nitrate N content over ZT + R and CT − R by 7 and 24% in the topsoil and 9% and 20% in the subsoil, respectively. Soil nitrate N was also markedly increased at 60 DAS with ZT + R by 16% in the topsoil and 10% in the subsoil over CT − R. At harvest, PB + R was reported as being on par with ZT + R, which improved soil nitrate N significantly over CT − R by 16% in the topsoil and 11% in the subsoil. ZT + R also increased soil nitrate N at harvest over CT − R by 14% in the topsoil and 8% in the subsoil layer. Cropping systems positively influenced the soil nitrate N, which was recorded as being highest in the GG–M system in both soil layers (0–15 and 15–30 cm) at all the stages from 30 DAS to harvest. GG–M increased nitrate N by 9, 28 and 8% in the topsoil and 7, 19 and 16% in the subsoil at 30 and 60 DAS and at harvest, respectively.
Total soil N content significantly (p < 0.05) increased with PB + R and ZT + R compared to CT − R and was recorded as being highest (1147 kg/ha in the subsoil) in PB + R practice (Table 7). The PB + R increased total soil N at 30 DAS by 20 and 38% in the topsoil and 34% and 48% in the subsoil compared to ZT + R and CT − R, respectively. ZT + R also increased the total soil N over the CT − R by 15% in the topsoil and 25% in the subsoil layer at 30 DAS. At 60 DAS, PB + R markedly increased total soil N over the ZT + R and CT − R by 10 and 26% in the topsoil and 13 and 24% in the subsoil, respectively. ZT + R also improved total soil N over CT − R by 18% in the topsoil and 14% in the subsoil layer. It was also observed that the higher amount of total N was measured in surface soil at 30 and 60 DAS, whereas, at harvest, the subsoil showed a higher amount of total N than in surface soil. Among the cropping systems, GG–M was recorded as having the highest total soil N content compared to other systems at both soil layers during the crop season. The GG–M system increased the total N content by 45, 55 and 36% in the topsoil and 130, 37 and 46% in the subsoil at 30 and 60 DAS and at harvest, respectively.
The available P content in the soil was significantly (p < 0.05) influenced by CA practices (PB + R and ZT + R) and was recorded as being highest in PB + R practice (Table 8). PB + R increased the available P content over ZT + R and CT − R by 17 and 9% in the topsoil and 27 and 22% in the subsoil, respectively. ZT + R also improved soil available P by 9% in the topsoil and 22% in the subsoil over CT − R. Among the cropping systems, GG–M recorded the highest available P in the soil, which was 29 and 37% higher in the topsoil and subsoil layer over the F–M system, respectively. GG–M, Mz–M and PM–M showed equal values in terms of the available phosphorus in the topsoil, whereas the subsoil samples had different values. Lower available P was measured in the subsoil samples compared to the surface soil. The available K content was also measured at harvest, and it was found that the K content markedly increased with PB + R (up to 319 kg/ha) at the end of the 5-year experiment compared to CT − R (270 kg/ha). PB + R, on par with ZT + R, increased the available K by 16 and 18% in the topsoil and subsoil over CT − R, respectively. Legume-based cropping systems (GG–M and CB-M) were recorded as having markedly higher available K in the soil compared to the conventional cropping system (F–M). GG–M increased available K in the soil by 28 and 23% in the topsoil and subsoil layer over F–M, respectively.

4. Discussion

Soil organic carbon as an indicator of soil health mediates plant nutrient dynamics in soil. In the present study, no-till permanent beds with crop residue recycling (PB + R) accumulated more SOC throughout the crop season compared to other practices. It could be due to constant crop residue addition under no soil disturbance conditions in permanent beds. CA practices (zero tillage and residue recycling) increased SOC by increasing organic inputs to the soil (plant residues) and by reducing SOC losses through oxidation and erosion [10,50]. SOC under no disturbance conditions might have also locked the organic C molecules into long-lived soil aggregates and retained as a permanent C pool. The residues of previous crops were added, decomposed and mineralized over time, and thus reached a peak at 60 DAS, showing the maximum SOC content in the soil in the present study. It might also be due to more diverse microbial populations, which can easily mineralize SOM, resulting in higher active C pools without affecting the recalcitrant pool in the residue-amended plots. Other workers have also reported that fresh crop residues are a continuous source of food for the soil biota, converting into the labile fraction of OC [51,52]. The priming effect of OC enhanced the soil aggregation stability, water holding capacity and physico-chemical properties of soils, which ultimately improved soil health and productivity [53].
The SOC content varies with soil depth due to variations in soil texture and structure and the quality of crop residues. The fractions of SOC present in the dissolved form are susceptible to leaching and were found more in the lower soil profiles. Therefore, to study the impact of CA practices, the entire plough depth (0–15 and 15–30 cm in the present study) should be analyzed [54]. The SOC content was found to be higher in the topsoil (0–15 cm) than in the subsoil (15–30 cm) in the CA plots compared to the CT plots in the present study. Higher availability of plant root exudates and microbial populations in the surface soil could be the reason behind the greater accumulation of the labile C fraction in the topsoil. Further, the accumulation rate of C content could be enhanced in topsoils due to minimum soil disturbance and the continuous enrichment of crop residues under conservation tillage practices. However, the variation in SOC storage in different plough layers depends on the quantity and quality of plant residues, time period and soil and climatic characteristics [55]. The topsoil is an active sheet for biological activities where the effects of management practices can be easily imitated [56,57]. Other workers also reported that CA practices increased the SOC stock up to 30 cm soil depth compared to conventional practices [58]. In maize–mustard rotation, CA systems keenly showed effects on SOC at 0–15 cm and 15–30 cm soil depths, while at 30–45 cm, there were no significant differences [59]. It was reported that no-tillage and reduced tillage systems with residue retention increased SOC stocks by 13 and 12% in comparison to CT practices, respectively [60]. Due to decreased exposure to air, accumulated SOC at 30 cm soil depths has a lower likelihood of oxidation–mineralization and is, therefore, anticipated to have a longer residence duration [61]. The overall effect of CA on SOC content in the plough layer (0–30 cm) was 12% more in comparison to conventional tillage, which corresponds to an increase of 0.48 Mg C/ha/year. However, the effects were variable depending on the SOC content under conventional tillage; it was 20% in soils that had ≤40 Mg C/ha, while it was only 7% in soils that had >40 Mg C/ha [62]. Thus, soils having less than 40 Mg C/ha stocks should be targeted with added residue biomass in a rotation to enrich the SOC. The soils of the current study site contained ≤10 Mg C/ha [63], which might be the possible reason for CA practices showing significant responses in terms of increased SOC compared to CT practices under semi-arid rainfed ecology. The effect of CA on SOC also depends on soil clay content, pH, EC, heavy metal and moisture, etc. [62]. Increase or decrease in SOC content depends on decomposition and mineralization processes, which are largely governed by dynamic soil and climatic parameters. These processes are also affected by the priming effects of crop residues in CA practices and mineral nitrogen and other nutrients in the CT system [64].
Legume-based cropping systems (green gram–mustard/cluster bean–mustard) were recorded as having higher organic carbon compared to cereal/oilseed-based systems in the present study. The highest organic carbon content was found in green gram–mustard cropping system where SOC increased by 13–52% in the topsoil (0–15 cm) and 2–36% in the subsoil (15–30 cm) over the traditional fallow–mustard system. SOC was recorded as being higher in the green gram–mustard cropping system, which might be due to green gram being a legume crop and the addition of an easily decomposable residue of low C/N ratio in soil compared to other crops. Legume crops inject elemental N into organic bound N and increase plant biomass and organic root exudates, which indirectly enhance the SOC content [65]. Moreover, the addition of residues with C/N ratios under a no-till system also affects the mineralization/immobilization cycle of nutrients, especially N, and thus, SOC content varied [66,67].
Microbial biomass carbon reflects the health of soils that accumulate and recycle essential plant nutrients and soil organic matter [68]. Soil microbial biomass carbon in the present study markedly increased through the use of CA practices (PB + R and ZT + R) compared to CT practices up to 30 cm of soil depth; however, the values were higher in the 0–15 cm depth throughout the crop season. The data indicated that the addition of residues helped to increase MBC, which is also considered one of the labile pools of SOC. Our findings conform to the notion that greater organic fractions improve microbial populations and their diversity in the soil, which ultimately increase MBC [69]. In CA practices, greater aeration in the topsoil might have increased the mineralization of SOM and thus increased MBC, nitrogen and microbial population [70]. Our findings revealed that MBC was recorded as being highest at 30 DAS in the topsoil, and thereafter showed a decreasing trend until harvest as well as in the subsoil layers, which could have been due to a greater availability of fresh and decomposable crop residues on the surface soil in the initial days. Other researchers have also reported that residue retention markedly increased MBC in the surface soil compared to non-residue plots in long-term [71,72,73]. Legume-based green gram–mustard cropping systems were recorded as having the highest soil MBC compared to the conventional fallow–mustard cropping system in the present study because the legume crops might have favored greater root exudates and rhizospheric microbial populations. Similar studies on a pigeon pea + soybean intercropping system under conservation tillage showed significantly higher SMB-C and SMB-N levels than CT without crop residues [74].
Analysis of enzyme activity in soil reflects the potential of the soil in performing different biochemical processes to maintain soil fertility and quality [75]. Enzyme activities are also good indicators of the decomposition potential of organic C and plant nutrients and, therefore, nutrient availability. In this study, CA-based practices significantly influenced soil enzymes such as DHA and alkaline phosphatase. Dehydrogenase enzyme activity in the soil also increased significantly under CA practices (PB + R and ZT + R) compared to CT practices during the crop season up to a 30 cm soil depth, which could be due to better aeration, a longer reaction period and the positive growth of the soil biota under CA practices [76]. The results showed that soil enzyme activity and nutrient concentration were strongly impacted by the tillage intensity, soil depth and growth phases in the present study. The higher concentration of crop residues along with the roots of previous crops in the surface soil affects microbial activities more under uncultivated soils. The secretion of root exudates under the favorable conditions of soil root ecology accelerated microbial biomass carbon accumulation, which might be a crucial factor under CA management compared to CT systems [77]. The long-term supply of C through the different residue management practices is supposed to accelerate the soil microbial count and diversity, mediating higher enzymatic activities compared to without residue plots [78]. Significant interactions were observed between different management practices and enzyme activities under CA management, directing positive improvement in soil enzyme activities [79]. It helps in the mineralization of SOM, improving nutrient cycling and the formation of soil aggregates, leading to higher crop yield [71]. Augmentation in microbial biomass, greater substrate availability, minimum soil disturbance and improved soil aggregated structures might have increased soil enzyme activity under CA-based cropping systems compared to CT [59,80]. On the other hand, the soil biological activities decreased under CT due to intensive tillage operations and lesser availability of fresh crop residues in a rice–wheat system, whereas partial CA in cereal-based systems exhibited higher DHA activity measured in the Indo-Gangatic plain of India [80].
In this experiment, DHA and alkaline phosphatase increased to their maximum from 30 to 60 DAS and slightly declined at harvest, and it was more present in the topsoil than in the subsoil. In a similar way, DHA and alkaline phosphatase activity in the soil were reported to be higher at maximum tillering in rice-based CSA systems over maize-based systems [39]. Further, the higher acid phosphatase activity in soils at the maximum tillering stage of rice and the flowering stage of the maize was reported due to the differential rate of residue decomposition, leading to variation in labile carbon release [39]. Further, the maize residues applied to the soil’s surface decomposed more quickly than rice and wheat residues, as well as mixes of those residues applied to the soil’s surface [80,81]. Studies have reported that soil biological indicators were higher under no-till plots with 30% residue of sweet sorghum in marginal soils of South Africa [82]. The microorganisms were also reported as being higher in the rhizosphere zone due to the greater rhizodeposition of C (54–63% in cereals) in below-ground carbon inputs through the roots [83]. Ectoenzymes produced in large quantities by soil microbes may break down macromolecular organic materials, facilitating the recycling of nutrients and the flow of energy in terrestrial ecosystems [14]. Legume-based cropping systems significantly improved the DHA at both soil layers (15 and 30 cm) in the crop season compared to other systems. Moreover, zero tillage, resource (irrigation water and nutrients) management and suitable crop rotation with mung bean provided hospitable habitats for microbes [84]. The decomposition of maize residues releases labile C, which become available to the microbes and resulted in higher DHA activity [39,85]. The association between no-till and crop rotation with mung bean also enhanced enzymatic activity in the soil surface [86,87,88].
Soil N fractions (available N, nitrate N and total N) increased when using CA-based practices, and crop residue recycling markedly increased at 30 and 60 DAS in relation to mustard. In this experiment, soil N fractions markedly increased when using the green gram–mustard cropping system up to 30 cm soil layers during the crop season compared to the other cropping systems. CA-based no-tillage and residue retention help to improve SOC, aggregation stability, microbial process and soil enzyme activities, which modulated the soil mineralization kinetics and increased N availability in the soil solution [89]. SOM plays a crucial role in soil fertility and sustainability, as it increases soil aggregate stability, water retention and provides essential nutrients for crops [90]. In this experiment, N fractions were reported as being the highest amount in the green gram–mustard cropping system compared to the rest of the cropping systems (Table 2). It might have been to the greater accumulation of SOM in the green gram–mustard cropping system, which induced the mineralization kinetics by enhanced soil microbial population. These processes improved the soil N levels in the soil solution and might have improved crop yield potential. These results are in close conformity with that of the 9% increase in total N under the CA-based rice–wheat system than the conventional tillage [81]. The nitrogen content was higher in the topsoil, which could be due to higher N mineralization rates and ammonium-to-nitrate ratio in intact soil core incubation in the CA top layer compared to deeply ploughed soil layers [91].
The available P and K contents in the soil were also highly influenced by CA practices (PB + R) and legume-based cropping subsystems at the end of the 5-year experiment in the top (0–15 cm) and subsoil (15–30 cm) layers. The available P content was found to be higher in the plough layer; however, a greater K content was recorded in the deeper layer. Phosphorus movement in the soil was reported less, and the leaching loss from the root zone was also lower, which might be the reason for the high P content in the topsoil [92]. Further, the applied fertilizers and organic P during the crop period accumulated 50% inorganic and 38% organic forms of P in the upper soil layer. Furthermore, enhanced SOM with fresh residue under the CA system ensures minimal soil mixing of the applied fertilizer with soluble P, leading to less fixation, adsorption and precipitation as soluble phosphate–humate complexes, thus enhancing the availability of soil P [93,94]. However, under CT, the availability of labile P is reduced due to maximum soil mixing [95]. Potassium is an important plant nutrient found in a cationic form, which is subjected to leaching in soil profiles under adequate conditions. In a study, more than 33% of the applied K leached into the lower profile after 81 days in Brazilian soils [96]. Apart from total K, only 2–3 percent of it is accessible to plants in a free soluble form since the majority is still bonded to SOM, with other soil minerals making up an estimated 95% of soil potassium [97]. Dissolved SOC also enhanced the leaching and immobilization rate of K in the lower layer of the soil profile [98]. The available P and K content in the soil was higher in the maize–mustard system in the present study under CA practices, which might have been due to the fact that the cereal residues supplied larger amounts of P and K to the soil through decomposition, as they have higher P and K concentrations in their biomass [66]. In addition to this, CA practices might have improved the availability of soil N, P and K by improving soil aggregation formation and stability, mineralization of SOM, and decreasing soil and nutrient losses from the soil [52].

5. Conclusions

Implementation of CA practices facing many challenges that must be addressed in order to increase their adoption on a large scale. This study revealed that conservation agriculture practices significantly improved soil fertility, with better chemical and biological health parameters in the top 0–15 cm soil layer. The addition of legume residues (green gram) along with mustard residues over the years improved the soil quality parameters (SOC, MBC, DHA, alkaline phosphatase, N fractions, and available P and K). In a nutshell, CA-based no-till PB + R in a GG–M cropping system with two-crop residue recycling could be a promising soil fertility management practice in northwestern India and in similar agro-ecologies of the tropic and sub-tropic regions. This study suggests that crop management practices under a specific agro-ecosystem have important implications in terms of nutrient availability to plants. The proper management of the crop residue decomposition rate promotes a balanced supply of nutrients, which could help save precious nutrients applied externally during the crop growth period. Therefore, this study leads this research area into the future, considering efforts focused on the nutrient availability and priming effects of crop residues at different crop growth stages in the rhizosphere under CA-based oilseed systems.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su16052027/s1, Table S1: Treatment abbreviations and description of management protocols for different crops in Indian mustard based cropping systems.

Author Contributions

Conceptualization, methodology, validation, investigation, data curation and writing—original draft, R.S.J.; writing—review and editing, H.V.S., M.L.D., R.L.C. and M.K.M.; project administration, P.K.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data will be made available by R.S. Jat ([email protected]) upon request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Anonymous. Second Advance Estimates of Production of Food Grains for 2022–2023; Ministry of Agriculture and Farmers Welfare, Department of Agriculture and Farmers Welfare, Government of India: New Delhi, India, 2023.
  2. Lal, R. Climate strategic soil management. Challenges 2014, 5, 43–74. [Google Scholar] [CrossRef]
  3. Smith, P.; Gregory, P.J. Climate change and sustainable food production. Proc. Nutr. Soc. 2013, 72, 21–28. [Google Scholar] [CrossRef]
  4. Rodríguez, B.C.; Durán-Zuazo, V.H.; Rodríguez, M.S.; García-Tejero, I.F.; Ruiz, B.G.; Tavira, S.C. Conservation agriculture as a sustainable system for soil health: A review. Soil Syst. 2022, 6, 87. [Google Scholar] [CrossRef]
  5. Francaviglia, R.; Almagro, M.; Vicente, J.L. Conservation agriculture and soil organic carbon: Principles, processes, practices and policy options. Soil Syst. 2023, 7, 17. [Google Scholar] [CrossRef]
  6. Caron, P.; Bienabe, E.; Hainzelin, E. Making transition towards ecological intensification of agriculture a reality: The gaps in and the role of scientific knowledge. Curr. Opin. Environ. Sustain. 2014, 8, 44–52. [Google Scholar] [CrossRef]
  7. Indoria, A.K.; Rao, C.S.; Sharma, K.L.; Reddy, K.S. Conservation agriculture—A panacea to improve soil physical health. Curr. Sci. 2017, 112, 52–61. [Google Scholar] [CrossRef]
  8. Smith, P.; Olesen, J.E. Synergies between the mitigation of, and adaptation to, climate change in agriculture. J. Agric. Sci. 2010, 148, 543–552. [Google Scholar] [CrossRef]
  9. Beillouin, D.; Corbeels, M.; Demenois, J.; Berre, D.; Boyer, A.; Fallot, A.; Feder, F.; Cardinael, R. A global meta-analysis of soil organic carbon in the Anthropocene. Nat. Commun. 2023, 14, 3700. [Google Scholar] [CrossRef]
  10. Lal, R. Soil carbon sequestration to mitigate climate change. Geoderma 2004, 123, 1–22. [Google Scholar] [CrossRef]
  11. Chenu, C.; Angers, D.A.; Barre, P.; Derrien, D.; Arrouays, D.; Balesdent, J. Increasing organic stocks in agricultural soils: Knowledge gaps and potential innovations. Soil Tillage Res. 2018, 188, 41–52. [Google Scholar] [CrossRef]
  12. Valkama, E.; Kunypiyaeva, G.; Zhapayev, R.; Karabayev, M.; Zhusupbekov, E.; Perego, A.; Schillaci, C.; Sacco, D.; Moretti, B.; Grignani, C.; et al. Can Conservation agriculture increase soil carbon sequestration? A modelling approach. Geoderma 2020, 369, 114298. [Google Scholar] [CrossRef]
  13. Powlson, D.S.; Stirling, C.M.; Thierfelder, K.C.; Rodger, P.; White, R.P.; Jat, M.L. Does conservation agriculture deliver climate change mitigation through soil carbon sequestration in tropical agro-ecosystems? Agric. Ecosyst. Environ. 2016, 220, 164–174. [Google Scholar] [CrossRef]
  14. Liu, M.; Han, G.; Zhang, Q. Effects of soil aggregate stability on soil organic carbon and nitrogen under land use change in an erodible region in southwest China. Int. J. Environ. Res. Public Health 2019, 16, 3809. [Google Scholar] [CrossRef]
  15. Alam, M.K.; Bell, R.W.; Haque, M.E.; Islam, M.A.; Kader, M.A. Soil nitrogen storage and availability to crops are increased by conservation agriculture practices in rice–based cropping systems in the Eastern Gangetic Plains. Field Crops Res. 2020, 250, 107764. [Google Scholar] [CrossRef]
  16. Haokip, I.C.; Dwivedi, B.S.; Meena Mahesh, C.; Datta, S.P.; Jat, H.S.; Dey, A.; Tigga, P. Effect of conservation agriculture and nutrient management options on soil phosphorus fractions under maize-wheat cropping system. J. Indian Soc. Soil Sci. 2020, 68, 45–53. [Google Scholar] [CrossRef]
  17. Sithole, N.J.; Magwaza, L.S. Long-term changes of soil chemical characteristics and maize yield in no-till conservation agriculture in a semi-arid environment of South Africa. Soil Till. Res. 2019, 194, 104317. [Google Scholar] [CrossRef]
  18. Chan, K.Y.; Roberts, W.P.; Heenan, D.P. Organic carbon and associated properties of a red earth after 10 years rotation under different stubble and tillage practices. Aust. J. Soil Res. 1992, 30, 71–83. [Google Scholar] [CrossRef]
  19. Sharma, V.; Irmak, S.; Padhi, J. Effects of cover crops on soil quality: Part II. Soil exchangeable bases (potassium, magnesium, sodium, and calcium), cation exchange capacity, and soil micronutrients (zinc, manganese, iron, copper, and boron). J. Soil Water Conserv. 2018, 73, 652–668. [Google Scholar] [CrossRef]
  20. Kumar, D.; Kumar, S.; Parveen, H.; Priyanka Kumar, R.; Kumari, D. Effect of establishment techniques and cropping systems on transformation of zinc in alluvial soil under conservation agriculture. Int. J. Curr. Microbiol. Appl. Sci. 2020, 9, 2585–2594. [Google Scholar] [CrossRef]
  21. Smith, D.R.; Francesconi, W.; Livingston, S.J.; Huang, C. Phosphorus losses from monitored fields with conservation practices in the Lake Erie Basin, USA. Ambio 2015, 44, 319–331. [Google Scholar] [CrossRef]
  22. Jayaraman, S.; Sahu, M.; Sinha, N.K.; Mohanty, M.; Chaudhary, R.S.; Yadav, B.; Srivastava, L.K.; Hati, K.M.; Patra, A.K.; Dalal, R.C. Conservation agricultural practices impact on soil organic carbon, soil aggregation and greenhouse gas emission in a Vertisol. Agriculture 2022, 12, 1004. [Google Scholar] [CrossRef]
  23. Sharma, S.; Saikia, R.; Thind, H.S.; Singh, Y.; Jat, M.L. Tillage, green manure and residue management accelerate soil carbon pools and hydrolytic enzymatic activities for conservation agriculture based rice-wheat systems. Commun. Soil Sci. Plant Anal. 2020, 52, 470–486. [Google Scholar] [CrossRef]
  24. Choudhary, M.; Jat, H.S.; Datta, A.; Yadav, A.K.; Sapkota, T.B.; Mondal, S.; Meena, R.; Sharma, P.C.; Jat, M. Sustainable intensification influences soil quality, biota, and productivity in cereal-based agroecosystems. Appl. Soil Ecol. 2018, 126, 189–198. [Google Scholar] [CrossRef]
  25. Feng, Y.; Liu, Q.; Tan, C.; Yang, G.; Qin, X.; Xiang, Y. Water and nutrient conservation effects of different tillage treatments in sloping fields. Arid. Land Res. Manag. 2014, 28, 14–24. [Google Scholar] [CrossRef]
  26. Govaerts, B.; Sayre, K.D.; Ceballos-Ramirez, J.M.; Luna-Guido, M.L.; Limon-Ortega, A.; Deckers, J.; Dendooven, L. Conventionally tilled and permanent raised beds with different crop residue management: Effects on soil C and N dynamics. Plant Soil 2006, 280, 143–155. [Google Scholar] [CrossRef]
  27. Sharma, K.L.; Rao, C.S.; Chandrika, D.S.; Nandini, N.; Munnalal; Reddy, K.S.; Indoria, A.K.; Kumar, T.S. Assessment of GMean biological soil quality indices under conservation agriculture practices in rainfed Alfisol soils. Curr. Sci. 2016, 111, 25. [Google Scholar] [CrossRef]
  28. Haichar, F.E.Z.; Santaella, C.; Heulin, T.; Achouak, W. Root exudates mediated interactions belowground. Soil Biol. Biochem. 2014, 77, 69–80. [Google Scholar] [CrossRef]
  29. Ronanki, S.; Behera, U.K. Effect of conservation agricultural practices and nitrogen management on soil properties. Indian J. Agric. Sci. 2019, 89, 1185–1189. [Google Scholar] [CrossRef]
  30. Rubio-Asensio, J.S.; Abbatantuono, F.; Ramírez-Cuesta, J.M.; Hortelano, D.; Ruíz, J.L.; Parra, M.; Martínez-Meroño, R.M.; Intrigliolo, D.S.; Buesa, I. Effects of cover crops and drip fertigation regime in a young almond agroecosystem. Agronomy 2022, 12, 2606. [Google Scholar] [CrossRef]
  31. Camarotto, C.; Ferro, N.D.; Piccoli, I.; Polese, R.; Furlan, L.; Chiarini, F.; Morari, F. Conservation agriculture and cover crop practices to regulate water, carbon and nitrogen cycles in the low-lying Venetian plain. Catena 2018, 167, 236–249. [Google Scholar] [CrossRef]
  32. Colombani, N.; Mastrocicco, M.; Vincenzi, F.; Castaldelli, G. Modeling soil nitrate accumulation and leaching in conventional and conservation agriculture cropping systems. Water 2020, 12, 1571. [Google Scholar] [CrossRef]
  33. Habig, J.; Swanepoel, C. Effects of conservation agriculture and fertilization on soil microbial diversity and activity. Environments 2015, 2, 358–384. [Google Scholar] [CrossRef]
  34. Sahu, G.; Mohanty, S.; Das, S. Conservation agriculture-A way to improve soil health. J. Exp. Biol. Agric. Sci. 2020, 8, 355–368. [Google Scholar] [CrossRef]
  35. Hermans, T.D.G.; Dougill, A.J.; Whitfield, S.; Peacock, C.L.; Eze, S.; Thierfelder, C. Combining local knowledge and soil science for integrated soil health assessments in conservation agriculture systems. J. Environ. Manag. 2021, 286, 112192. [Google Scholar] [CrossRef] [PubMed]
  36. Giller, K.E.; Andersson, J.A.; Corbeels, M.; Kirkegaard, J.; Mortensen, D.; Erenstein, O.; Vanlauwe, B. Beyond conservation agriculture. Front. Plant Sci. 2015, 6, 870. [Google Scholar] [CrossRef] [PubMed]
  37. Lal, R. Sustainable intensification of China’s agroecosystems by conservation agriculture. Int. Soil Water Conserv. Res. 2018, 6, 1–12. [Google Scholar] [CrossRef]
  38. Page, K.L.; Dang, Y.P.; Dalal, R.C. The ability of conservation agriculture to conserve soil organic carbon and the subsequent impact on soil physical, chemical, and biological properties and yield. Front. Sustain. Food Syst. 2020, 4, 31. [Google Scholar] [CrossRef]
  39. Jat, H.S.; Datta, A.; Choudhary, M.; Sharma, P.C.; Dixit, B.; Jat, M.L. Soil enzymes activity: Effect of climate smart agriculture on rhizosphere and bulk soil under cereal based systems of north-west India. Eur. J. Soil Biol. 2021, 103, 103292. [Google Scholar] [CrossRef]
  40. Walkley, A.J.; Black, C.A. An examination of the effect of the digestive method for determining soil organic matter and the proposed modification of the chromic acid titration method. Soil Sci. 1934, 37, 29–38. [Google Scholar] [CrossRef]
  41. Jenkinson, D.S.; Powlson, D.S. The effects of biocidal treatment on metabolism in soil—V. A method for measuring soil biomass. Soil Biol. Biochem. 1976, 8, 209–213. [Google Scholar] [CrossRef]
  42. Subbiah, B.V.; Asija, G.L. A rapid procedure for the estimation of available nitrogen in soils. Curr. Sci. 1956, 25, 259–260. [Google Scholar]
  43. Keeney, D.S.; Nelson, D.W. Nitrogen—Inorganic Forms. In Methods of Soil Analysis, Part 2; Bottomley, P.J., Angle, J.S., Weaver, R.W., Eds.; ASA, SSSA: Madison, WI, USA, 1982; p. 643. [Google Scholar]
  44. Bremmer, J.M.; Mulvaney, C.S. Nitrogen—Total. In Methods of Soil Analysis, Part 2; Bottomley, P.J., Angle, J.S., Weaver, R.W., Eds.; ASA, SSSA: Madison, WI, USA, 1982; p. 595. [Google Scholar]
  45. Olsen, S.R.; Cole, C.V.; Watanable, F.S.; Dean, L.A. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate; USDA Circular No. 939; US Government Printing Office: Washington, DC, USA, 1954.
  46. Jackson, M.L. Soil Chemical Analysis; Constable Co., Ltd.: London, UK, 1973; p. 498. [Google Scholar]
  47. Klein, D.A.; Loh, T.C.; Goulding, R.L. A rapid procedure to evaluate the dehydrogenase activity of soils low in organic matter. Soil Biol. Biochem. 1971, 3, 385–387. [Google Scholar] [CrossRef]
  48. Tabatabai, M.A.; Bremner, J.M. Use of p-nitrophenyl phosphate for assay of soil phosphatase activity. Soil Biol. Biochem. 1969, 1, 301–307. [Google Scholar] [CrossRef]
  49. SSCNARS, IASRI. Available online: http://www.iasri.res.in/sscnars/2016 (accessed on 20 May 2023).
  50. Six, J.; Ogle, S.M.; Breidt, F.J.; Conant, R.T.; Mosiers, A.R.; Paustian, K. The potential to mitigate global warming with no-tillage management is only realized when practised in the long term. Glob. Chang. Biol. 2004, 10, 155–160. [Google Scholar] [CrossRef]
  51. Jat, S.L.; Parihar, C.; Dey, A.; Nayak, H.; Ghosh, A.; Parihar, N.; Goswami, A.; Singh, A. Dynamics and temperature sensitivity of soil organic carbon mineralization under medium-term conservation agriculture as affected by residue and nitrogen management options. Soil Tillage Res. 2019, 190, 175–185. [Google Scholar] [CrossRef]
  52. Parihar, C.M.; Singh, A.; Jat, S.; Dey, A.; Nayak, H.; Mandal, B.; Saharawat, Y.; Jat, M.; Yadav, O. Soil quality and carbon sequestration under conservation agriculture with balanced nutrition in intensive cereal-based system. Soil Tillage Res. 2020, 202, 104653. [Google Scholar] [CrossRef]
  53. Bhattacharyya, R.; Das, T.; Das, S.; Dey, A.; Patra, A.; Agnihotri, R.; Ghosh, A.; Sharma, A. Four years of conservation agriculture affects topsoil aggregate associated 15nitrogen but not the 15nitrogen use efficiency by wheat in a semi-arid climate. Geoderma 2019, 337, 333–340. [Google Scholar] [CrossRef]
  54. Vanden, B.A.J.; Angers, D.A. Towards accurate measurements of soil organic carbon stock change in agroecosystems. Can. J. Soil Sci. 2006, 86, 465–471. [Google Scholar] [CrossRef]
  55. González-Sánchez, E.J.; Ordóñez, F.R.; Carbonell, B.R.; Veroz, G.O.; Gil, R.J.A. Meta-analysis on atmospheric carbon capture in Spain through the use of conservation agriculture. Soil Tillage Res. 2012, 122, 52–60. [Google Scholar] [CrossRef]
  56. Luo, Z.; Wang, E.; Sun, O.J. Can no-tillage stimulate carbon sequestration in agricultural soils? A meta-analysis of paired experiments. Agric. Ecosyst. Environ. 2010, 139, 224–231. [Google Scholar] [CrossRef]
  57. Mondal, S.; Chakraborty, D.; Bandyopadhyay, K.; Aggarwal, P.; Rana, D.S. A global analysis of the impact of zero-tillage on soil physical condition, organic carbon content, and plant root response. Land Degrad. Dev. 2020, 31, 557–567. [Google Scholar] [CrossRef]
  58. Camarotto, C.; Piccoli, I.; Ferro, N.D.; Polese, R.; Chiarini, F.; Furlan, L.; Morari, F. Have we reached the turning point? Looking for evidence of SOC increase under conservation agriculture and cover crop practices. Eur. J. Soil Sci. 2020, 71, 1050–1063. [Google Scholar] [CrossRef]
  59. Pooniya, V.; Biswakarma, N.; Parihar, C.; Swarnalakshmi, K.; Lama, A.; Zhiipao, R.; Nath, A.; Pal, M.; Jat, S.; Satyanarayana, T.; et al. Six years of conservation agriculture and nutrient management in maize–mustard rotation: Impact on soil properties, system productivity and profitability. Field Crops Res. 2021, 260, 108002. [Google Scholar] [CrossRef]
  60. Li, Y.; Li, Z.; Chang, S.X.; Cui, S.; Jagadamma, S.; Zhang, Q.; Cai, Y. Residue retention promotes soil carbon accumulation in minimum tillage systems: Implications for conservation agriculture. Sci. Total Environ. 2020, 740, 140147. [Google Scholar] [CrossRef]
  61. Ashworth, D.J.; Alloway, B.J. Soil mobility of sewage sludge-derived dissolved organic matter, copper, nickel and zinc. Environ. Pollut. 2004, 127, 137–144. [Google Scholar] [CrossRef]
  62. Yadav, R.K.; Goyal, B.; Sharma, R.K.; Dubey, S.K.; Minhas, P.S. Post-irrigation impact of domestic sewage effluent on composition of soils, crops and ground water—A case study. Environ. Int. 2002, 28, 481–486. [Google Scholar] [CrossRef]
  63. Jat, R.S.; Choudhary, R.L.; Singh, H.V.; Meena, M.K.; Singh, V.V.; Rai, P.K. Sustainability, productivity, profitability and soil health with conservation agriculture based sustainable intensification of oilseed brassica production system. Sci. Rep. 2021, 11, 13366. [Google Scholar] [CrossRef] [PubMed]
  64. Lal, R. Soil carbon management and climate change. In Soil Carbon Progress in Soil Science; Hartemink, A., Hartemink, K., McSweeney, K., Eds.; Springer International: Geneva, Switzerland, 2014; pp. 339–362. [Google Scholar]
  65. Kumar, S.; Meena, R.S.; Lal, R.; Singh Yadav, G.; Mitran, T.; Meena, B.L.; Dotaniya, M.L.; EL-Sabagh, A. Role of legumes in soil carbon sequestration. In Legumes for Soil Health and Sustainable Management; Meena, R., Das, A., Yadav, G., Lal, R., Eds.; Springer: Singapore, 2018; pp. 109–138. [Google Scholar]
  66. Meean, M.C.; Dwivedi, B.S.; Mahala, D.; Das, S.; Dey, A. Nutrient dynamics and management under conservation agriculture. In System Based Conservation Agriculture; Singh, V.K., Gangwar, B., Eds.; Westville Publishing House: New Delhi, India, 2018; p. 43. [Google Scholar]
  67. Pheap, S.; Lefevre, C.; Thoumazeau, A.; Leng, V.; Boulakia, S.; Koy, R. Multifunctional assessment of soil health under Conservation Agriculture in Cambodia. Soil Tillage Res. 2019, 194, 104349. [Google Scholar] [CrossRef]
  68. Carter, M.R. Influence of reduced tillage systems on organic matter, microbial biomass, macro-aggregate distribution and structural stability of the surface soil in a humid climate. Soil Tillage Res. 1992, 23, 361–372. [Google Scholar] [CrossRef]
  69. Gao, R.P.; Duan, Y.; Zhang, J.; Ren, Y.F.; Liang, J.M.; Jing, Y.P.; Zhao, P.Y. Effects of Long-term Fertilization on Soil Microbial Diversity and Community Structure in the Agro-pastoral Ecotone. Environ. Sci. 2023, 8, 1063–1073. (In Chinese) [Google Scholar]
  70. Li, Y.; Chang, S.X.; Tian, L.; Zhang, Q. Conservation agriculture practices increase soil microbial biomass carbon and nitrogen in agricultural soils: A global meta-analysis. Soil Biol. Biochem. 2018, 121, 50–58. [Google Scholar] [CrossRef]
  71. Kumar, B.T.N.; Babalad, H.B. Soil organic carbon, carbon sequestration, soil microbial biomass carbon and nitrogen and soil enzymatic activity as influenced by conservation agriculture in pigeonpea and soybean intercropping system. Int. J. Curr. Microbiol. Appl. Sci. 2018, 7, 323–333. [Google Scholar] [CrossRef]
  72. Spedding, T.A.; Hamel, C.; Mehuys, G.R.; Madramootoo, C.A. Soil microbial dynamics in maize-growing soil under different tillage and residue management systems. Soil Biol. Biochem. 2004, 36, 499–512. [Google Scholar] [CrossRef]
  73. Govaerts, B.; Fuentes, M.; Mezzalama, M.; Nicol, J.M.; Deckers, J.; Etchevers, J.D.; Figueroa-Sandoval, B.; Sayre, K.D. Infiltration, soil moisture, root rot and nematode populations after 12 years of different tillage, residue and crop rotation managements. Soil Till. Res. 2007, 94, 209–219. [Google Scholar] [CrossRef]
  74. Govaerts, B.; Mezzalama, M.; Unno, Y.; Sayre, K.D.; Luna-Guido, M.; Vanherck, K.; Dendooven, L.; Deckers, J. Influence of tillage, residue management, and crop rotation on soil microbial biomass and catabolic diversity. Appl. Soil Ecol. 2007, 37, 18–30. [Google Scholar] [CrossRef]
  75. Yang, Y.; Liu, H.; Wu, J.; Zhang, S.; Gao, C.; Zhang, S.; Tang, D.W.S. Soil enzyme activities, soil physical properties, photosynthetic physical characteristics and water use of winter wheat after long-term straw mulch and organic fertilizer application. Front. Plant Sci. 2023, 14, 1186376. [Google Scholar] [CrossRef]
  76. Giller, K.E.; Witter, E.; Corbeels, M.; Tittonell, P. Conservation agriculture and smallholder farming in Africa: The heretics’ view. Field Crops Res. 2009, 114, 23–34. [Google Scholar] [CrossRef]
  77. Bandick, A.K.; Dick, R.P. Field management effects on soil enzyme activities. Soil Biol. Biochem. 1999, 31, 1471–1479. [Google Scholar] [CrossRef]
  78. Engell, I.; Linsler, D.; Sandor, M.; Joergensen, R.G.; Meinen, C.; Potthoff, M. The effects of conservation tillage on chemical and microbial soil parameters at four sites across Europe. Plants 2022, 11, 1747. [Google Scholar] [CrossRef]
  79. Madarasz, B.; Jakab, G.; Szalai, Z.; Juhos, K.; Kotroczó, Z.; Tóth, A.; Ladányi, M. Long-term effects of conservation tillage on soil erosion in central Europe: A random forest-based approach. Soil Tillage Res. 2021, 209, 104959. [Google Scholar] [CrossRef]
  80. Datta, A.; Choudhary, M.; Jat, H.; Sharma, P.; Kakraliya, S.; Dixit, B.; Jat, M. Climate smart agriculture influences soil enzymes activity under cereal-based systems of north-West India. J. Indian Soc. Soil Sci. 2021, 69, 86–95. [Google Scholar] [CrossRef]
  81. Dey, A.; Dwivedi, B.; Bhattacharyya, R.; Datta, S.; Meena, M.; Das, T.; Singh, V. Conservation agriculture in a rice-wheat cropping system on an alluvial soil of north-western Indo-Gangetic plains: Effect on soil carbon and Nitrogen pools. J. Ind. Soc. Soil Sci. 2016, 64, 246–254. [Google Scholar] [CrossRef]
  82. Malobane, M.E.; Nciizah, A.D.; Nyambo, P.; Mudau, F.N.; Wakindiki, I.I. Microbial biomass carbon and enzyme activities as influenced by tillage, crop rotation and residue management in a sweet sorghum cropping system in marginal soils of South Africa. Heliyon 2020, 6, 11. [Google Scholar] [CrossRef]
  83. Singh, R.; Bhardwaj, D.R.; Pala, N.A.; Kaushal, R.; Rajput, B.S. Soil microbial characteristics in sub-tropical agroecostystems of North Western Himalaya. Curr. Sci. 2018, 115, 1956–1959. [Google Scholar] [CrossRef]
  84. Liu, R.; Yao, Y.; Li, Q.; Cai, Z.; Wei, D.; Wang, X.; Zhang, S. Rhizosphere soil microbes benefit carbon and nitrogen sinks under long-term afforestation on the Tibetan Plateau. Catena 2023, 220, 106705. [Google Scholar] [CrossRef]
  85. Pataczek, L.; Zahir, Z.A.; Ahmad, M.; Rani, S.; Nair, R.; Schafleitner, R.; Cadisch, G.; Hilger, T. Beans with Benefits―The Role of Mungbean (Vigna radiata) in a Changing Environment. Am. J. Plant Sci. 2018, 9, 1577–1600. [Google Scholar] [CrossRef]
  86. Bonini, P.C.A.; Amado, T.J.C.; Reimche, G.; Schwalbert, R.; Sarto, M.V.M.; Nicoloso, R.S.; Fiorin, J.E.; Rice, C.W. Diversified crop rotation with no-till changes microbial distribution with depth and enhances activity in a subtropical Oxisol. Eur. J. Soil Sci. 2020, 71, 1173–1187. [Google Scholar] [CrossRef]
  87. Manjaiah, K.M.; Singh, D. Soil organic matter and biological properties after 26 years of maize-wheat-cowpea cropping as affected by manure and fertilization in a cambisol in semi-arid region of India. Agric. Ecosyst. Environ. 2001, 86, 155–162. [Google Scholar]
  88. Roldan, A.; Caravaca, F.; Hernández, M.; Garcıa, C.; Sánchez-Brito, C.; Velásquez, M.; Tiscareño, M. No-tillage, crop residue additions and legume cover cropping effects on soil quality characteristics under maize in Patzcuaro watershed (Mexico). Soil Tillage Res. 2003, 72, 65–73. [Google Scholar] [CrossRef]
  89. Tigga, P.; Meena, M.C.; Dey, A.; Dwivedi, B.S.; Datta, S.P.; Jat, H.S.; Jat, M.L. Effect of conservation agriculture on soil organic carbon dynamics and mineral nitrogen under different fertilizer management practices in maize (Zea mays)-wheat (Triticum aestivum) cropping system. Indian J. Agric. Sci. 2020, 90, 1568–1574. [Google Scholar] [CrossRef]
  90. Fageria, N.K. Role of soil organic matter in maintaining sustainability of cropping systems. Commun. Soil Sci. Plant Anal. 2012, 43, 2063–2113. [Google Scholar] [CrossRef]
  91. Wacker, T.S.; Jensen, L.S.; Kristian, T.K. Conservation agriculture affects soil organic matter distribution, microbial metabolic capacity and nitrogen turnover under Danish field conditions. Soil Tillage Res. 2022, 224, 105508. [Google Scholar] [CrossRef]
  92. Pasket, A.; Zhang, H.; Raun, W.; Deng, S. Recovery of Phosphorus in Soils Amended with Manure for 119 Years. Agronomy 2020, 10, 1947. [Google Scholar] [CrossRef]
  93. Piegholdt, C.; Geisseler, D.; Koch, H.J.; Ludwig, B. Long-term tillage effects on the distribution of phosphorus fractions of loess soils in Germany. J. Plant Nutri. Soil Sci. 2013, 176, 217–226. [Google Scholar] [CrossRef]
  94. Dorneles, P.; Lisboa, B.B.; Abichequer, A.D.; Bissani, C.A.; Meurer, E.J.; Vaegas, L.K. Tillage, fertilization systems and chemical attributes of a Paleudult. Sci. Agric. 2015, 72, 175–186. [Google Scholar] [CrossRef]
  95. Kumawat, C.; Sharma, V.K.; Meena, M.C.; Dwivedi, B.S.; Baeman, M.; Kumar, S.; Chobhe, K.A.; Dey, A. Effect of crop residue retention and phosphorous fertilization on P use efficiency of maize (Zea mays) and biological properties of soil under maize-wheat (Triticum aestivum) cropping system in an Inceptisol. Indian J. Agric. Sci. 2018, 88, 1184–1189. [Google Scholar] [CrossRef]
  96. Mendes, W.; Junior, J.A.; Cunha, P.C.; Silva, A.R.; Evangelista, A.W.P.; Casaroli, D. Potassium leaching in different soils as a function of irrigation depths. Soil Water Plant Mang. 2016, 20, 972–977. [Google Scholar] [CrossRef]
  97. Etesami, H.; Emami, S.; Likhani, H.A. Potassium solubilizing bacteria (KSB): Mechanisms, promotion of plant growth, and future prospects—A review. J. Soil Sci. Plant Nutr. 2017, 17, 897–911. [Google Scholar] [CrossRef]
  98. Das, I.; Pradhan, M. Potassium-solubilizing microorganisms and their role in enhancing soil fertility and health. In Potassium Solubilizing Microorganisms for Sustainable Agriculture; Meena, V., Maurya, B., Verma, J., Meena, R., Eds.; Springer: New Delhi, India, 2016; pp. 281–291. [Google Scholar]
Table 1. SOC (%) at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residues and mustard-based cropping systems.
Table 1. SOC (%) at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residues and mustard-based cropping systems.
Crop Stage
30 DAS60 DASAt Harvest
TopsoilSubsoilTopsoilSubsoilTopsoilSubsoil
Tillage and crop residue
PB + R0.690.580.790.780.600.58
ZT + R0.580.510.740.720.570.55
CT − R0.440.430.690.680.540.53
SEm±0.010.010.020.020.010.01
LSD (p = 0.05)0.060.050.060.07NSNS
Cropping systems
F–M0.460.420.690.670.530.50
CB–M0.610.570.770.760.600.58
GG–M0.700.570.790.790.600.59
Mz–M0.590.510.760.730.590.58
PM–M0.570.510.730.710.580.54
S–M0.490.460.710.690.540.52
SEm±0.010.010.020.020.010.01
LSD (p = 0.05)0.030.040.060.060.040.04
DAS: days after sowing; F–M: fallow–mustard; CB–M: cluster bean–mustard; GG–M: green gram–mustard; Mz–M: maize–mustard; PM–M: pearl millet–mustard; S–M: sesame–mustard; PB + R: permanent beds with residue; ZT + R: zero tillage with residue; CT − R: conventional tillage without residue; SEm±: standard error of means; LSD: least significant difference.
Table 2. MBC (mg/kg) at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Table 2. MBC (mg/kg) at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Crop Stage
30 DAS60 DASAt Harvest
TopsoilSubsoilTopsoilSubsoilTopsoilSubsoil
Tillage and crop residue
PB + R12812312311810479
ZT + R1151101121079573
CT − R1019298908865
SEm±311211
LSD (p = 0.05)1255655
Cropping systems
F–M100951041008569
CB–M1351131201159881
GG–M14612413512311184
Mz–M1151101181129773
PM–M1151051091069371
S–M1021011051048870
SEm±322233
LSD (p = 0.05)967587
DAS: days after sowing; F–M: fallow–mustard; CB–M: cluster bean–mustard; GG–M: green gram–mustard; Mz–M: maize–mustard; PM–M: pearl millet–mustard; S–M: sesame–mustard; PB + R: permanent beds with residue; ZT + R: zero tillage with residue; CT − R: conventional tillage without residue; SEm±: standard error of means; LSD: least significant difference.
Table 3. Effect of tillage, crop residue and mustard-based cropping systems on DHA (µg TPF/g soil/24 h) at different crop stages after 5 years under different treatments.
Table 3. Effect of tillage, crop residue and mustard-based cropping systems on DHA (µg TPF/g soil/24 h) at different crop stages after 5 years under different treatments.
Crop Stage
30 DAS60 DASAt Harvest
TopsoilSubsoilTopsoilSubsoilTopsoilSubsoil
Tillage and crop residue
PB + R585767655453
ZT + R474863535452
CT − R414253504946
SEm±0.70.710.80.70.8
LSD (p = 0.05)334333
Cropping systems
F–M403444533937
CB–M555672606159
GG–M585779676861
Mz–M536069585458
PM–M464752514750
S–M404149484441
SEm±212211
LSD (p = 0.05)546445
DAS: days after sowing; F–M: fallow–mustard; CB–M: cluster bean–mustard; GG–M: green gram–mustard; Mz–M: maize–mustard; PM–M: pearl millet–mustard; S–M: sesame–mustard; PB + R: permanent beds with residue; ZT + R: zero tillage with residue; CT − R: conventional tillage without residue; SEm±: standard error of means; LSD: least significant difference.
Table 4. Alkaline phosphatase (µg PNP/g soil/24 h) at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Table 4. Alkaline phosphatase (µg PNP/g soil/24 h) at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Crop Stage
30 DAS60 DASAt Harvest
TopsoilSubsoilTopsoilSubsoilTopsoilSubsoil
Tillage and crop residue
PB + R242088847765
ZT + R221683737253
CT − R201370646450
SEm±0.50.3110.90.9
LSD (p = 0.05)214443
Cropping systems
F–M151261565550
CB–M221585707160
GG–M25201111078567
Mz–M231883808358
PM–M221787816951
S–M191562495248
SEm±0.70.32122
LSD (p = 0.05)216454
DAS: days after sowing; F–M: fallow–mustard; CB–M: cluster bean–mustard; GG–M: green gram–mustard; Mz–M: maize–mustard; PM–M: pearl millet–mustard; S–M: sesame–mustard; PB + R: permanent beds with residue; ZT + R: zero tillage with residue, CT − R: conventional tillage without residue; SEm±: standard error of means; LSD: least significant difference.
Table 5. Available N (kg/ha) in the soil at different crop stages in the top (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Table 5. Available N (kg/ha) in the soil at different crop stages in the top (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Crop Stage
30 DAS60 DASAt Harvest
TopsoilSubsoilTopsoilSubsoilTopsoilSubsoil
Tillage and crop residue
PB + R58476154189185
ZT + R43425745187183
CT − R43363630182174
SEm±0.40.51144
LSD (p = 0.05)1244NSNS
Cropping systems
F–M43434130175175
CB–M48396952182179
GG–M53458068194191
Mz–M48414435194182
PM–M49423634193181
S–M47384037178176
SEm±112145
LSD (p = 0.05)44531110
DAS: days after sowing; F–M: fallow–mustard; CB–M: cluster bean–mustard; GG–M: green gram–mustard; Mz–M: maize–mustard; PM–M: pearl millet–mustard; S–M: sesame–mustard; PB + R: permanent beds with residue; ZT + R: zero tillage with residue; CT − R: conventional tillage without residue; SEm±: standard error of means; LSD: least significant difference.
Table 6. Nitrate N (kg/ha) in the soil at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Table 6. Nitrate N (kg/ha) in the soil at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Crop Stage
30 DAS60 DASAt Harvest
TopsoilSubsoilTopsoilSubsoilTopsoilSubsoil
Tillage and crop residue
PB + R363131244342
ZT + R332929224241
CT − R302625203738
SEm±0.70.60.40.40.50.7
LSD (p = 0.05)322123
Cropping systems
F–M332925213937
CB–M352830234043
GG–M363132254243
Mz–M362929214141
PM–M332928214039
S–M262527204039
SEm±10.90.90.510.8
LSD (p = 0.05)333222
DAS: days after sowing; F–M: fallow–mustard; CB–M: cluster bean–mustard; GG–M: green gram–mustard; Mz–M: maize–mustard; PM–M: pearl millet–mustard; S–M: sesame–mustard; PB + R: permanent beds with residue; ZT + R: zero tillage with residue; CT − R: conventional tillage without residue; SEm±: standard error of means; LSD: least significant difference.
Table 7. Total N (kg/ha) in the soil at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Table 7. Total N (kg/ha) in the soil at different crop stages in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Crop Stage
30 DAS60 DASAt Harvest
TopsoilSubsoilTopsoilSubsoilTopsoilSubsoil
Tillage and crop residue
PB + R941617111087111341147
ZT + R784460100877210721084
CT − R684368882702910947
SEm±201415161221
LSD (p = 0.05)805660614783
Cropping systems
F–M687299774672896849
CB–M871647108582110891075
GG–M996687120292112151237
Mz–M821526107079611171065
PM–M7474489837729951045
S–M697383886747920886
SEm±231419162721
LSD (p = 0.05)653754567965
DAS: days after sowing; F–M: fallow–mustard; CB–M: cluster bean–mustard; GG–M: green gram–mustard; Mz–M: maize–mustard; PM–M: pearl millet–mustard; S–M: sesame–mustard; PB + R: permanent beds with residue; ZT + R: zero tillage with residue; CT − R: conventional tillage without residue; SEm±: standard error of means; LSD: least significant difference.
Table 8. Available P and K (kg/ha) in the soil at harvest in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Table 8. Available P and K (kg/ha) in the soil at harvest in the top- (0–15 cm) and subsoil (15–30 cm) after 5 years under different tillage, crop residue and mustard-based cropping systems.
Available PAvailable K
TopsoilSubsoilTopsoilSubsoil
Tillage and crop residue
PB + R1414274319
ZT + R1211275296
CT − R119236270
SEm±0.30.357
LSD (p = 0.05)112026
Cropping systems
F–M109227264
CB–M1211277314
GG–M1312291326
Mz–M1312277290
PM–M1311258284
S–M1211239272
SEm±0.50.358
LSD (p = 0.05)111522
DAS: days after sowing; F–M: fallow–mustard; CB–M: cluster bean–mustard; GG–M: green gram–mustard; Mz–M: maize–mustard; PM–M: pearl millet–mustard; S–M: sesame–mustard; PB + R: permanent beds with residue; ZT + R: zero tillage with residue; CT − R: conventional tillage without residue; SEm±: standard error of means; LSD: least significant difference.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Jat, R.S.; Singh, H.V.; Dotaniya, M.L.; Choudhary, R.L.; Meena, M.K.; Rai, P.K. Biological and Chemical Vicissitudes in Soil Rhizosphere Arbitrated under Different Tillage, Residues Recycling and Oilseed Brassica-Based Cropping Systems. Sustainability 2024, 16, 2027. https://doi.org/10.3390/su16052027

AMA Style

Jat RS, Singh HV, Dotaniya ML, Choudhary RL, Meena MK, Rai PK. Biological and Chemical Vicissitudes in Soil Rhizosphere Arbitrated under Different Tillage, Residues Recycling and Oilseed Brassica-Based Cropping Systems. Sustainability. 2024; 16(5):2027. https://doi.org/10.3390/su16052027

Chicago/Turabian Style

Jat, Ram Swaroop, Har Vir Singh, Mohan Lal Dotaniya, Ram Lal Choudhary, Mukesh Kumar Meena, and Pramod Kumar Rai. 2024. "Biological and Chemical Vicissitudes in Soil Rhizosphere Arbitrated under Different Tillage, Residues Recycling and Oilseed Brassica-Based Cropping Systems" Sustainability 16, no. 5: 2027. https://doi.org/10.3390/su16052027

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop