Quantifying the effect of soil organic matter on indigenous soil N supply and wheat productivity in semiarid sub-tropical India

Benbi, D. K.; Chand, Milap

doi:10.1007/s10705-007-9100-z

Cited by 41 publications

(16 citation statements)

References 15 publications

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“…The organic N pool size regulates N mineralization rate in many soils (Wang et al, 2001, O'Connell et al, 2003, Li et al, 2008) despite that some studies reported that the C/N ratio (Springob and Kirchmann, 2003), or the amount of labile soil components may be better predictors (Mishra et al, 2005). Apparent mineralization assessed by the balance approach had been observed to be curvilinearly‐correlated to soil organic C with a net release of 4.8 kg N Mg −1 organic C in some subtropical Indian soils (Benbi and Chand, 2007). The ANN model developed for pampean agroecosystems predicted a mean ANMH of approximately 8 kg N Mg −1 organic N, a much lower mineralization rate, for these soils with a mean C/N of approximately 10 for soil organic matter (Table 1).…”

Section: Discussionmentioning

confidence: 99%

Modeling Apparent Nitrogen Mineralization under Field Conditions Using Regressions and Artificial Neural Networks

Álvarez

Steinbach

2011

Agronomy Journal

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Soil N mineralization is an important source of N for grain crops, but its estimation under fi eld conditions is usually very difficult. Our objective was to develop models suitable for predicting N mineralization during the growing seasons of wheat (Triticum aestivum L.) and corn (Zea mays L.) under fi eld conditions. Fift y-eight fi eld experiments were performed with wheat, and 35 with corn, along three growing seasons, in which soil apparent N mineralization was estimated by the mass balance approach. Apparent nitrogen mineralized from decomposing residues (ANMR) or soil humic substances (ANMH) were estimated separately. Two empirical modeling techniques were tested, linear regression and artifi cial neural networks, using as independent variables or inputs some environmental variables. Both techniques allowed the development of suitable models for N mineralization prediction (R 2 > 0.68), but neural networks gave slightly better results. Th e ANMR ranged from −42 to 64 kg N ha −1 , increasing as residue mass and N concentration increased. An average ANMR of 15 to 16 kg N ha −1 was produced both during wheat and corn growing seasons. Th e ANMH ranged from −80 to 328 kg N ha −1 , being on average four times greater during corn growing cycle than during wheat season (127 vs. 34 kg N ha −1 ). Th e ANMH decreased as initial mineral N content of the soil, remaining residue mass or fi ne particles content of the soil increased, and it was greater in soils of higher organic matter level and mineralization potential, as determined by an incubation test. Increases in temperature and rainfall also determine greater ANMH. Th e methodology developed for apparent N mineralization estimation may be applied to other crops and production regions.

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Section: Discussionmentioning

confidence: 99%

Modeling Apparent Nitrogen Mineralization under Field Conditions Using Regressions and Artificial Neural Networks

Álvarez

Steinbach

2011

Agronomy Journal

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“…Soil organic matter (SOM) and various physical properties are important indicators of soil quality and play an important role in the soil functionality of production (Shukla et al, 2006;Benbi and Chand, 2007). Cavalieri et al (2009) reported that dynamic properties such as soil aeration, aggregation, bulk density and water transmission have a greater impact on soil physical quality in the surface layers.…”

Section: Introductionmentioning

confidence: 99%

Effects of no-tillage systems on soil physical properties and carbon sequestration under long-term wheat–maize double cropping system

Huang

Liang

Wang

et al. 2015

CATENA

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A thorough assessment of changes in soil quality associated with soil management practices is vital for the selection and establishment of sustainable agricultural management. The winter wheat (Triticum aestivum L.)-maize (Zea mays L.) double cropping system was used to study the integrated effects of a 9-year-old tillage coupled with fertilization on soil carbon sequestration and other physical properties in the Yellow River Delta (YRD). Three tillage systems were selected: no-tillage with straw cover plus recommended urea nitrogen rate (NTS), no-tillage with straw removed and manure applied plus recommended urea nitrogen rate (NTM), and conventional tillage with straw removed plus conventional urea nitrogen application rate (CT). There were three replicates of each treatment organized in a randomized block design. NTS and NTM treatments were found to result in a slightly decrease in the soil bulk density (BD), and significantly increased the proportion of water stable aggregates (WSA) (N2 mm), as well as the water infiltration capacity. The proportion of water stable macroaggregates (N0.25 mm), the mean weight diameter (MWD) and the geometric mean diameter (GMD) of aggregates in the 0-20 cm layer were unchanged by NTS and NTM. The total soil organic carbon (SOC) stock at a depth of 0-60 cm was not significantly different among the treatments. Both aggregate-associated SOC concentration and stocks (0-5 cm) were significantly greater for NTS and NTM compared with CT, while CT led to a greater OC accumulation in the 20-60 cm soil layer compared with NTS and in the 10-20 cm compared with NTM. The mesoaggregate fraction (2-0.25 mm) and its associated OC pool accounted for the highest percentages in the whole soil profile under the CT treatment. The NT system was found to have a positive effect on the investigated soil physical properties and increase soil carbon content in the soil surface layer. The CT system in conjunction with the wheat-maize double cropping system, however, improved soil aggregation in the soil profile (0-60 cm) and also maintained a higher fraction of SOC in the subsoil compared with the NT systems.

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“…Similarly, there are studies from temperate regions which have also reported a strong positive impact of the SOC pool on agronomic yields, including those from Australia(Cotching et al 2002;Farquharson et al 2003), Relationship between grain yield and soil organic carbon concentration in a cambisol, New Delhi, India (Redrawn fromKanchikerimath and Singh, 2001) Influence of soil organic carbon concentration on grain yield of wheat with and without fertilizer and on productivity (redrawn fromBenbi and Chand 2007) …”

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confidence: 99%

Beyond Copenhagen: mitigating climate change and achieving food security through soil carbon sequestration

Lal¹

2010

Food Sec.

193

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This article explains the technical potential of C (carbon) sequestration in world soils for mitigating climate change and describes its positive impacts on agronomic productivity and global food security through the improvement of soil quality. It also supports the idea of economic development through the provision of payments to farmers in developing countries for their stewardship and enhancement of ecosystem services. These would be generated by their use of recommended management practices for improved agriculture. The technical potential of C sequestration in soils of terrestrial ecosystems and restoration of peat soils is ∼3 Petagram (Pg) C/yr (i.e. 3×10 15 g=3× 10 9 tonnes C/yr) or 50 ppm draw down of atmospheric CO 2 by the end of the 21st century by increasing the soil C pool at a rate of 1 Mg/ha/yr. Depending upon climate and other variables, this could increase cereal and food legume production in developing countries by 32 million Mg/yr and roots and tubers by 9 million Mg/yr. It is precisely this strategy which would have received broad political support at the COP-15 meeting in Copenhagen in December 2009 from developing countries, emerging economies and the industrialized world. Addressing the issue of foodinsecurity and global warming through sequestration of C in soils and the biota, along with payments to resource-poor farmers for the ecosystem services rendered, would be a timely win-win strategy.

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Quantifying the effect of soil organic matter on indigenous soil N supply and wheat productivity in semiarid sub-tropical India

Cited by 41 publications

References 15 publications

Modeling Apparent Nitrogen Mineralization under Field Conditions Using Regressions and Artificial Neural Networks

Modeling Apparent Nitrogen Mineralization under Field Conditions Using Regressions and Artificial Neural Networks

Effects of no-tillage systems on soil physical properties and carbon sequestration under long-term wheat–maize double cropping system

Beyond Copenhagen: mitigating climate change and achieving food security through soil carbon sequestration

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