首页> 外文期刊>Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution >Climate Smart Agriculture practices improve soil organic carbon pools, biological properties and crop productivity in cereal-based systems of North-West India
【24h】

Climate Smart Agriculture practices improve soil organic carbon pools, biological properties and crop productivity in cereal-based systems of North-West India

机译:气候智能农业实践改善印度西北部谷物系统的土壤有机碳库,生物学性质和作物生产力

获取原文
获取原文并翻译 | 示例
       

摘要

Intensive tillage coupled with crop residue burning in rice-wheat (RW) system is a serious issue that causes soil degradation and environmental pollution. Soil organic carbon (SOC) is one of the main indicators of soil health and system's sustainability. Zero-tillage has been widely recommended as an alternative for improving carbon sequestration in soil under different ecologies. But the SOC sequestration is very inconsistent and varied as it depends on the crop management practices. This study was performed in the western Indo-Gangetic plains (IGP) of India where RW system contributes 40% to the total country's food grain basket; however there exists issue of its sustainability because of declining SOC coupled with open field crop residue burning. Therefore, we evaluated the effects of different management scenarios (Sc) namely Sc1 (conventional till rice-wheat cropping system; business as usual), Sc2 (partial climate smart agriculture (CSA)-based rice-wheat-mungbean system), Sc3 (CSA-based rice-wheat-mungbean system), and Sc4 (CSA-based maize-wheat-mungbean system) on SOC pools and biological properties after 4 crop cycles (year 2009-2013). Soil samples were collected from surface and sub surface layers (0-15 and 15-30 cm soil depth) after rice harvesting in 2013. Results showed that the SOC stock at surface layer was higher by 70% with Sc4 than Sc1 (16.2 Mg C ha(-1)) (P 0.05). All the forms of carbon in different pools were higher (P 0.05) with Sc4 and Sc2 over Scl at 0-15 and 15-30 can soil depths, respectively. At surface soil SOC pools were found in order of Sc4 > Sc3 > Sc2 > Sc1 (P 0.05). Higher lability index (LI) (2.1) and stratification ratio (SR) (2.5) of organic carbon were observed in CSA-based systems (Sc2 and Sc4). At surface layer (0-15 cm) the CSA- based scenarios (mean of Sc2, Sc3 and Sc4) showed higher (P 0.05) enzyme activities viz. dehydrogenase (641 mu gTPF g(-1) 24 h (-1)) and alkaline phosphatase (158 mu g pnitrophenol g(-1)), and microbial biomass carbon (MBC) (787 mu g g(-1)) and microbial biomass nitrogen (MBN) (98 mu g g(-1)) compared with Sc1. Higher value of the basal soil respiration (34%) was also observed with CSA-based scenarios (Sc2, Sc3, Sc4). Surface soil layer showed maximum counts of fungi, bacteria and actinomycetes in Sc4. MBC, fungal population and SOC were the most sensitive biological soil parameters identified through principal component analysis (PCA) which can be used for soil quality assessment. Therefore, medium term adoption of climate smart agricultural practices involving zero-tillage, crop establishment, residue management and crop diversification in rice-wheat system can significantly improve the systems productivity by improving SOC and soil biological quality.
机译:稻米(RW)体系中燃烧的作物残留燃烧的强化耕作是一种严重的问题,导致土壤退化和环境污染。土壤有机碳(SOC)是土壤健康和系统可持续性的主要指标之一。零耕地已被广泛推荐作为改善不同生态下土壤中碳封存的替代方案。但SOC封存非常不一致,而且变化,因为它取决于作物管理实践。该研究在印度的西部印度难潮平原(IGP)中进行,RW系统贡献了全国总食品谷物篮子的40%;然而,由于SOC拒绝与开放的田间作物残留物燃烧,存在其可持续性问题。因此,我们评估了不同管理场景(SC)即SC1(常规米 - 小麦种植制度的影响),SC2(部分气候智能农业(CSA)基础 - 小麦汞系统),SC3(基于CSA的米 - 小麦汞系统)和4种作物周期后SOC池和生物特性的SC4(基于CSA的玉米 - 小麦系统)(2009-2013年)。在2013年的水稻收获后,从表面和子表面层(0-15和15-30cm)中收集土壤样品。结果表明,SC4的表面层的SoC库存比SC4高70%(16.2mg C. HA(-1))(P <0.05)。不同池中的所有形式的碳均高(P <0.05),SC4和SC2在0-15和15-30的SCL上,分别是土壤深度。在SC4> SC2> SC1(P <0.05)的SC4> SC2> SC2> SC1(P <0.05)的顺序中,发现了地面土壤SOC池。在基于CSA的系统(SC2和SC4)中观察到有机碳的较高的可倾角(Li)(2.1)和分层比(2.5)。在表面层(0-15cm)的基于CSA的场景(SC2,SC3和SC4的平均值)显示出高(P <0.05)酶活性的ZIZ。脱氢酶(641μGTPFg(-1)24h(-1))和碱性磷酸酶(158μg硝基苯酚G(-1))和微生物生物质碳(MBC)(787μg(-1))和微生物与SC1相比,生物质氮(MBN)(98μg(-1))。基于CSA的场景,还观察到基于CSA的场景(SC2,SC3,SC4)的基础土壤呼吸(34%)的较高值。表面土壤层显示出SC4中的最大真菌,细菌和放线菌数。 MBC,真菌人口和SOC是通过主要成分分析(PCA)确定的最敏感的生物土壤参数,可用于土壤质量评估。因此,中小期采用了涉及零耕作,作物建立,残留管理和作物多样化的气候智能农业实践,通过改善SOC和土壤生物质量,可以显着提高系统生产率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号