Choudhary Madhu, Jat Hanuman S, Jat Mangi L, Sharma Parbodh C
Indian Council of Agricultural Research-Central Soil Salinity Research Institute (ICAR-CSSRI), Karnal, India.
International Maize and Wheat Improvement Center (CIMMYT), New Delhi, India.
Front Microbiol. 2022 Dec 13;13:986519. doi: 10.3389/fmicb.2022.986519. eCollection 2022.
Fungal communities in agricultural soils are assumed to be affected by climate, weather, and anthropogenic activities, and magnitude of their effect depends on the agricultural activities. Therefore, a study was conducted to investigate the impact of the portfolio of management practices on fungal communities and soil physical-chemical properties. The study comprised different climate-smart agriculture (CSA)-based management scenarios (Sc) established on the principles of conservation agriculture (CA), namely, ScI is conventional tillage-based rice-wheat rotation, ScII is partial CA-based rice-wheat-mungbean, ScIII is partial CSA-based rice-wheat-mungbean, ScIV is partial CSA-based maize-wheat-mungbean, and ScV and ScVI are CSA-based scenarios and similar to ScIII and ScIV, respectively, except for fertigation method. All the scenarios were flood irrigated except the ScV and ScVI where water and nitrogen were given through subsurface drip irrigation. Soils of these scenarios were collected from 0 to 15 cm depth and analyzed by Illumina paired-end sequencing of Internal Transcribed Spacer regions (ITS1 and ITS2) for the study of fungal community composition. Analysis of 5 million processed sequences showed a higher Shannon diversity index of 1.47 times and a Simpson index of 1.12 times in maize-based CSA scenarios (ScIV and ScVI) compared with rice-based CSA scenarios (ScIII and ScV). Seven phyla were present in all the scenarios, where Ascomycota was the most abundant phyla and it was followed by Basidiomycota and Zygomycota. Ascomycota was found more abundant in rice-based CSA scenarios as compared to maize-based CSA scenarios. Soil organic carbon and nitrogen were found to be 1.62 and 1.25 times higher in CSA scenarios compared with other scenarios. Bulk density was found highest in farmers' practice (Sc1); however, mean weight diameter and water-stable aggregates were found lowest in ScI. Soil physical, chemical, and biological properties were found better under CSA-based practices, which also increased the wheat grain yield by 12.5% and system yield by 18.8%. These results indicate that bundling/layering of smart agricultural practices over farmers' practices has tremendous effects on soil properties, and hence play an important role in sustaining soil quality/health.
农业土壤中的真菌群落被认为会受到气候、天气和人为活动的影响,其影响程度取决于农业活动。因此,开展了一项研究,以调查一系列管理措施对真菌群落和土壤理化性质的影响。该研究包括基于不同气候智能型农业(CSA)的管理方案(Sc),这些方案基于保护性农业(CA)的原则制定,即ScI是基于传统耕作的稻麦轮作,ScII是基于部分CA的稻麦绿豆轮作,ScIII是基于部分CSA的稻麦绿豆轮作,ScIV是基于部分CSA的玉米小麦绿豆轮作,ScV和ScVI是基于CSA的方案,除了施肥方式外,分别与ScIII和ScIV类似。除ScV和ScVI通过地下滴灌供水和施氮外,所有方案均采用淹灌。从这些方案的0至15厘米深度采集土壤,并通过对内部转录间隔区(ITS1和ITS2)进行Illumina双端测序来分析真菌群落组成。对500万个处理后的序列进行分析表明,与基于水稻的CSA方案(ScIII和ScV)相比,基于玉米的CSA方案(ScIV和ScVI)的香农多样性指数高1.47倍,辛普森指数高1.12倍。所有方案中均存在七个门,其中子囊菌门是最丰富的门,其次是担子菌门和接合菌门。与基于玉米的CSA方案相比,基于水稻的CSA方案中子囊菌门更为丰富。发现CSA方案中的土壤有机碳和氮含量分别比其他方案高1.62倍和1.25倍。在农民的常规做法(Sc1)中土壤容重最高;然而,在ScI中平均重量直径和水稳性团聚体最低。基于CSA的做法下土壤的物理、化学和生物学性质更好,这也使小麦籽粒产量提高了12.5%,系统产量提高了18.8%。这些结果表明,在农民常规做法基础上捆绑/分层实施智能农业措施对土壤性质有巨大影响,因此在维持土壤质量/健康方面发挥着重要作用。