Development of a soil quality index for sequences with different levels of land occupation using soil chemical, physical and microbiological properties

Serri, Dannae Lilia; Brandán, Carolina Pérez; Meriles, José Manuel; Salvagiotti, Fernando; Bacigaluppo, Silvina; Malmantile, Alberto; Vargas-Gil, Silvina

doi:10.1016/j.apsoil.2022.104621

Cited by 10 publications

(9 citation statements)

References 68 publications

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“…There was no significant improvement in soil quality of RC for 1‐ and 6‐year systems compared with RM systems. This may be due to the differences in input quantity, crayfish breeding density, and soil texture in this study (De Laurentiis et al, 2019; Serri et al, 2022; Valani et al, 2020). According to the previous study, the BD, pH, BG, TN, MBC, and MBN were the important factors that affected the soil quality (Bilgili et al, 2019; Raiesi & Kabiri, 2016).…”

Section: Discussionmentioning

confidence: 78%

“…To comprehensively and objectively evaluate soil quality, we not only considered soil physicochemical properties but also soil biological properties, during the evaluation process (Cheng et al, 2016; Zhou et al, 2020). Moreover, the differences of farming period, soil texture, and agricultural practice also affect the selection of soil indicators for the evaluation of soil quality (Marion et al, 2022; Serri et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, soil quality can be affected from various aspects when RC farming starts and continues (Si et al, 2017;Sun et al, 2021). Among many methods for soil quality assessment, the soil quality index (SQI) is widely accepted and used, because it is not only easy to use but also reflects the effects of field management on soil quality (Serri et al, 2022;Taghipour et al, 2022). There are many factors affecting soil properties and can be indicators of soil quality.…”

Section: Introductionmentioning

confidence: 99%

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Changes in soil quality under long‐term rice‐crayfish farming in the Dongting Lake Plain, China

Du,

Wang,

Zhang

et al. 2023

Land Degrad Dev

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Rice‐crayfish (RC) integrated cultivation, as a sustainable agricultural system, could significantly improve soil fertility. However, the soil quality under the long‐term RC farming system is still unclear. To examine the effects of RC cultivation on soil quality in paddy fields, this study utilized an integrated soil quality index (SQI) for examining the soil quality at different soil profiles (0–10, 10–20, and 20–30 cm depth) in rice monoculture (RM) and RC farming systems (after 1, 6, 10, and 15 years) scattered in Nanxian County, Hunan Province, China. The minimum datasets for evaluating soil quality were assembled using the soil pH, bulk density, total nitrogen, microbial biomass carbon, microbial biomass nitrogen, and β‐d‐glucosidase. The findings demonstrated that soil quality was greatly impacted by RC farming, which improved with the increase of years under RC management. The soil quality of 10‐ and 15‐year RC farming systems were significantly higher than RM system. Besides, soil quality declined with increasing soil depth. The SQI value, which may be used as an indicator to assess the soil quality of RC systems, was dominated by total nitrogen, which contributed 27.60% to the SQI value. On the whole, long‐term RC farming affected the soil quality of paddy fields through management methods including non‐rice season flooding, feeding, and no tillage. Through this study, it was found that MDS and SQI composed of appropriate physical, chemical, and biological indicators could more objectively analyze the soil quality of long‐term RC system and provide guidance for sustainable development of RC farming.

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Section: Discussionmentioning

confidence: 78%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Changes in soil quality under long‐term rice‐crayfish farming in the Dongting Lake Plain, China

Du,

Wang,

Zhang

et al. 2023

Land Degrad Dev

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“…Among the identified six soil indexes for the MDS, the BST and SOM were definitely the core of the SQ in the thin black-soil region, which presented a strong buffering capacity for crop yield from the climate conditions. The importance of the two factors to soil productivity has been frequently reported [16,50,51]. For example, based on a three-year field experiment, Guo et al found that the corn yield decreased by 9-22% when the BST decreased from 30 to 10 cm [52].…”

Section: The Key To Improving Soil Qualitymentioning

confidence: 99%

“…For example, based on a three-year field experiment, Guo et al found that the corn yield decreased by 9-22% when the BST decreased from 30 to 10 cm [52]. The SOM is considered to be the main determining factor of corn yield [53,54], and the SOM is always identified as the top contributor to the SQ in diverse regions [16,49,51]. As a compressive index, the BST generally means a high SOM and a high nitrogen content.…”

Section: The Key To Improving Soil Qualitymentioning

confidence: 99%

Soil Quality Mediates the Corn Yield in a Thin-Layer Mollisol in Northeast China

Fang

Zhong

Peng

et al. 2023

Land

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Soil quality (SQ) is critical to sustainable agricultural development. It is sensitive to the crop yield, especially in thin-layer black-soil regions, which have experienced severe degradation in recent years. However, how to evaluate the SQ and its influence on land productivity is not clear in regions with thin black-soil coverage. Therefore, an integrated soil quality index (SQI) was constructed using diverse datasets along a 30 km transect in a typical thin-layer black-soil region of China. The results showed that obvious soil degradation was observed in this area. Black-soil thickness (BST), soil organic matter (SOM), and the total nitrogen (TN) content were the most strongly correlated with corn yield among the 13 investigated indexes, with Pearson coefficients of 0.65, 0.39 and 0.34, respectively. The minimum-dataset-based SQI using six soil properties within 0–30 cm was the optimal solution for SQ evaluation in the study area. The good performance of the established SQI using the optimal method was supported by its strong correlation with the corn yield, with a Pearson coefficient and linear R2 of 0.75 and 0.56, respectively. The BST identified by differences in colour across the soil profile provided powerful information for the SQI, the value of which would be underestimated by 8% if this index were ignored. The linear R2 between the SQI and corn yield decreased from 0.56 to 0.49 when the BST index was removed. This study showed the significance of improving the SQ in thin-layer black-soil regions. The core of soil management is to prevent the losses of surface black soil and improve the SOM content in this region. These findings can help farmers and decision makers adopt proper measures to improve SQ and thereby crop yield.

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Deciphering the Role and Diversity of Microbes Present in Millet Rhizosphere

Kotra,

Singh,

Kumar

et al. 2023

Rhizosphere Biology

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Development of a soil quality index for sequences with different levels of land occupation using soil chemical, physical and microbiological properties

Cited by 10 publications

References 68 publications

Changes in soil quality under long‐term rice‐crayfish farming in the Dongting Lake Plain, China

Changes in soil quality under long‐term rice‐crayfish farming in the Dongting Lake Plain, China

Soil Quality Mediates the Corn Yield in a Thin-Layer Mollisol in Northeast China

Deciphering the Role and Diversity of Microbes Present in Millet Rhizosphere

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