Multivariate assessment of soil quality indicators for crop rotation and tillage in Illinois

Zuber, Stacy M.; Behnke, Gevan D.; Nafziger, Emerson D.; Villamil, María B.

doi:10.1016/j.still.2017.07.007

Cited by 107 publications

(55 citation statements)

References 49 publications

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“…On the other hand, Hickman (2002), studied nutrient availability under long-term rotations and tillage options in West Lafayette, IN, and found that unlike tillage, crop rotations had little effect on soil chemical parameters even though crop rotations with more corn had reduced pH, which might have been expected to affect nutrient availability. Similar results were found by Zuber et al (2015Zuber et al ( , 2017 when looking at rotations of CCC, CS, CSW (corn-soybean-wheat), and SSS in combination with tillage options following 14 yr of management at two Illinois sites. Though several soil attributes contributed to discriminate between the corn and soybean monocultures and, more strongly between tillage options, the rotations CCC and CS were not found to be different than the CSW rotation from a soil quality standpoint.…”

Section: Discussionsupporting

confidence: 70%

Short Corn Rotations Do Not Improve Soil Quality, Compared with Corn Monocultures

et al. 2018

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Short-duration summer annual crop rotations are widely used in the Midwest, but their long-term impact on soil quality has not been thoroughly examined. Our goal was to compare soil properties under long-term use of the most common crop rotations around Illinois, and to identify soil quality indicators for rotations in the state. Crop rotations of continuous corn (Zea mays L.) (CCC), corn-soybean [Glycine max (L.) Merr.] (CS), and corn-corn-soybean (CCS) were arranged in a randomized complete block design (RCBD), with three or four replications at each of six locations, with all phases present each year for 12 yr. We measured 21 soil properties on the surface soil and 18 properties at four successive depths, rendering a total of 126 and 504 observations available for the multivariate statistical analyses, including principal component analyses (PCA) and canonical discriminant analysis (CDA) in both data sets. We found that our discriminant rules based on the measured soil properties correctly identified the location of origin of the soil samples in 98% of cases, representing <2% error rates for the cross-validation results at each location. Crop rotations, on the other hand, did not affect any of the soil properties evaluated, results further confirmed by our CDA analyses that showed high error rates for classification. Though these short corn rotations make economic sense, they behave similarly to corn monocultures from the soil quality standpoint, compromising the sustainability of our current agricultural systems and highlighting the need to increase temporal and spatial diversification.

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Section: Discussionsupporting

confidence: 70%

Short Corn Rotations Do Not Improve Soil Quality, Compared with Corn Monocultures

et al. 2018

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“…Lastly, three subsamples from the 1-2-mm soil fraction were used to determine the water aggregate stability (WAS) with an Eijkelkamp wet sieving apparatus (Eijkelkamp Agrisearch Equipment, Giesbeek, The Netherlands), following Kemper and Rosenau [54]. The microbial biomasses of C (MBC, µg g −1 ) and N (MBN, µg g −1 ) were analyzed on a Shimadzu TOC-L and TNM-L analyzer (Shimadzu Corporation, Kyoto, Japan), following the modified chloroform fumigation extraction protocol for air-dried soils described in Zuber, et al [55]. Furthermore, soil macronutrients included soil ammonia intensity (NH 4 , mg-N kg −1 day −1 during the growing season), soil nitrate intensity (NO 3 , mg-N kg −1 day −1 during the growing season), and total soil nitrogen intensity (TIN, mg-N kg −1 day −1 during the growing season), which was determined by trapezoidal integration of soil concentration over time [8]-NH 4 and NO 3 separately and the sum of the two for TIN.…”

Section: Soil Sampling and Analysesmentioning

confidence: 99%

Exploring the Relationships between Greenhouse Gas Emissions, Yields, and Soil Properties in Cropping Systems

et al. 2018

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Abstract:Relationships between greenhouse gas emissions, yields, and soil properties are not well known. Utilizing two datasets from long-term cropping systems in Illinois, USA, our we aim to address these knowledge gaps. The objective of this study was to explore the relationships between the physical and chemical properties and greenhouse gas (GHG) emissions of soil, and cash crop yields over a four-year time-period and following 15 years of treatment implementation in Illinois, USA. The experimental layout was a split-plot arrangement involving rotation and tillage treatments in a randomized complete block design with four replications. The studied crop rotations were continuous corn [Zea mays L.] (CCC), corn-soybean [Glycine max (L.) Merr.] (CS), continuous soybean (SSS), and corn-soybean-wheat [Triticum aestivum L.] (CSW), with each phase being present for every year. The tillage options were chisel tillage (T) and no-tillage (NT). We used an array of multivariate approaches to analyze both of our datasets that included 31 soil properties, GHG emissions (N 2 O, CO 2 , and CH 4 ) and cash crop yields. The results from our analyses indicate that N 2 O emissions are associated with a low soil pH, an increased Al concentration, the presence of soil nitrate throughout the growing season, an increase in plant available water (PAW) and an increased soil C concentration. Likewise, soil CO 2 respiration was correlated with low pH, elevated Al concentrations, low Ca, increased PAW, higher levels of microbial biomass carbon (MBC), and lower water aggregate stability (WAS). Emissions of CH 4 were associated with increased levels of MBC. Lastly, the yield index (YdI) was correlated with lower levels of soil Ca and available P and lower values of WAS. The association between high YdI and lower WAS can be attributed to tillage, as tillage lowers WAS, but increases yields in highly productive cropping systems in the Midwest.

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“…Selection of variables (indicators) for inclusion in a SQI may be simplified by statistical methods. Several multivariate statistical techniques and modelling approaches have been widely applied to evaluate soil quality for different soils under different management regimes (Biswas et al 2017;Brejda et al 2000;de Paul Obade and Lal 2016;Nabiollahi et al 2018a,b;Nosrati 2013;Raiesi 2017;Sánchez-Navarro et al 2015;Yu et al 2018b;Zuber et al 2017). While the number and diversity of soil quality studies has increased, there remains a need to explore the scope for developing new SQIs.…”

Section: Introductionmentioning

confidence: 99%

A soil quality index for evaluation of degradation under land use and soil erosion categories in a small mountainous catchment, Iran

Nosrati

Collins

2019

J. Mt. Sci.

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Multivariate assessment of soil quality indicators for crop rotation and tillage in Illinois

Cited by 107 publications

References 49 publications

Short Corn Rotations Do Not Improve Soil Quality, Compared with Corn Monocultures

Short Corn Rotations Do Not Improve Soil Quality, Compared with Corn Monocultures

Exploring the Relationships between Greenhouse Gas Emissions, Yields, and Soil Properties in Cropping Systems

A soil quality index for evaluation of degradation under land use and soil erosion categories in a small mountainous catchment, Iran

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