Summary: Excess fertilizer applied to
agriculturally important crops such as corn can leach into nearby waterbodies and lead to harmful algal blooms. To retain the excess fertilizer from leaching, cover crops are being used to retain nutrients and promote soil health. However, the cover crop decomposition rate is still unknown and the type/mixes of cover crop that releases nutrient at a slower rate for an even load on tile water upon decomposition is unclear. We propose to determine the effect of cover crop on nutrient retention/release, soil health and water quality. As fungal/microbial activities are central to cover nutrient cycling, transfer and decomposition, the functional genes associated with fungal co-denitrification, bacterial denitrification, the dissimilatory nitrate reduction to ammonium (DNRA) and anammox pathways will be quantified. The role of these activities in nitrate reduction affected by cover crop decomposition on soil health and tile water quality will help us modulate the microbiome
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Corresponding author
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[email protected]Assistant Professor in Soil Microbiology, Biology and Microbiology Department, SDSU; Co-PI: Michael Lehman, Adjunct faculty, Plant Science Department, SDSU, Research Microbiologist, USDA-ARS, North Central Agricultural Research Laboratory.
feeding into the woodchip bioreactor
downstream to maximize the nutrient removal. Cover crop decomposition and microbial metabolic pathway analyses: In the field, we have collected corn roots on 6/22 to quantify the abundance and diversity of functional genes related to N cycling transformations of interest by quantitative polymerase chain reaction (qPCR). Therefore, soil DNA extraction is on the way. qPCR based quantification of the nrfA and hzo genes involved in DNRA and anammox, respectively, will enable the comparisons of gene abundance. Similarly, qPCR based quantification of fungal co-denitrification gene will be measured by P450nor genes. In the greenhouse experiment, we performed preliminary evaluation of the nutrient release from the decomposition of different cover crops. Leachates were analyzed for phosphorusby colorimetric method to determine nutrient levels comparing rye and oats.
Progress (up to June 2018): A postdoctoral research associate, Dr. Suresh Damodaran, was hired to oversee the day-to-day activity of the project from September until January, but left because of other interest. Recently, Dr. Huma Saleem was hired to continue with the project. On October 4th, soil samples were collected from the tiled fields before the rye/cover crop planting in the SDSU Southeast Research Farm. Soil health was assessed by measuring short- term mineralizable C, permanganate oxidizable
74 C (POXC), β-glucosidase enzyme activity that
catalyzes the depolymerization of cellulose, and total soil protein. These soil health measures have been shown to reflect levels of soil nutrient cycling that result in retention of C and N in the soil and are associated with positive soil-water dynamics. Both the mineralizable C and POXC showed no significant difference in the soil active C between the fields chosen for pre-cover crop treatment and pre control treatment plots (Fig 1A and 1B). The other soil health indicators such as the β-glucosidase assay for the enzyme activity and total protein content also indicated no significant difference in the two treatment plots (Fig 1C and 1D). For statistical analysis paired t-test was performed with a P ≤0.05. These preliminary soil health analysis report indicated that there is no significant difference in the soil properties prior to cover crop treatment, which will enable us to determine the change in soil health due to the treatments proposed. Soil DNA were extracted, and bacterial diversity have been sequenced. Data analysis is ongoing. For the cover crop decomposition assay in the greenhouse, we have planted oats, rye or triticale as shown in Fig 1E on November 18. The termination date was December 18, performed based on the recommended growth stage by the Midwest Cover Crop Council (MCCC).
Leachate were collected on June 6 thanks to the hiring of Dr. Saleem. Data showed that there is wide variation between the three replications but there is no significantly higher concentration of
phosphorus found in the leachat of decomposing oats or rye compared to the negative control. Growers should not have concern over
phosphorus leaching from decomposing rye or oats, based on our finding.
Plan for July 1 2018 to Dec 31 2018:
In collaboration with Dr. Peter Sexton at SDSU for the infield rye comparison, we will continue to quantify rhizospheric soil N-cycling genes. 1) use of cover crops (already funded to some extent and field work has started); 2) research on bioreactors (will be fully installed in the spring with EQIP support); 3) create a small managed wetland at the end of the tile line. These three measures would be in a series, so hopefully the cumulative effect is substantial. We will inoculate one of the bioreactors with a fungal isolate that is supposed to help with co- denitrification. We will finish the qPCR as described.
ACKNOWLEDGEMENT
The authors appreciate the support of the South Dakota Agricultural Experiment Station, the Soil Microbiology, Biology, and Microbiolgy
Department at SDSU, and the USDA-ARS North Central Agricultural Research Laboratory.
Figure 1. Soil health indicators in plots prior to cover crop treatment (RYE) and no-cover crop treatment (CONTROL). A) Short term mineralizable C was measured using soil burst test at 72hours and B) Permanganate oxidizable C measured using POXC assay. C) β-glucosidase extracellular enzyme activity assay. D) Total glomalin measurement using autoclaved citric extractable soil protein. E) one week old rye planted in the green house to study the leachate between control and rye treated pots for nutrient retention.
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Statistics associated with cover crop decomposition: > t.test(Oats,Control)
Welch Two Sample t-test data: Oats and Control
t = 1.2754, df = 2.0702, p-value = 0.3266
alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval:
-0.9894413 1.8626410 sample estimates: mean of x mean of y 1.2947443 0.8581445 > t.test(Rye,Control)
Welch Two Sample t-test data: Rye and Control
t = 0.61391, df = 2.0607, p-value = 0.6002
alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval:
-1.313044 1.764699 sample estimates: mean of x mean of y 1.0839720 0.8581445
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