Location: Weed and Insect Biology Research
Project Number: 3060-21220-033-020-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Jun 1, 2022
End Date: Dec 31, 2025
Objective:
Healthy soils can reduce the levels of fertilizers and herbicides needed to maintain crop productivity, which reduces production costs and is a benefit to the environment. Best management practices for maintaining or improving soil health include no-till, cover cropping, and rotational diversity, which are considered mechanisms for sequestering carbon and reducing nutrient losses, increasing soil aggregate stability and water infiltration, and improving habitat for wildlife and pollinators. Additionally, soil health and agricultural production have also been associated with the soil microbiome, which is part of a living ecosystem including pathogens, bacteria, fungi, viruses and other beneficial organisms. However, knowledge gaps exist regarding how incorporating climate resilient cover crops and forages, such as winter camelina and alfalfa, into rotational cropping systems impacts the soil microbiome, crop yield, and ecosystem services in colder climates.
To evaluate how incorporating a climate resilient annual cover crop (winter camelina) or a forage (alfalfa) into rotational cropping combinations including wheat, early maturity sunflower, soybean, and fallow contribute to crop yield, pathogen and weed pressure, nutrient retention, and other factors associated with soil health in northern agro-ecosystems. Because partial funding for this proposal is linked to the National Predictive Modeling Tools Initiative (NPMTI), this project is also interested in understanding the potential impact cover crops have on soil pathogens – particularly those associated with sunflower (e.g., Sclerotinia and Phomopsis) or other beneficial soil microbes. The objectives of this project are to: 1) determine how rotational multi-cropping combinations including alfalfa, winter camelina, early maturity sunflower, fallow, soybean, and wheat impact crop yield, 2) evaluate seasonal and yearly weed pressure and nutrient retention among the various rotational multi-cropping systems, and 3) determine how incorporating a winter hardy cover/cash crop or forage into rotational multi-cropping systems impacts soil microbial taxa that include pathogens and beneficial microbes and their potential interactions with crop yield, disease and weed pressure, and other ecosystem services.
Approach:
A randomized complete block design with four replicates, conducted over two years (2022-2024) at Hickson and Prosper, North Dakota, will include ten treatments (T1-T10):
T1=Wheat, Cam (FP), EMSF (LP), fallow
T2=Wheat, fallow, EMSF (EP), Cam (FP)
T3=Wheat, fallow, Alf (EP), Alf
T4=EMSF (EP), Alf (FP), Alf, Alf
T5=EMSF (EP), Cam (FP), Alf (FP), Alf
T6=EMSF (EP), Cam (FP), Soy (RP), fallow
T7=EMSF (LP), fallow, Wheat, fallow
T8=Soy, fallow, Wheat, Cam (FP)
T9=fallow, Cam (FP), fallow, Cam (FP)
T10=Alf (EP), Alf, Alf, Alf
Abbreviations: Cam=Camelina, Alf=Alfalfa, EMSF=Early Maturity Sunflower, Soy=Soybean, FP=Fall Planted; LP=Late Planted; EP=Early Planted; RP=Relay Planted.
Obj. 1: Crop yield among treatments will be evaluated using above ground fresh and dry weight biomass and final season seed yields per location/year. Total seed oil, protein content, and fatty acid composition will also be evaluated for EMSF and Cam.
Obj. 2: Evaluation of weed pressure will include stem counts and fresh and dry weight of weeds/m2 by treatment/location/year. Two ¼ m quadrates will be randomly chosen for determining stem counts and above ground biomass. Sub-samples will be harvested at mid-season and full maturity from two inter-plot crop rows, dried, ground to a fine powder and used to analyze crop nutrient retention. Soil nitrate at each location and treatment combination will be determined from soil samples taken in the spring and fall of every year.
Obj. 3: To evaluate the impact of cover crop or forage on soil microbial taxa, soil samples will only be collected from fallow and the rhizosphere of treatments including camelina, alfalfa, and sunflower at each location/year (264 samples total). Soil associated with crop root systems will be collected early- to mid-summer and late-fall and screen-sifted to separate root tissue. DNA will be extracted from soil samples using established protocols for amplification of rDNA using primers (ITS for fungi, 16S for prokaryotic) to conduct amplicon sequencing using Illumina Miseq (528 libraries total). Read trimming, filtering and identification of amplicon sequence variants (ASVs) from amplicon sequence data will be performed using the Dada2 pipeline in R. Taxonomy will be assigned to ASVs within Dada2 through somparisons to the SILVA (for 16S) and UNITE (for ITS) databases. Differences in soil microbiome composition between treatments will be evaluated in R using the phyloseq package. Specifically, the alpha diversity of each microbial community will be performed using Shannon and Simpson indices, with statistical support established with a pairwise wilcox test. Differences in the beta diversity of microbial communities will be assessed by nonmetric multidimensional scaling using Bray-Curtis dissimilarity. Statistical analysis of the microbial community dissimilarities (PERMANOVA) will be determined using the adonis function of the VEGAN package. Differential abundance of microbial taxa that include pathogens and beneficial microbes in response to the treatments will be analyzed using the DeSeq2 package, which will serve as a starting point for validating pathogen or beneficial microbe enrichment or suppression.
