From weeds to natural enemies: Implications of weed cultivation and bio-pesticides for organic onion production
Data files
Apr 02, 2024 version files 13.12 KB
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2019weedyielddisdr.csv
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onion19datd.csv
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onion20datd.csv
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README.md
Abstract
Weed management is challenging for vegetable crops highly sensitive to weed competition, such as onions. Thrips (Thysanoptera: Thripidae) are major insect pests of onion, causing damage through feeding, and vector bacterial pathogens causing rot. Both thrips and their associated pathogens are known to survive on many weed species in onion growing regions. Combining weeding with bio-pesticides may synergistically manage thrips and disease by reducing disease prevalence and indirectly increasing onion yield. However, disturbances from weeding may negatively impact natural enemies. We estimate the effects of organic weed management and bio-pesticides on weed density, thrips and natural enemy activity, disease severity, and yield. The experiment was a randomized complete block design, with four replications of each weeding (control, tine-weeded 2x, tine-weeded 4x, and hand-weeded) and bio-pesticide (control, OxiDate 2.0, Serenade) combination. Arthropods were monitored using yellow sticky cards, and weed counts, marketable yield, and bulb rot prevalence were estimated. Hand-weeding resulted in the lowest weed density and thrips abundance. Additionally, hand-weeding produced 9x higher yield compared to all other treatments. Significant interactions were observed between tine-weeding and bio-pesticide treatments. Natural enemy abundance was slightly negatively impacted by weeding, dependent on year. DNA metabarcoding results show high parasitoid diversity in onion systems and strong reads for multiple genera containing important known biological control agents. Our study suggests hand-weeding is necessary in the southeast for maximum onion yield. Future research should focus on exploring the impact of management on natural enemy communities in onion systems at a large scale.
README: From weeds to natural enemies: implications of weed cultivation and bio-pesticides for organic onion production
https://doi.org/10.5061/dryad.q2bvq83st
Description of the data and file structure
Three datasets are provided in in relation to the manuscript: Two datasets for overall data for 2019/2020: 'onion19.dat.csv' for data collected in 2019, and 'onion20.dat.csv' for 2020. The third dataset is for specific yield data for 2019: '2019weedyielddis2.csv'
-Columns present the following are represented in the onion#.dat.csv files:
plot- plot number
year-year of study
cultivation- cultivation treatment as specified in the manuscript
bactericide - bactericide treatment as specified in the manuscript
onS,LSC, HT, CEP,WR= weed categories sampled as specified in the manuscript
medium, jumbo, colossal= mass of sizes of onions by plot, then later this was converted to kg/ha
Ncenterrrot,Nsrskin=scoring for disease observed, and TotOn = total number of onions scored for disease
Natural enemy predators data columns = counts of natural enemies and then total
Geocoridae | Anthocoridae | Carabidae | Staphylinidae | Syrphidae | Spider | Coccinellidae | Predators |
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PW=parasitoid wasps total
thrips = counts of thrips
-Columns present the following are represented in the '2019weedyieddis2.csv':
plot- plot number
block-grouping of plots and treatments in design
year-year of study
cultivation- cultivation treatment as specified in the manuscript
bactericide - bactericide treatment as specified in the manuscript
medium-kilograms of medium sized onions in plot
jumbo-kilograms of jumbo sized onions in plot
yieldtot-total yield of both onion sized combined within plots
kghamed-kg/ha of medium sized onions estimated to scaled up to hectares
kghajum-kg/ha of jumbo sized onions estimated to scaled up to hectares