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ORCID

https://orcid.org/0000-0002-5438-7250

Document Type

Open Access Thesis

Embargo Period

4-26-2020

Degree Program

Plant Biology

Degree Type

Master of Science (M.S.)

Year Degree Awarded

2020

Month Degree Awarded

May

Abstract

The American Cranberry (Vaccinium macrocarpon Ait.) represents a vital sector of the economy of southeastern Massachusetts. Due to the hydrogeological and edaphic characteristics of peatlands, variations in soil drainage and soil moisture represent major management challenges for growers in Massachusetts. An emerging trend of upland (mineral soil) cranberry farms planted with new hybrid cultivars has the potential to enhance the profitability and long-term viability of cranberry production in Massachusetts. However, sparse data exist on soil moisture characteristics of peatland and upland cranberry farms. The purpose of this research was to elucidate the differences in soil moisture between upland and peatland cranberry farms, to evaluate the soil temperature-moisture relationship and its use for inferring soil moisture, and to explore the use of unmanned aircraft systems (UAS) as a soil moisture management tool in cranberry agriculture.In this thesis, we found that volumetric soil water content (qv) in upland farms ranged from 5-15%, contrasting with values of 10-40% for peatland farms. In general, soil moisture in upland farms was two times drier and four times more uniform than peatlands farms. Our results suggest that open ditches should be dredged to at least 50 cm to obtain irrigation setpoints of -5 to -2 kPa for Massachusetts cranberry farms. We found that soil temperature and near-surface temperature were accurate predictors of soil moisture but were also strongly dependent on the magnitude of differences between air and water temperature. Soil and near-surface temperatures were also better predictors of moisture in soils with lower vegetation coverage and organic matter content. Near-surface temperature collected with a UAS was consistent with field measurements of qv, suggesting that UAS could be used to assist Massachusetts cranberry farmers by predicting large-scale variation in q v and offering management insights.

First Advisor

Hilary A. Sandler

Second Advisor

Casey Kennedy

Third Advisor

Michelle DaCosta

Fourth Advisor

Peter Jeranyama

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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