Profitability of irrigating for corn, cotton, and soybeans under projected drought scenarios in the Southeastern United States
Autor: | Katryn Pasaribu, Lixia He Lambert, Dayton M. Lambert, Burton C. English, Christopher D. Clark, Chad M. Hellwinckel, Christopher N. Boyer, S. Aaron Smith |
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Rok vydání: | 2021 |
Předmět: |
Irrigation
Conventional tillage business.industry 0207 environmental engineering Soil Science Row crop 04 agricultural and veterinary sciences 02 engineering and technology Commodity market Agricultural science Agriculture 040103 agronomy & agriculture Market price 0401 agriculture forestry and fisheries Environmental science 020701 environmental engineering Irrigation management business Agronomy and Crop Science Hectare Water Science and Technology |
Zdroj: | ORCID Microsoft Academic Graph |
ISSN: | 1432-1319 0342-7188 |
Popis: | This study estimates breakeven price distributions for irrigated and non-irrigated corn, cotton, and soybean production in Tennessee under conventional tillage and no-till for three field sizes and two sources of energy for irrigation. The distributions were compared using forecasted prices of corn, cotton, and soybean realized under different climate scenarios. The price simulation focuses on the short-, medium-, and long-term impacts of drought-induced yield reduction on commodity market prices. Electric pump irrigation systems in the southeastern United States have lower energy costs and, thus, a lower breakeven price than diesel-fueled irrigation pumps. A corn producer could obtain a lower breakeven price per kg by irrigating fields of 51–81 hectares. Cotton and soybean producers managing fields of 81 hectares or less could realize lower breakeven prices by not irrigating. Under extended drought conditions during which the market price for corn, soybeans, and cotton are higher, irrigated corn is more likely to be profitable compared to irrigated cotton or soybeans. These results could inform the development of irrigation management plans for row crop producers in the southeastern United States. |
Databáze: | OpenAIRE |
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