Predicting Net Returns of Organic and Conventional Strawberry Following Soil Disinfestation with Steam or Steam Plus Additives

Pre-plant methods for managing soil-borne pests and diseases are an important priority for many agricultural production systems. This study investigates whether the application of steam is an economically sustainable pre-plant soil disinfestation technique for organic and conventional strawberry (&l...

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Main Authors: Aleksandr Michuda, Rachael E. Goodhue, Mark Hoffmann, Steven A. Fennimore
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Agronomy
Subjects:
Online Access:https://www.mdpi.com/2073-4395/11/1/149
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spelling doaj-a84af6b220774d058904fc32333001312021-04-02T18:34:18ZengMDPI AGAgronomy2073-43952021-01-011114914910.3390/agronomy11010149Predicting Net Returns of Organic and Conventional Strawberry Following Soil Disinfestation with Steam or Steam Plus AdditivesAleksandr Michuda0Rachael E. Goodhue1Mark Hoffmann2Steven A. Fennimore3Department of Agricultural and Resource Economics, University of California, Davis, CA 95616, USADepartment of Agricultural and Resource Economics, University of California, Davis, CA 95616, USADepartment of Horticultural Science, North Carolina State University, Raleigh, NC 27695, USADepartment of Plant Sciences, University of California, Davis, CA 95616, USAPre-plant methods for managing soil-borne pests and diseases are an important priority for many agricultural production systems. This study investigates whether the application of steam is an economically sustainable pre-plant soil disinfestation technique for organic and conventional strawberry (<i>Fragaria ananassa</i>) production in California’s Central Coast region. We analyze net returns from field trials using steam and steam + mustard seed meal (MSM) as pre-plant soil disinfestation treatments. ANOVA tests identify statistically significant differences in net revenues by treatment and trial. Multivariate regressions estimate the magnitude of these effects. Predictive polynomial models identify relationships between net returns and two treatment characteristics: maximum temperature (°C) and time at ≥60 °C (minutes). For organic production, net returns are statistically similar for the steam and steam + MSM treatments. For conventional production, the steam + MSM treatment has significantly higher net returns than the steam treatment. Cross-validated polynomial models outperform the sample mean for prediction of net returns, except for the steam + MSM treatment in conventional production. The optimal degree of the polynomial ranges from 1–4 degrees, depending on the production system and treatment. Results from two of three organic models suggest that maximum soil temperatures of 62–63 °C achieved for 41–44 min maximizes net returns and may be a basis for further experiments.https://www.mdpi.com/2073-4395/11/1/149strawberrysteameconomic feasibility of steam for soil disinfestationpartial budget analysismachine learningallyl isothiocyanate
collection DOAJ
language English
format Article
sources DOAJ
author Aleksandr Michuda
Rachael E. Goodhue
Mark Hoffmann
Steven A. Fennimore
spellingShingle Aleksandr Michuda
Rachael E. Goodhue
Mark Hoffmann
Steven A. Fennimore
Predicting Net Returns of Organic and Conventional Strawberry Following Soil Disinfestation with Steam or Steam Plus Additives
Agronomy
strawberry
steam
economic feasibility of steam for soil disinfestation
partial budget analysis
machine learning
allyl isothiocyanate
author_facet Aleksandr Michuda
Rachael E. Goodhue
Mark Hoffmann
Steven A. Fennimore
author_sort Aleksandr Michuda
title Predicting Net Returns of Organic and Conventional Strawberry Following Soil Disinfestation with Steam or Steam Plus Additives
title_short Predicting Net Returns of Organic and Conventional Strawberry Following Soil Disinfestation with Steam or Steam Plus Additives
title_full Predicting Net Returns of Organic and Conventional Strawberry Following Soil Disinfestation with Steam or Steam Plus Additives
title_fullStr Predicting Net Returns of Organic and Conventional Strawberry Following Soil Disinfestation with Steam or Steam Plus Additives
title_full_unstemmed Predicting Net Returns of Organic and Conventional Strawberry Following Soil Disinfestation with Steam or Steam Plus Additives
title_sort predicting net returns of organic and conventional strawberry following soil disinfestation with steam or steam plus additives
publisher MDPI AG
series Agronomy
issn 2073-4395
publishDate 2021-01-01
description Pre-plant methods for managing soil-borne pests and diseases are an important priority for many agricultural production systems. This study investigates whether the application of steam is an economically sustainable pre-plant soil disinfestation technique for organic and conventional strawberry (<i>Fragaria ananassa</i>) production in California’s Central Coast region. We analyze net returns from field trials using steam and steam + mustard seed meal (MSM) as pre-plant soil disinfestation treatments. ANOVA tests identify statistically significant differences in net revenues by treatment and trial. Multivariate regressions estimate the magnitude of these effects. Predictive polynomial models identify relationships between net returns and two treatment characteristics: maximum temperature (°C) and time at ≥60 °C (minutes). For organic production, net returns are statistically similar for the steam and steam + MSM treatments. For conventional production, the steam + MSM treatment has significantly higher net returns than the steam treatment. Cross-validated polynomial models outperform the sample mean for prediction of net returns, except for the steam + MSM treatment in conventional production. The optimal degree of the polynomial ranges from 1–4 degrees, depending on the production system and treatment. Results from two of three organic models suggest that maximum soil temperatures of 62–63 °C achieved for 41–44 min maximizes net returns and may be a basis for further experiments.
topic strawberry
steam
economic feasibility of steam for soil disinfestation
partial budget analysis
machine learning
allyl isothiocyanate
url https://www.mdpi.com/2073-4395/11/1/149
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