Quantifying the seasonal variations in grapevine yield components based on pre- and post-flowering weather conditions
Seasonal differences in weather conditions cause marked variation in grapevine yield. However, quantitative relationships between various yield components and climatic factors at field scales are still lacking. By using a long-term field trial, we quantified the correlation between weather condition...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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International Viticulture and Enology Society
2020-04-01
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| Series: | OENO One |
| Subjects: | |
| Online Access: | https://oeno-one.eu/article/view/2926 |
| _version_ | 1798028151179182080 |
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| author | Junqi Zhu Rémi Fraysse Michael C.T. Trought Victoria Raw Linlin Yang Marc Greven Damian Martin Rob Agnew |
| author_facet | Junqi Zhu Rémi Fraysse Michael C.T. Trought Victoria Raw Linlin Yang Marc Greven Damian Martin Rob Agnew |
| author_sort | Junqi Zhu |
| collection | DOAJ |
| description | Seasonal differences in weather conditions cause marked variation in grapevine yield. However, quantitative relationships between various yield components and climatic factors at field scales are still lacking. By using a long-term field trial, we quantified the correlation between weather conditions during the key development stages and the yield components of Vitis vinifera L. Sauvignon blanc growing under cool-climate conditions. A long-term phenology and yield monitoring trial using both two-cane and four-cane trained vertically shoot positioned (VSP) Sauvignon blanc vines was established in four vineyards in Marlborough, New Zealand in 2004. Phenology, bunch number, berry mass, yield and meteorology records were collated. A multivariable mixed linear model was used to assess the relationship between various yield components and weather conditions. The critical periods for each yield component and weather factor were optimised based on the maximum likelihood returned from the mixed linear model. The optimised critical periods of temperature for all yield components occurred mainly before 50 % flowering either in the previous season (during inflorescence initiation) and the current season, indicating the importance of the pre-flowering period on yield formation. Out of all weather factors, maximum daily temperature had the largest effect on bunch number and overall yield and strongly influenced berry number and bunch mass. Rainfall near flowering time had a negative effect on berry mass and bunch mass, but post-flowering rainfall had a strong positive effect. The statistical model explained 60 to 85 percent of the seasonal variations in bunch number, berry number, berry and bunch mass and yield per vine. |
| first_indexed | 2024-04-11T19:04:19Z |
| format | Article |
| id | doaj.art-a0487cb49c364662829b9ac2a65ae0a3 |
| institution | Directory Open Access Journal |
| issn | 2494-1271 |
| language | English |
| last_indexed | 2024-04-11T19:04:19Z |
| publishDate | 2020-04-01 |
| publisher | International Viticulture and Enology Society |
| record_format | Article |
| series | OENO One |
| spelling | doaj.art-a0487cb49c364662829b9ac2a65ae0a32022-12-22T04:07:51ZengInternational Viticulture and Enology SocietyOENO One2494-12712020-04-0154210.20870/oeno-one.2020.54.2.2926Quantifying the seasonal variations in grapevine yield components based on pre- and post-flowering weather conditionsJunqi Zhu0Rémi Fraysse1Michael C.T. Trought2Victoria Raw3Linlin Yang4Marc Greven5Damian Martin6Rob Agnew7The New Zealand Institute for Plant & Food Research Ltd, Marlborough Research Centre, PO Box 845, Blenheim 7240Montpellier SupAgro, 2 Place Pierre Viala, 34060 MontpellierThe New Zealand Institute for Plant & Food Research Ltd, Marlborough Research Centre, PO Box 845, Blenheim 7240The New Zealand Institute for Plant & Food Research Ltd, Marlborough Research Centre, PO Box 845, Blenheim 7240The New Zealand Institute for Plant & Food Research Ltd, Marlborough Research Centre, PO Box 845, Blenheim 7240The New Zealand Institute for Plant & Food Research Ltd, Marlborough Research Centre, PO Box 845, Blenheim 7240The New Zealand Institute for Plant & Food Research Ltd, Marlborough Research Centre, PO Box 845, Blenheim 7240The New Zealand Institute for Plant & Food Research Ltd, Marlborough Research Centre, PO Box 845, Blenheim 7240Seasonal differences in weather conditions cause marked variation in grapevine yield. However, quantitative relationships between various yield components and climatic factors at field scales are still lacking. By using a long-term field trial, we quantified the correlation between weather conditions during the key development stages and the yield components of Vitis vinifera L. Sauvignon blanc growing under cool-climate conditions. A long-term phenology and yield monitoring trial using both two-cane and four-cane trained vertically shoot positioned (VSP) Sauvignon blanc vines was established in four vineyards in Marlborough, New Zealand in 2004. Phenology, bunch number, berry mass, yield and meteorology records were collated. A multivariable mixed linear model was used to assess the relationship between various yield components and weather conditions. The critical periods for each yield component and weather factor were optimised based on the maximum likelihood returned from the mixed linear model. The optimised critical periods of temperature for all yield components occurred mainly before 50 % flowering either in the previous season (during inflorescence initiation) and the current season, indicating the importance of the pre-flowering period on yield formation. Out of all weather factors, maximum daily temperature had the largest effect on bunch number and overall yield and strongly influenced berry number and bunch mass. Rainfall near flowering time had a negative effect on berry mass and bunch mass, but post-flowering rainfall had a strong positive effect. The statistical model explained 60 to 85 percent of the seasonal variations in bunch number, berry number, berry and bunch mass and yield per vine.https://oeno-one.eu/article/view/2926grapevine yieldbunch numberberry numberberry massseasonal variations |
| spellingShingle | Junqi Zhu Rémi Fraysse Michael C.T. Trought Victoria Raw Linlin Yang Marc Greven Damian Martin Rob Agnew Quantifying the seasonal variations in grapevine yield components based on pre- and post-flowering weather conditions OENO One grapevine yield bunch number berry number berry mass seasonal variations |
| title | Quantifying the seasonal variations in grapevine yield components based on pre- and post-flowering weather conditions |
| title_full | Quantifying the seasonal variations in grapevine yield components based on pre- and post-flowering weather conditions |
| title_fullStr | Quantifying the seasonal variations in grapevine yield components based on pre- and post-flowering weather conditions |
| title_full_unstemmed | Quantifying the seasonal variations in grapevine yield components based on pre- and post-flowering weather conditions |
| title_short | Quantifying the seasonal variations in grapevine yield components based on pre- and post-flowering weather conditions |
| title_sort | quantifying the seasonal variations in grapevine yield components based on pre and post flowering weather conditions |
| topic | grapevine yield bunch number berry number berry mass seasonal variations |
| url | https://oeno-one.eu/article/view/2926 |
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