Computational Canopy Models For Precision Measurement And Adaptive Management Of Grapevine Performance
| dc.contributor.author | Meyers, James | en_US |
| dc.contributor.chair | Vanden Heuvel, Justine E. | en_US |
| dc.contributor.committeeMember | Wilcox, Wayne Frank | en_US |
| dc.contributor.committeeMember | Sacks, Gavin Lavi | en_US |
| dc.contributor.committeeMember | Van Es, Harold Mathijs | en_US |
| dc.date.accessioned | 2013-07-23T18:23:41Z | |
| dc.date.available | 2016-06-01T06:15:50Z | |
| dc.date.issued | 2011-01-31 | en_US |
| dc.description.abstract | Effective control of winegrape fruit quality requires the simultaneous consideration of multiple response models including: the relationship between the chemical profile of harvested fruit and the organoleptic qualities of a finished wine; a mechanistic understanding of key flavor and aroma compound biosynthesis; and the role of physical vineyard parameters in these biosynthetic processes. Any attempt to predictably influence the performance of a winegrape cropping system, with respect to flavor and aroma, requires the ability to both measure the relevant physical parameters of that system and to accurately manipulate them to achieve a deliberate and quantitative response. Although the sub-discipline of precision viticulture has established that a quantitative understanding of plot-scale spatial variability can guide cultural inputs toward plot-scale consistency, the existence and small-scale spatial patterns and their effect on precision management have not been extensively studied. The experiments presented here were designed to: 1) improve the precision and increase the spatial resolution of commonly used viticultural research methods with the goal of identifying, characterizing and quantifying small-scale spatial patterns in fruiting-zone of winegrape canopies; 2) explore the impact of small-scale spatial structure on the efficacy of common plot-level cultural inputs; 3) develop methods for optimizing vineyard research and commercial production operations within known parametric spatial patterns at multiple scales; and, 4) explore the potential application of these methods in the control of a specific sunlight-sensitive compound vital to the organoleptic qualities of Riesling wine. The development and application of new computational methods for managing both the data volume of high-resolution models and the combinatorial complexities of multi-objective vineyard optimization, resulted in: new quantitative metrics for describing fruit-zone sunlight regimes; the discovery and quantification of small-scale culturally-induced microclimatic spatial patterns; the discovery that small-scale spatial patterns can negatively impact the efficacy of plotscale cultural inputs; and an enhanced understanding of the relationship between canopy microclimatic variability and concentrations of C13-norisoprenoids in Riesling grapes. To date, the software tools developed within the scope of dissertation have been adopted by researchers and winegrape growers in a dozen countries and 14 U.S. states for use in the study and optimization of crop performance and fruit metabolite profiles. | en_US |
| dc.identifier.other | bibid: 8213842 | |
| dc.identifier.uri | https://hdl.handle.net/1813/33547 | |
| dc.language.iso | en_US | en_US |
| dc.subject | light interception | en_US |
| dc.subject | canopy management | en_US |
| dc.subject | sampling strategies | en_US |
| dc.subject | heurustics | en_US |
| dc.subject | Riesling | en_US |
| dc.subject | norisprenoids | en_US |
| dc.title | Computational Canopy Models For Precision Measurement And Adaptive Management Of Grapevine Performance | en_US |
| dc.type | dissertation or thesis | en_US |
| thesis.degree.discipline | Horticultural Biology | |
| thesis.degree.grantor | Cornell University | en_US |
| thesis.degree.level | Doctor of Philosophy | |
| thesis.degree.name | Ph. D., Horticultural Biology |
Files
Original bundle
1 - 1 of 1