Abstract
Understanding spatial and temporal patterns in grapevine growth is crucial for optimizing vineyard management and improving yield and quality. This study evaluated the use of satellite remote sensing to assess spatial and temporal patterns in grapevine vigor and yield in a commercial vineyard in Terry County, Texas. Grapevine vigor was evaluated using measurements of cane length, cane diameter, and pruning weight. Yield and yield components were assessed as grape yield, clusters per vine, cluster weight, and berry weight. Using vegetation indices (VIs) derived from high-resolution PlanetScope (3 m) and moderate-resolution Sentinel-2 (10 m) satellite imagery, we assessed the spatial and temporal variability in vine vigor. The results showed significant variability in grapevine vigor, with high vigor showing greater cane length, pruning weight, and clusters per vine. The spatial autocorrelation analysis revealed significant positive clustering for cane length, pruning weight, and clusters per vine, indicating distinct spatial patterns of vine vigor within the vineyard. In contrast, cane diameter, cluster weight, grape yield, and berry weight showed weak spatial autocorrelation, suggesting minimal spatial dependence across the vineyard. Pruning weight showed the most significant relationship with grape yield, reflecting its role as an integrative indicator of vine growth. Both PlanetScope and Sentinel-2 VIs captured similar phenological patterns and spatial and temporal dynamics of grapevines. However, PlanetScope’s high spatial resolution provides greater sensitivity to subtle variability across the vineyard. Both NDVI and EVI showed comparable performance at distinguishing spatial and temporal differences among vine vigor zones, making them more effective at detecting spatial and temporal vine vigor variability during mid-to-late seasons than during early seasons. While VIs showed strong correlations with vine vigor traits during the mid-to-late seasons, their correlations with grape yield and yield components were low, indicating the need for precision management to improve vigor uniformity. These findings highlight the potential of integrating satellite-based remote sensing into precision viticulture to enhance vineyard monitoring and promote sustainable grape production.
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Claims 13
Claim · model-written summary
Grapevine vigor showed significant variability within the commercial vineyard.
- Outcome
- variability in grapevine vigore1
VitisOrganisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“The results showed significant variability in grapevine vigor”
Claim · model-written summary
High-vigor vines showed greater cane length, pruning weight and clusters per vine.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“high vigor showing greater cane length, pruning weight, and clusters per vine”
Claim · model-written summary
Spatial autocorrelation analysis showed significant positive clustering for cane length, pruning weight and clusters per vine.
- Outcome
- positive clustering for cane length, pruning weight, and clusters per vinee1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“significant positive clustering for cane length, pruning weight, and clusters per vine”
Claim · model-written summary
Cane diameter and cluster weight showed weak spatial autocorrelation.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“cane diameter, cluster weight, grape yield, and berry weight showed weak spatial autocorrelation”
Claim · model-written summary
Grape yield and berry weight showed weak spatial autocorrelation.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“cane diameter, cluster weight, grape yield, and berry weight showed weak spatial autocorrelation”
Claim · model-written summary
Pruning weight showed the most significant relationship with grape yield.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“Pruning weight showed the most significant relationship with grape yield”
Claim · model-written summary
PlanetScope and Sentinel-2 vegetation indices captured similar phenological patterns and spatial and temporal dynamics of grapevines.
- Outcome
- similar phenological patterns and spatial and temporal dynamics of grapevinese1
- Direction
- similare1
- Comparator
- Sentinel-2e1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“Both PlanetScope and Sentinel-2 VIs captured similar phenological patterns and spatial and temporal dynamics of grapevines”
Claim · model-written summary
PlanetScope, with its higher spatial resolution, provides greater sensitivity to subtle variability across the vineyard than Sentinel-2.
- Outcome
- sensitivity to subtle variability across the vineyarde1
- Direction
- greatere1
- Comparator
- Sentinel-2e2
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“PlanetScope’s high spatial resolution provides greater sensitivity to subtle variability across the vineyard”
e2“moderate-resolution Sentinel-2 (10 m)”
Claim · model-written summary
NDVI and EVI showed comparable performance at distinguishing spatial and temporal differences among vine vigor zones.
- Outcome
- performance at distinguishing spatial and temporal differences among vine vigor zonese1
- Direction
- comparablee1
- Comparator
- EVIe1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“Both NDVI and EVI showed comparable performance at distinguishing spatial and temporal differences among vine vigor zones”
Claim · model-written summary
NDVI and EVI were more effective at detecting spatial and temporal vine vigor variability during mid-to-late seasons than during early seasons.
- Outcome
- detecting spatial and temporal vine vigor variabilitye1
- Direction
- more effectivee1
- Comparator
- early seasonse1
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“more effective at detecting spatial and temporal vine vigor variability during mid-to-late seasons than during early seasons”
Claim · model-written summary
Vegetation indices showed strong correlations with vine vigor traits during the mid-to-late seasons.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“VIs showed strong correlations with vine vigor traits during the mid-to-late seasons”
Claim · model-written summary
Vegetation index correlations with grape yield and yield components were low.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“their correlations with grape yield and yield components were low”
Claim · model-written summary
The authors conclude that precision management is needed to improve vigor uniformity.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“grapevine”
e1“the need for precision management to improve vigor uniformity”