Search claims · PlantClaims

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

At harvest, inflorescence and bunch detection error fell slightly to 46%.

Taxon: GrapevineVitist0
Organ / stage: Inflorescences and bunchese1
Outcome: MA%Ee0
Direction: slight decreasee0
Value: 46%e0

Verbatim

e0
“with a slight decrease at harvest (MA%E=46%)”
✓ located verbatim in the source · abstract, characters 1502–1546

e1
“Inflorescences and bunches showed the highest MA%E”
✓ located verbatim in the source · abstract, characters 1396–1446

t0
“Grapevine”
✓ located verbatim in the source · title, characters 0–9

Title

Grapevine yield components detection using image analysis: a case study with the white cultivar ‘Encruzado’

G. Victorino; C.M. Lopes Acta Horticulturae 2021. doi:10.17660/actahortic.2021.1314.22

Other claims from this paper (5)

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Mortality rate was an earlier indicator of decline than yield loss.

Taxon: grapevineVitist0
Outcome: mortality ratee0
Direction: earliere0
Comparator: yield losse0

Verbatim

e0
“mortality rate and the normalised difference vegetation index (NDVI) indicators were shown to be earlier indicators of grapevine decline than yield loss (yield achievement ratio, YAR)”
✓ located verbatim in the source · abstract, characters 1436–1619

t0
“grapevine”
✓ located verbatim in the source · title, characters 23–32

Title

A systemic approach to grapevine decline diagnosed using three key indicators: plant mortality, yield loss and vigour decrease

Anne MEROT; Guillaume Coulouma; Nathalie Smits; et al. OENO One 2023. doi:10.20870/oeno-one.2023.57.1.5575

Other claims from this paper (9)

Association Farmers’ perceptions agreed with field measures of decline.
Observation Vine mortality spread progressively over years.
Association The survey and historical analysis found no direct link between decline and yield loss.
Observation Yield fluctuated annually without systematically declining.
Method / resource NDVI was an earlier indicator of decline than yield loss.
Method / resource Ground based NDVI indicators were proposed for accessible decline diagnosis.
Method / resource An aerial photograph image analysis method was proposed for accessible decline diagnosis.
Association NDVI indicators correlated linearly with yield achievement ratio.
Association NDVI indicators correlated linearly with mortality rate.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

NDVI was an earlier indicator of decline than yield loss.

Taxon: grapevineVitist0
Outcome: normalised difference vegetation index (NDVI) indicatorse0
Direction: earliere0
Comparator: yield losse0

Verbatim

e0
“mortality rate and the normalised difference vegetation index (NDVI) indicators were shown to be earlier indicators of grapevine decline than yield loss (yield achievement ratio, YAR)”
✓ located verbatim in the source · abstract, characters 1436–1619

t0
“grapevine”
✓ located verbatim in the source · title, characters 23–32

Title

A systemic approach to grapevine decline diagnosed using three key indicators: plant mortality, yield loss and vigour decrease

Anne MEROT; Guillaume Coulouma; Nathalie Smits; et al. OENO One 2023. doi:10.20870/oeno-one.2023.57.1.5575

Other claims from this paper (9)

Association Farmers’ perceptions agreed with field measures of decline.
Observation Vine mortality spread progressively over years.
Association The survey and historical analysis found no direct link between decline and yield loss.
Observation Yield fluctuated annually without systematically declining.
Method / resource Mortality rate was an earlier indicator of decline than yield loss.
Method / resource Ground based NDVI indicators were proposed for accessible decline diagnosis.
Method / resource An aerial photograph image analysis method was proposed for accessible decline diagnosis.
Association NDVI indicators correlated linearly with yield achievement ratio.
Association NDVI indicators correlated linearly with mortality rate.

Method / resourceauthor interpretationoriginal resultpositivemeasured

Claim · model-written summary

Machine learning methods can reduce citrus yield-estimation error and field measurement needs, cost and time.

Taxon: citrusCitrust0
Outcome: estimation errore0
Direction: reducee0

Not reportedComparatorValue

Verbatim

e0
“Machine learning techniques were applied to predict yield; these methods can reduce the estimation error as well as decrease the need for in-field measuring, thus reducing both the cost and time of the process”
✓ located verbatim in the source · abstract, characters 602–811

t0
“citrus”
✓ located verbatim in the source · title, characters 34–40

Title

Using regression trees to predict citrus load balancing accuracy and costs

G.R.R. Bóbeda; E.F. Combarro; S. Mazza; et al. International Journal of Computational Intelligence Systems 2018. doi:10.2991/ijcis.2018.25905183

Method / resourceauthor interpretationoriginal resultbasis n/a

Claim · model-written summary

An aerial photograph image analysis method was proposed for accessible decline diagnosis.

Taxon: grapevineVitist0
Outcome: image-analysis methodology using aerial photographse0

Not reportedComparator

Verbatim

e0
“an image-analysis methodology using aerial photographs were proposed as easy-to-obtain indicators of grapevine decline”
✓ located verbatim in the source · abstract, characters 1901–2019

t0
“grapevine”
✓ located verbatim in the source · title, characters 23–32

Title

A systemic approach to grapevine decline diagnosed using three key indicators: plant mortality, yield loss and vigour decrease

Anne MEROT; Guillaume Coulouma; Nathalie Smits; et al. OENO One 2023. doi:10.20870/oeno-one.2023.57.1.5575

Other claims from this paper (9)

Association Farmers’ perceptions agreed with field measures of decline.
Observation Vine mortality spread progressively over years.
Association The survey and historical analysis found no direct link between decline and yield loss.
Observation Yield fluctuated annually without systematically declining.
Method / resource Mortality rate was an earlier indicator of decline than yield loss.
Method / resource NDVI was an earlier indicator of decline than yield loss.
Method / resource Ground based NDVI indicators were proposed for accessible decline diagnosis.
Association NDVI indicators correlated linearly with yield achievement ratio.
Association NDVI indicators correlated linearly with mortality rate.

Method / resourceauthor interpretationoriginal resultbasis n/a

Claim · model-written summary

Ground based NDVI indicators were proposed for accessible decline diagnosis.

Taxon: grapevineVitist0
Outcome: ground-based NDVI indicatorse0
Value: twoe0

Verbatim

e0
“two ground-based NDVI indicators and an image-analysis methodology using aerial photographs were proposed as easy-to-obtain indicators of grapevine decline”
✓ located verbatim in the source · abstract, characters 1864–2019

t0
“grapevine”
✓ located verbatim in the source · title, characters 23–32

Title

A systemic approach to grapevine decline diagnosed using three key indicators: plant mortality, yield loss and vigour decrease

Anne MEROT; Guillaume Coulouma; Nathalie Smits; et al. OENO One 2023. doi:10.20870/oeno-one.2023.57.1.5575

Other claims from this paper (9)

Association Farmers’ perceptions agreed with field measures of decline.
Observation Vine mortality spread progressively over years.
Association The survey and historical analysis found no direct link between decline and yield loss.
Observation Yield fluctuated annually without systematically declining.
Method / resource Mortality rate was an earlier indicator of decline than yield loss.
Method / resource NDVI was an earlier indicator of decline than yield loss.
Method / resource An aerial photograph image analysis method was proposed for accessible decline diagnosis.
Association NDVI indicators correlated linearly with yield achievement ratio.
Association NDVI indicators correlated linearly with mortality rate.

“yield decrease”

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