Paper · 2022 · Agronomy

Modelling the Impact of Water Stress during Post-Veraison on Berry Quality of Table Grapes

Abdelmalek Temnani; Pablo Berríos; María R. Conesa; et al.

5
claims
10
verbatim quotes
10
citations
3
research areas
✓
Open access · cc-by

Abstract

The aims of this work were modelling the effect of water stress intensity during post-veraison on table grape quality and yield, as well as predicting berry quality at harvest using a machine learning algorithm. The dataset was obtained by applying different irrigation regimes in two commercial table grape vineyards during seven growing seasons. From these data, it was possible to train and validate the predictive models over a wide range of values for the independent (water stress intensity and fruit load) and dependent (firmness and berry color) variables. The supervised learning algorithm Gaussian Process Regression allowed us to predict the variables with high accuracy. It was also determined that a reduction in irrigation of up to 40% during post-veraison, compared to vines without water limitations, and the accumulation of the water stress integral of up to 30 MPa per day, linearly increase the irrigation water use efficiency (IWUE) and promote higher berry color and firmness. The severe water scarcity and the increasing uncertainty about the irrigation water availability for the season that farmers are facing highlight the advantage of incorporating these validated techniques into agricultural decision making, as they allow for the planning of cultural practices and criteria to increase the IWUE and crop sustainability.

Abstract from the paper’s OpenAlex record; open copy licensed cc-by. Read at the source ↗

The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.

Claims 5

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Gaussian Process Regression predicted berry quality variables of table grapes with high accuracy.

Taxon
Grapest0
Outcome
accuracye0
Value
high accuracye0

Verbatim

e0

“The supervised learning algorithm Gaussian Process Regression allowed us to predict the variables with high accuracy”

✓ located verbatim in the source · abstract, characters 565–681 · show in text ↑
t0

“Table Grapes”

✓ located verbatim in the source · title, characters 78–90 · show in text ↑
Intervention effectobservedoriginal resultpositivemeasured

Claim · model-written summary

Reducing irrigation by up to 40% during post-veraison linearly increased irrigation water use efficiency in table grapes compared with vines without water limitations.

Taxon
Grapest0
Treatment
a reduction in irrigation of up to 40% during post-veraisone0
Outcome
irrigation water use efficiency (IWUE)e0
Direction
increasee0
Comparator
vines without water limitationse0

Verbatim

e0

“a reduction in irrigation of up to 40% during post-veraison, compared to vines without water limitations, and the accumulation of the water stress integral of up to 30 MPa per day, linearly increase the irrigation water use efficiency (IWUE) and promote higher berry color and firmness”

✓ located verbatim in the source · abstract, characters 711–996 · show in text ↑
t0

“Table Grapes”

✓ located verbatim in the source · title, characters 78–90 · show in text ↑
Intervention effectobservedoriginal resultpositivemeasured

Claim · model-written summary

Reducing irrigation by up to 40% during post-veraison promoted higher berry color and firmness in table grapes compared with vines without water limitations.

Taxon
Grapest0
Treatment
a reduction in irrigation of up to 40% during post-veraisone0
Outcome
berry color and firmnesse0
Direction
highere0
Comparator
vines without water limitationse0

Verbatim

e0

“a reduction in irrigation of up to 40% during post-veraison, compared to vines without water limitations, and the accumulation of the water stress integral of up to 30 MPa per day, linearly increase the irrigation water use efficiency (IWUE) and promote higher berry color and firmness”

✓ located verbatim in the source · abstract, characters 711–996 · show in text ↑
t0

“Table Grapes”

✓ located verbatim in the source · title, characters 78–90 · show in text ↑
Intervention effectobservedoriginal resultpositivemeasured

Claim · model-written summary

Accumulation of a water stress integral of up to 30 MPa per day linearly increased irrigation water use efficiency in table grapes.

Taxon
Grapest0
Treatment
the accumulation of the water stress integral of up to 30 MPa per daye0
Outcome
irrigation water use efficiency (IWUE)e0
Direction
increasee0
Comparator
vines without water limitationse0

Verbatim

e0

“a reduction in irrigation of up to 40% during post-veraison, compared to vines without water limitations, and the accumulation of the water stress integral of up to 30 MPa per day, linearly increase the irrigation water use efficiency (IWUE) and promote higher berry color and firmness”

✓ located verbatim in the source · abstract, characters 711–996 · show in text ↑
t0

“Table Grapes”

✓ located verbatim in the source · title, characters 78–90 · show in text ↑
Intervention effectobservedoriginal resultpositivemeasured

Claim · model-written summary

Accumulation of a water stress integral of up to 30 MPa per day promoted higher berry color and firmness in table grapes.

Taxon
Grapest0
Treatment
the accumulation of the water stress integral of up to 30 MPa per daye0
Outcome
berry color and firmnesse0
Direction
highere0
Comparator
vines without water limitationse0

Verbatim

e0

“a reduction in irrigation of up to 40% during post-veraison, compared to vines without water limitations, and the accumulation of the water stress integral of up to 30 MPa per day, linearly increase the irrigation water use efficiency (IWUE) and promote higher berry color and firmness”

✓ located verbatim in the source · abstract, characters 711–996 · show in text ↑
t0

“Table Grapes”

✓ located verbatim in the source · title, characters 78–90 · show in text ↑

drought · physiology: water · VitisResults differ

26 papers: 12 positive, 14 negative or no effect

11 papers in the same direction as this paper · 14 in the opposite direction

  1. negative
  2. negative
  3. negative

22 papers more in this group

See all 26 papers →

irrigation · quality: postharvest · VitisPositive and negative results

9 papers: 7 positive, 2 negative or no effect

6 papers in the same direction as this paper · 2 in the opposite direction

  1. negative
  2. no effect
  3. positive

5 papers more in this group

See all 9 papers →

irrigation · physiology: water · VitisPositive and negative results

47 papers: 40 positive, 7 negative or no effect

39 papers in the same direction as this paper · 6 in the opposite direction · 1 reporting no difference from an alternative

  1. no effect
  2. negative
  3. negative

43 papers more in this group

See all 47 papers →

drought · quality: postharvest · VitisResults agree

4 papers: 4 positive, 0 negative or no effect

3 papers in the same direction as this paper

  1. positive
  2. positive
  3. positive
See all 4 papers →

Claims are grouped by organism, treatment and what was measured or targeted. A paper counts as positive when any of its claims in the group is positive.