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Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

The temporal for spatial variability assumption is sensitive to interactions at the soil plant atmosphere interface and fails under some circumstances.

Taxon
cropt0
Outcome
the assumptione0
Qualifier
under certain circumstancese0

Not reportedComparatorValue

Verbatim

e0

“the assumption is highly sensitive to specific interactions at the soil-plant-atmosphere interface and, consequently, does not hold under certain circumstances.”

✓ located verbatim in the source · abstract, characters 867–1027
t0

“impact of climate change on crop yield”

✓ located verbatim in the source · abstract, characters 302–340

Title

Issues of Spatial and Temporal Variability in Climate Impact Studies

Gregory J. Carbone The Professional Geographer 1995. doi:10.1111/j.0033-0124.1995.00030.x

Other claims from this paper (1)
Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

Deep learning architectures encountered more challenges in temporal extrapolation of soybean yield, with RRMSE 51% across years.

Taxon
soybeanGlycine maxe0
Outcome
RRMSEe2
Value
51 %e2
Qualifier
temporal extrapolatione2

Verbatim

e0

“predicting within-field soybean yields”

✓ located verbatim in the source · abstract, characters 208–246
e2

“The DL architectures encountered more challenges with temporal extrapolation (RRMSE 51 % in across-years)”

✓ located verbatim in the source · abstract, characters 1000–1105

Title

Predicting spatial and temporal variability in soybean yield using deep learning and open source data

Deborah V. Gaso; Laura Elena Cue La Rosa; Laila A. Puntel; et al. European Journal of Agronomy 2025. doi:10.1016/j.eja.2024.127498

Other claims from this paper (5)
Method / resourceobservedoriginal resultnegativesimulated

Claim · model-written summary

Temporal disaggregation increased overfitting risk with sample sizes below 300.

Taxon
maizeZea mayse0
Outcome
risk of overfittinge1
Direction
increasese1
Value
below 300e1

Verbatim

e0

“maize yields”

✓ located verbatim in the source · abstract, characters 436–448
e1

“with sample sizes below 300, temporal disaggregation increases the risk of overfitting”

✓ located verbatim in the source · abstract, characters 757–843

Title

Predicting Crop Yield Responses to Temperature and Precipitation Variability Using Statistical Models in Nellore District, Andhra Pradesh, India

G. Varalakshmi Advances in Research 2026. doi:10.9734/air/2026/v27i41658

Other claims from this paper (7)
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Grain yield maps from four previous years could only account for 46% of the 1995 grain yield variability.

Outcome
1995 grain yield variabilitye6
Value
46%e6
Qualifier
Grain yield maps for four previous years could only account fore6

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51
e6

“Grain yield maps for four previous years could only account for 46% of the 1995 grain yield variability”

✓ located verbatim in the source · abstract, characters 5786–5889

Title

Spatial and Temporal Stability of Corn Grain Yields

J. A. Lamb; R. H. Dowdy; J. L. Anderson; et al. jpa 1997. doi:10.2134/jpa1997.0410

Other claims from this paper (7)
Associationobservedoriginal resultnegativesignificant (as stated)measured

Claim · model-written summary

Heat episode variability was negatively associated with observed rice grain yield across all subregions.

Outcome
observed grain yielde0
Direction
negativee0
Setting
all subregionse0

Verbatim

e0

“Significant negative ( p < 0.05) impacts of the variability of high‐temperature episodes on the observed grain yield were found in all subregions.”

✓ located verbatim in the source · abstract, characters 1594–1740
t0

“Rice Yield in China”

✓ located verbatim in the source · title, characters 81–100

Title

High‐Temperature Episodes with Spatial‐Temporal Variation Impacted Middle‐Season Rice Yield in China

Xinsu Sun; Zhiwei Long; Guangpeng Song; et al. Agronomy Journal 2018. doi:10.2134/agronj2017.09.0510

Other claims from this paper (6)
Method / resourceauthor interpretationoriginal resultnegativesimulated

Claim · model-written summary

Large-scale simulated yields can have systematic bias at higher temporal or spatial evaluation resolution.

Outcome
large-scale simulationse0
Qualifier
depending on the model and its parameterizatione0
Comparator
higher temporal or spatial resolutione0

Verbatim

e0

“large-scale simulations can be systematically biased when being evaluated at higher temporal or spatial resolution depending on the model and its parameterization.”

✓ located verbatim in the source · abstract, characters 1547–1710

Title

Variability of effects of spatial climate data aggregation on regional yield simulation by crop models

H Hoffmann; G Zhao; LGJ van Bussel; et al. Climate Research 2015. doi:10.3354/cr01326

Other claims from this paper (5)
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Ca and CaPK without manure gave low, unstable yields.

Treatment
no mineral N (Ca and CaPK) and no additional manure supplye0
Outcome
yieldse0
Direction
low and unstablee0

Verbatim

e0

“yields of treatments with no mineral N (Ca and CaPK) and no additional manure supply were low and unstable”

✓ located verbatim in the source · abstract, characters 1546–1652
t0

“Effects of Fertilizers and Manures on Temporal Yield Variability of Winter Rye”

✓ located verbatim in the source · title, characters 0–78

Title

Effects of Fertilizers and Manures on Temporal Yield Variability of Winter Rye

Marcin Studnicki; Janna Macholdt; Andy Macdonald; et al. Agronomy 2021. doi:10.3390/agronomy11030519

Other claims from this paper (4)
Intervention effectobservedoriginal resultnegativemeasured

Claim · model-written summary

Organic input increased rye yield variability under CaNPK and NPK.

Treatment
additional organic inpute0
Outcome
variable rye yieldse0
Direction
more variablee0
Qualifier
CaNPK and NPKe0
Comparator
those with no additional manuree0

Verbatim

e0

“additional organic input led to more variable rye yields in already ‘optimal’ treatments including mineral N (CaNPK and NPK), compared to those with no additional manure”

✓ located verbatim in the source · abstract, characters 1236–1405

Title

Effects of Fertilizers and Manures on Temporal Yield Variability of Winter Rye

Marcin Studnicki; Janna Macholdt; Andy Macdonald; et al. Agronomy 2021. doi:10.3390/agronomy11030519

Other claims from this paper (4)
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Previous-year grain yields accounted for only 4 to 42% of the grain yield variability in a given year.

Outcome
grain yield variabilitye5
Value
4 to 42%e5
Qualifier
accounted for by a knowledge of the grain yields from a previous yeare5

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51
e5

“Only 4 to 42% of the grain yield variability for a given year is accounted for by a knowledge of the grain yields from a previous year”

✓ located verbatim in the source · abstract, characters 1585–1719

Title

Spatial and Temporal Stability of Corn Grain Yields

J. A. Lamb; R. H. Dowdy; J. L. Anderson; et al. jpa 1997. doi:10.2134/jpa1997.0410

Other claims from this paper (7)
Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Discarding the lowest and highest yielding years, 32% of the 1995 yield variability could be predicted from previous yields.

Outcome
1995 yield variabilitye7
Value
32%e7
Qualifier
discard the lowest yielding year (1993) and the highest yielding year (1991)e7

Verbatim

t0

“Corn Grain Yields”

✓ located verbatim in the source · title, characters 34–51
e7

“Using the strategy to discard the lowest yielding year (1993) and the highest yielding year (1991), 32% of the 1995 yield variability could be predicted from yields in previous years”

✓ located verbatim in the source · abstract, characters 5891–6073

Title

Spatial and Temporal Stability of Corn Grain Yields

J. A. Lamb; R. H. Dowdy; J. L. Anderson; et al. jpa 1997. doi:10.2134/jpa1997.0410

Other claims from this paper (7)

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