Search claims · PlantClaims

Method / resourceobservedoriginal resultnegativeprojected

Claim · model-written summary

The 4M model predicted a considerable future decrease in maize yield safety.

Taxon: maizeZea mayse0
Outcome: yield safetye0
Direction: decreasee0

Not reportedComparatorValue

Verbatim

e0
“4M predicted a considerable decrease of maize yields as well as yield safety for the future.”
✓ located verbatim in the source · abstract, characters 933–1025

Title

USING LONG-TERM FIELD EXPERIMENT DATA TO PREPARE A CROP SIMULATION MODEL FOR CLIMATE IMPACT STUDIES

GY. MICSKEI Applied Ecology and Environmental Research 2016. doi:10.15666/aeer/1403_263280

Other claims from this paper (6)

Method / resource After calibration, the 4M model adequately simulated biomass production differences among fertilizer levels.
Method / resource After calibration, the 4M model adequately simulated long-term biomass production trends and averages.
Method / resource The 4M model underestimated inter-annual yield variability.
Method / resource A new formula was proposed to simulate increased leaf decay under heat and water stress.
Method / resource The 4M model predicted a considerable future decrease in maize yields.
Method / resource Comparison of observed and simulated data suggested two model improvements for projections of environmental stress impacts.

Method / resourceobservedoriginal resultnegativesimulated

Claim · model-written summary

Median ensemble potato yield fell 2% for each 10% rainfall decrease at nonirrigated sites.

Taxon: potatoSolanum tuberosumt0
Outcome: yielde1
Direction: declinede0
Value: 2%e0
Qualifier: for every 10% decrease in rainfall (for nonirrigated sites)e0

Verbatim

e0
“declined 2% for every 10% decrease in rainfall (for nonirrigated sites)”
✓ located verbatim in the source · abstract, characters 1652–1723

e1
“yield increased on average 6% per 100-ppm C”
✓ located verbatim in the source · abstract, characters 1581–1624

t0
“potato”
✓ located verbatim in the source · title, characters 2–8

Title

A potato model intercomparison across varying climates and productivity levels

David H. Fleisher; Bruno Condori; Roberto Quiroz; et al. Global Change Biology 2016. doi:10.1111/gcb.13411

Other claims from this paper (16)

Method / resource The median potato model ensemble replicated observed yield better than any individual model across all locations.
Method / resource Full calibration reduced simulated yield uncertainty from 38% to 20%.
Observation Model uncertainty increased with interannual variability.
Method / resource Predictions for all agronomic variables differed significantly among models.
Method / resource Model uncertainty averaged 15% higher at low input than high input sites.
Method / resource Low versus high input sites differed more in uncertainty for evapotranspiration, nitrogen uptake and water use efficiency than dry matter.
Method / resource At least five partially calibrated models were needed to keep ensemble variability below field variation.
Method / resource At least three fully calibrated models were needed to keep ensemble variability below field variation.
Observation Carbon dioxide change did not influence model variation.
Method / resource Temperature or rainfall departures from historical levels raised yield model variation as much as 41%.
Method / resource Temperature or rainfall departures raised evapotranspiration model variation as much as 23%.
Observation Temperature increases accounted for the most uncertainty among the climate factors.
Method / resource Median ensemble potato yield rose on average 6% per 100 ppm carbon dioxide increase.
Method / resource Median ensemble potato yield fell 4.6% per °C temperature increase.
Method / resource Different representations of light utilization produced significantly different predictions.
Recommendation The authors suggest that ensemble approaches can improve assessments of climate change impacts on potato.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

The polynomial model could not calculate a salinity yield decrease value.

Taxon: vegetables, and ornamentalse1
Outcome: calculation of the salinity yield decrease (SYD) value is not possiblee0
Comparator: polynomial modele0

Not reportedDirection

Verbatim

e0
“The polynomial model has the drawback that calculation of the salinity yield decrease (SYD) value is not possible.”
✓ located verbatim in the source · abstract, characters 676–790

e1
“various vegetables, and ornamentals were grown in a substrate system”
✓ located verbatim in the source · abstract, characters 95–163

Title

Modeling Osmotic Salinity Effects on Yield Characteristics of Substrate-Grown Greenhouse Crops

C. Sonneveld; A. L. van den Bos; W. Voogt Journal of Plant Nutrition 2004. doi:10.1081/lpla-200030053

Other claims from this paper (8)

Method / resource Polynomial and exponential models generally had higher correlation coefficients than the piecewise linear model.
Method / resource All tested models produced salinity threshold estimates.
Method / resource The polynomial model estimated an average EC threshold of 2.4 dS m−1.
Method / resource The exponential model estimated an average EC threshold of 2.1 dS m−1.
Method / resource The piecewise linear model estimated an average EC threshold of 2.2 dS m−1.
Method / resource The exponential equation gave the closest relationship between root environment EC and crop yield characteristics.
Method / resource Fifth order polynomial equations had equal or higher correlation coefficients but were sensitive to observation placement.
Method / resource The Maas and Hoffman model could reasonably estimate salinity parameters when observations were insufficient for exponential fitting.

Method / resourceobservedoriginal resultnegativeprojected

Claim · model-written summary

EPIC projected a corn yield decrease under the coarse scenario.

Taxon: cornZea mays subsp. mayst0
Direction: decreasee0
Comparator: coarse scenarioe0

Not reportedOutcomeValue

Verbatim

e0
“EPIC simulated a decrease for the coarse scenario but no change for the fine scale scenario”
✓ located verbatim in the source · abstract, characters 568–659

t0
“for wheat and corn”
✓ located verbatim in the source · abstract, characters 61–79

Title

Comparative responses of EPIC and CERES crop models to high and low spatial resolution climate change scenarios

L. O. Mearns; T. Mavromatis; E. Tsvetsinskaya; et al. Journal of Geophysical Research Atmospheres 1999. doi:10.1029/1998jd200061

Other claims from this paper (5)

Method / resource CERES projected moderate corn yield decreases under both scenarios.
Method / resource EPIC projected no change in corn yield under the fine scale scenario.
Method / resource The models also differed in simulated wheat yields.
Mechanism Model differences in yield arose from contrasting formation of final yield despite similar potential biomass simulation.
Method / resource Crop model type was identified as an uncertainty in impact assessment alongside climate scenario spatial resolution.

Method / resourceobservedoriginal resultnegativesimulated

Claim · model-written summary

No nitrogen application decreased simulated yield by 8%.

Treatment: no N is appliede0
Outcome: yield decreasee0
Direction: decreasee0
Value: 8%e0

Not reportedTaxon

Verbatim

e0
“8% yield decrease when no N is applied”
✓ located verbatim in the source · abstract, characters 3036–3074

Title

Targeting the right input data to improve crop modeling at global level : [ePoster abstract Gc13B-1085]

Myriam Adam; Richard Robertson; Sika Gbegbelegbe; et al. Agritrop (Cirad) 2012

Other claims from this paper (6)

Method / resource Null soil carbon and nitrogen decreased simulated wheat yields by 45%.
Method / resource Twice the reference soil carbon and nitrogen increased simulated wheat yields by 15%.
Method / resource Initial soil water at wilting point yielded 0% increase in simulated yield.
Method / resource Initial soil water at field capacity yielded 6% increase in simulated yield.
Method / resource Nitrogen application of 150 kg.ha-1 increased simulated yield by 9%.
Method / resource Model yield was more sensitive to nitrogen application than initial soil carbon and nitrogen in Vietnam, Thailand and Japan.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

Selecting for minimal yield decrease under stress failed to identify the best genotypes in this context.

Taxon: barleyHordeum vulgaree1
Outcome: identify the best genotypese0
Direction: failede0
Comparator: favorable conditionse0

Verbatim

e0
“a selection based on minimum yield decrease under stress with respect to favorable conditions failed to identify the best genotypes.”
✓ located verbatim in the source · abstract, characters 1535–1667

e1
“barley ( Hordeum vulgare L.)”
✓ located verbatim in the source · abstract, characters 131–159

Title

Use of a Water Stress Index to Identify Barley Genotypes Adapted to Rainfed and Irrigated Conditions

F. Rizza; F. W. Badeck; L. Cattivelli; et al. Crop Science 2004. doi:10.2135/cropsci2004.2127

Other claims from this paper (4)

Method / resourceobservedoriginal resultnegativeprojected

Claim · model-written summary

The 4M model predicted a considerable future decrease in maize yields.

Taxon: maizeZea mayse0
Outcome: maize yieldse0
Direction: decreasee0

Not reportedComparatorValue

Verbatim

e0
“4M predicted a considerable decrease of maize yields as well as yield safety for the future.”
✓ located verbatim in the source · abstract, characters 933–1025

Title

USING LONG-TERM FIELD EXPERIMENT DATA TO PREPARE A CROP SIMULATION MODEL FOR CLIMATE IMPACT STUDIES

GY. MICSKEI Applied Ecology and Environmental Research 2016. doi:10.15666/aeer/1403_263280

Other claims from this paper (6)

Method / resource After calibration, the 4M model adequately simulated biomass production differences among fertilizer levels.
Method / resource After calibration, the 4M model adequately simulated long-term biomass production trends and averages.
Method / resource The 4M model underestimated inter-annual yield variability.
Method / resource A new formula was proposed to simulate increased leaf decay under heat and water stress.
Method / resource The 4M model predicted a considerable future decrease in maize yield safety.
Method / resource Comparison of observed and simulated data suggested two model improvements for projections of environmental stress impacts.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

Estimates from images before harvest showed only a slight decrease in performance compared with the statistic obtained just before harvest.

Taxon: WheatTriticum aestivumt0
Outcome: performancee1
Direction: slight decreasee1
Comparator: the statistic obtained just before the harveste1

Verbatim

t0
“Wheat Yield Estimates”
✓ located verbatim in the source · title, characters 67–88

e1
“only a slight decrease in performance is observed compared to the statistic obtained just before the harvest”
✓ located verbatim in the source · abstract, characters 1342–1450

Title

Combined Use of Multi-Temporal Landsat-8 and Sentinel-2 Images for Wheat Yield Estimates at the Intra-Plot Spatial Scale

Remy Fieuzal; Vincent Bustillo; David Collado; et al. Agronomy 2020. doi:10.3390/agronomy10030327

Other claims from this paper (7)

Observation The best performances were obtained when NDVI was combined with the yield maps collected during the crop rotation.
Method / resource In 2014 the coefficient of determination (R2) of the yield estimate was 0.44, the lowest season.
Method / resource In 2014 the root mean square error (RMSE) of the yield estimate was 8.13 quintals per hectare.
Method / resource In the three other years the R2 of the yield estimate was close to or above 0.60.
Method / resource In the three other years the RMSE of the yield estimate was lower than 7 q.h−1.
Method / resource The relative error of the yield estimate in the three other years was inferior to 11.3%.
Method / resource Early and accurate yield estimates were obtained three months before the end of the crop cycle.

Method / resourceobservedoriginal resultnegativesimulated

Claim · model-written summary

The model simulated lower cereal yield due to nitrogen competition.

Taxon: cereale0
Outcome: cereal yielde0
Direction: decreasee0
Qualifier: competition for nitrogene0

Not reportedComparator

Verbatim

e0
“a decrease in cereal yield due to competition for nitrogen”
✓ located verbatim in the source · abstract, characters 2413–2471

Title

Ability of the STICS soil-crop model for simulating performances and inter-specific interactions in tropical cereal-legume intercropping

de Freitas, Mathilde; Couedel, Antoine; Falconnier, Gatien N.; et al. HAL (Le Centre pour la Communication Scientifique Directe) 2024

Other claims from this paper (9)

Method / resource STICS simulated cereal grain yield with similar accuracy for sole crops and intercrops.
Method / resource STICS accuracy for legumes was lower under intercropping than sole cropping.
Method / resource STICS correctly reproduced cereal legume competition and complementarity in Mali and Burkina Faso.
Method / resource STICS came close to reproducing cereal legume competition and complementarity in Brazil.
Method / resource In Senegal STICS overestimated legume partial land equivalent ratio.
Method / resource In Senegal STICS underestimated cereal partial land equivalent ratio.
Method / resource The model simulated lower legume yield due to light competition.
Method / resource Water stress had little simulated effect on yield and crop interactions.
Method / resource The authors judge STICS accuracy acceptable for tropical intercropping where legume yields are not too low.

Method / resourceobservedoriginal resultnegativesimulated

Claim · model-written summary

The SDI models indicated a linear decline in relative yield with increasing wetness.

Taxon: CORNZea mays subsp. mayst0
Outcome: relative yielde0
Direction: linear decreasee0
Comparator: increasing wetness (SDI values)e0

Verbatim

e0
“The SDI models indicated a linear decrease in the relative yield with increasing wetness (SDI values)”
✓ located verbatim in the source · abstract, characters 823–924

t0
“CORN”
✓ located verbatim in the source · title, characters 0–4

Title

CORN GROWTH AS AFFECTED BY EXCESS SOIL WATER

S. Mukhtar; J. L. Baker; R. S. Kanwar Transactions of the ASAE 1990. doi:10.13031/2013.31348

Other claims from this paper (9)

Observation Corn was most susceptible to flooding at the early vegetative stage.
Intervention effect Flooding caused maximum plant canopy height reduction at the early vegetative stage.
Intervention effect Flooding caused maximum dry matter reduction at the early vegetative stage.
Intervention effect Flooding caused maximum grain yield reduction at the early vegetative stage.
Observation Early vegetative crop susceptibility factor was 0.64.
Observation Late vegetative crop susceptibility factor was 0.44.
Observation Flowering crop susceptibility factor was 0.15.
Observation Yield formation crop susceptibility factor was 0.19.
Observation Yield SDI regression lines differed considerably between years in the undrained area.

“yield decrease”

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