Try:droughtFusariumnitrogen fertilizerArabidopsisseed germination

“decrease in A”

111 matches

Claim types

Direction of the findings

Over time

1970 ’80 ’90 2000 ’10 ’20

Refine ·

More filters

Clear filters

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 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 resultnegativemeasured

Claim · model-written summary

YOLOv5_E accuracy shows a 0.9% marginal decrease compared with the original YOLOv5.

Taxon: pineappleAnanas comosuse0
Outcome: accuracye5
Direction: marginal decreasee5
Value: 0.9%e5
Comparator: the original YOLOv5e5

Verbatim

e0
“During pineapple cultivation”
✓ located verbatim in the source · abstract, characters 9–37

e5
“Compared to the original YOLOv5, YOLOv5_E shows a 0.9% marginal decrease in accuracy”
✓ located verbatim in the source · abstract, characters 1033–1117

Title

A-pruning: a lightweight pineapple flower counting network based on filter pruning

Guoyan Yu; Ruilin Cai; Yingtong Luo; et al. Complex & Intelligent Systems 2023. doi:10.1007/s40747-023-01261-7

Other claims from this paper (10)

Method / resource YOLOv5_E reached 71.7% accuracy in counting pineapple flowers.
Method / resource YOLOv5_E has 1.7 M parameters.
Method / resource YOLOv5_E has a model size of 3.8 MB.
Method / resource YOLOv5_E runs at 178 frames per second.
Method / resource YOLOv5_E reduced the number of parameters by 75.8%.
Method / resource YOLOv5_E reduced the model size by 73.8%.
Method / resource The running speed of YOLOv5_E is nearly twice that of the original network.
Method / resource YOLOv5_E has the fastest detection speed among the ten networks evaluated.
Method / resource YOLOv5_E ranks second in detection accuracy among the ten networks evaluated.
Method / resource YOLOv5_E achieved an average detection speed of 24 frames per second on an NVIDIA Jetson Xavier NX board.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

Models with one and four augmentation techniques showed a decrease in performance.

Taxon: Tea Leaft0
Outcome: performancee0
Direction: decreasee0
Comparator: one and four augmentation techniquese0

Verbatim

t0
“Tea Leaf Disease Classification”
✓ located verbatim in the source · title, characters 83–114

e0
“models with one and four augmentation techniques experience a decrease in performance”
✓ located verbatim in the source · abstract, characters 889–974

Title

Comparative Analysis of Data Augmentation Techniques on MobileNetV2 Performance in Tea Leaf Disease Classification

Fitri Mintarsih; Dewi Khairani; M. Farhan 2024 12th International Conference on Cyber and IT Service Management (CITSM) 2024. doi:10.1109/citsm64103.2024.10775557

Other claims from this paper (5)

Method / resource Variation in combinations of data augmentation techniques in the MobileNetV2 model did not affect changes in accuracy, loss, precision, recall or F1-score in tea leaf disease classification.
Method / resource The use of augmentation techniques significantly affected the model performance.
Method / resource Models with three and five augmentation techniques showed very good results.
Method / resource Model number 32, using flip, rotation, translation, zoom and contrast augmentation, had the highest accuracy of 0.9867.
Method / resource Model number 32 had a low loss value of 0.0603.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

All four models had a slight accuracy decrease on workstations and mobile devices.

Taxon: Plantt0
Outcome: accuracye1
Direction: decreasee0
Comparator: workstation and mobile devicese0

Verbatim

e0
“the four models have a slight accuracy decrease on both workstation and mobile devices”
✓ located verbatim in the source · abstract, characters 765–851

e1
“Mason model has a highest accuracy of 90.54%”
✓ located verbatim in the source · abstract, characters 567–611

t0
“Plant Diseases”
✓ located verbatim in the source · title, characters 40–54

Title

Evaluation of CNN Models in Identifying Plant Diseases on a Mobile Device

Teddy Aristan; Gede Putra Kusuma Revue d intelligence artificielle 2023. doi:10.18280/ria.370221

Other claims from this paper (7)

Method / resource Mason reached the highest accuracy, 90.54%, for plant disease classification.
Method / resource Mason had the smallest output file, 0.85MB.
Method / resource MobileNetV3 achieved 88.83% accuracy and a 16.85MB file.
Method / resource EfficientNetB0 achieved 88.75% accuracy and a 16.08MB file.
Method / resource ShuffleNetV2 achieved 83.52% accuracy and a 15.89MB file.
Method / resource MobileNetV3 consumed fewer resources overall than the other models.
Recommendation The authors recommend Mason for mobile devices based on accuracy and low resource consumption.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

A qPCR detection method confirmed a twofold decrease of health indicators in beet clamps.

Taxon: beetBeta vulgarist0
Outcome: health indicatorse0
Direction: decreasee0
Value: twofolde0
Qualifier: qPCR-based early detection techniquee0

Verbatim

e0
“a qPCR-based early detection technique was developed and confirmed a twofold decrease of health indicators and an up to 10,000-fold increase of disease indicators in beet clamps”
✓ located verbatim in the source · abstract, characters 1485–1662

t0
“sugar beets”
✓ located verbatim in the source · title, characters 85–96

Title

Microbiome-driven identification of microbial indicators for postharvest diseases of sugar beets

Peter Kusstatscher; Christin Zachow; Karsten Harms; et al. Microbiome 2019. doi:10.1186/s40168-019-0728-0

Other claims from this paper (8)

Observation Stored beet microbiomes differed regionally across clamps in Austria and Germany.
Observation Microbial diversity significantly decreased in decaying sugar beets.
Observation The overall microbiome composition shifted in decaying sugar beets.
Observation Candida, Penicillium, and Lactobacillus were main disease indicators in decaying sugar beets.
Observation Plectosphaerella and Vishniacozyma reflected the microbiome of healthy beets.
Association Higher microbial diversity reflected healthy beet microbiomes.
Method / resource A qPCR detection method confirmed up to a 10,000-fold increase of disease indicators in beet clamps.
Method / resource Sugar content analyses verified the microbial indicator findings.

Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

One mode captured vegetation decrease during the El Niño 2006-2007 flood.

Taxon: vegetatione0
Outcome: vegetation decreasee0
Direction: decreasee0
Value: 2006-2007e0

Verbatim

e0
“The remaining mode captures the vegetation decrease caused by the flood related to El Niño 2006-2007”
✓ located verbatim in the source · abstract, characters 950–1050

Title

Independent component analysis of MODIS-NDVI data in a large South American wetland

Andrés Antico Remote Sensing Letters 2011. doi:10.1080/01431161.2011.603376

Other claims from this paper (3)

Method / resource ICA extracted three interpretable modes of vegetation response to hydrological change.
Method / resource One mode isolated a vegetation response to severe La Niña drought in 2007-2008.
Method / resource A component reflected lagoon expansion or contraction with Paraná River water level.

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 resultnegativemeasured

Claim · model-written summary

Leaf-level analysis showed a decrease in accuracy of 4 to 11% across the four seasons relative to canopy-level results.

Outcome: accuracye0
Direction: decreasee0
Value: 4 – 11%e0

Verbatim

e0
“The results of the leaf-level analysis showed a decrease in accuracy of between 4 – 11% for the four seasons”
✓ located verbatim in the source · abstract, characters 1458–1566

Title

IDENTIFYING THE BEST SEASON FOR MAPPING EVERGREEN SWAMP AND MANGROVE SPECIES USING LEAF-LEVEL SPECTRA IN AN ESTUARINE SYSTEM IN KWAZULU-NATAL, SOUTH AFRICA

Heidi van Deventer; Moses Azong Cho; Onisimo Mutanga; et al. 2014

Other claims from this paper (4)

Method / resource When upscaled to canopy level, all four seasons produced overall classification accuracies above 90%.
Method / resource Spring, summer and autumn produced the highest overall accuracy, 94.7%.
Method / resource The overall accuracy for winter was 89.5%.
Method / resource The simulated object-oriented approach gave higher accuracy than the pixel-level approach.

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.

Lexical search (BM25). All words must match; if nothing does, any word. Organism names also match every spelling of the same organism. No semantic search yet.

“decrease in A”

Claim types

Direction of the findings

Over time

Claim type

Research area

Polarity

Statistics