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Method / resourceobservedoriginal resultpositivesignificant (as stated)measured

Claim · model-written summary

Field testing found a significant decrease in bird numbers in targeted areas.

Taxon: riceOryza sativae1
Interactor: birdsAvese0pest
Outcome: number of birds in the targeted arease0
Direction: decreasinge0
Value: significante0

Verbatim

e0
“the result of the prototype field-testing showed a significant effect in decreasing the number of birds in the targeted areas”
✓ located verbatim in the source · abstract, characters 1282–1407

e1
“Filipino rice farmers, resulting in losses in annual harvest yield. Farmers suffer the challenge of crop damage by birds”
✓ located verbatim in the source · abstract, characters 45–165

Title

Bird-Repelling Device for Agricultural Application using Motion Detection

Maribelle Dequilla-Pabiania; Chris Julian C. Alcedo; Henry G. Morales; et al. 2024 16th International Conference on Computer and Automation Engineering (ICCAE) 2024. doi:10.1109/iccae59995.2024.10569619

Other claims from this paper (3)

Method / resource In field testing, the prototype deterred birds at 73% versus 42% for a scarecrow.
Method / resource In controlled testing, the prototype deterred birds at 67% versus 49% for a scarecrow.
Method / resource The controlled environment showed no significant change in bird numbers, attributed to low population.

Method / resourceobservedoriginal resultpositivesignificant (as stated)measured

Claim · model-written summary

The stacked ensemble model significantly decreases RMSE compared with traditional machine learning models.

Taxon: crope0
Outcome: RMSEe1
Direction: decreasee1
Comparator: traditional machine learning modelse1

Verbatim

e0
“Predicting crop yields remains a crucial challenge in agriculture”
✓ located verbatim in the source · abstract, characters 9–74

e1
“The proposed stacked ensemble model achieves superior crop yield prediction performance, evidenced by a notable enhancement in accuracy and a significant decrease in RMSE, surpassing the predictive capabilities of traditional machine learning models”
✓ located verbatim in the source · abstract, characters 1125–1374

Title

Stacked ensemble model for accurate crop yield prediction using machine learning techniques

Ramesh V; Kumaresan P Environmental Research Communications 2025. doi:10.1088/2515-7620/adb9c0

Other claims from this paper (6)

Method / resource The stacked ensemble model achieves superior crop yield prediction performance compared with traditional machine learning models.
Method / resource The stacked ensemble model notably enhances accuracy compared with traditional machine learning models.
Method / resource Mean Absolute Error of the stacked ensemble model is 7.20 tons/hectare.
Method / resource Mean Square Error of the stacked ensemble model is 15570.32 tons 2 /hectare 2.
Method / resource Root Mean Square Error of the stacked ensemble model is 124.78 tons/hectare.
Method / resource Coefficient of determination (R2) of the stacked ensemble model is 0.98.

Method / resourceobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

The percentage decline in Δ F / Fm ′ 14s after dehydration correlated with cultivar drought susceptibility index at r = 0·72.

Outcome: percentage decrease of Δ F / Fm ′ 14se0
Value: r = 0·72e0
Comparator: drought susceptibility index (DSI)e0

Not reportedTaxonDirection

Verbatim

e0
“The percentage decrease of Δ F / Fm ′ 14s after dehydration was correlated with the drought susceptibility index (DSI) of the cultivars, evaluated on a yield basis and a significant correlation ( r = 0·72, P < 0·001) was found.”
✓ located verbatim in the source · abstract, characters 966–1193

Title

The quantum yield of photosynthetic electron transport evaluated by chlorophyll fluorescence as an indicator of drought tolerance in durum wheat

Z. Flagella; D. Pastore; R. G. Campanile; et al. The Journal of Agricultural Science 1995. doi:10.1017/s0021859600084823

Other claims from this paper (4)

Intervention effect Dehydration lowered leaf Δ F / Fm ′ 14s by an average of 20%.
Intervention effect The 200-second Δ F / Fm ′ measure showed no great difference between dehydrated and control leaves.
Intervention effect The 14-second Fv ′/ Fm ′ measure showed no great difference between dehydrated and control leaves.
Intervention effect The 200-second Fv ′/ Fm ′ measure showed no great difference between dehydrated and control leaves.

Method / resourceobservedoriginal resultnegativesignificant (as stated)measured

Claim · model-written summary

Marker-based selection significantly decreased the response to selection compared with the other approaches

Taxon: wheatTriticum aestivume0
Treatment: MSe4
Outcome: response to selectione4
Direction: decreasee4
Qualifier: P < 0.05e4
Comparator: the other approachese4

Verbatim

e0
“Ten populations of Washington State University (WSU) winter wheat breeding lines including a diversity panel”
✓ located verbatim in the source · abstract, characters 421–529

e4
“MS was not successful in terms of R relative to the other selection approaches; using this strategy resulted in a significant (P < 0.05) decrease in response to selection compared with the other approaches”
✓ located verbatim in the source · abstract, characters 1537–1742

Title

Gains through selection for grain yield in a winter wheat breeding program

Dennis N. Lozada; Brian P. Ward; Arron H. Carter PLoS ONE 2020. doi:10.1371/journal.pone.0221603

Other claims from this paper (5)

Method / resourceobservedoriginal resultpositivesignificant (as stated)measured

Claim · model-written summary

Band correction significantly improved transferability between sensors, reducing RRMSE by 15.05–59.99%.

Taxon: riceOryza sativat0
Treatment: band correctione0
Outcome: Model transferabilitye0
Direction: improvede0
Value: 15.05–59.99%e0
Comparator: different sensorse0

Verbatim

e0
“Model transferability was improved significantly between different sensors after band correction with a decrease of 15.05–59.99% in RRMSE.”
✓ located verbatim in the source · abstract, characters 1525–1663

t0
“Rice Grain Yield”
✓ located verbatim in the source · title, characters 41–57

Title

Transferability of Models for Predicting Rice Grain Yield from Unmanned Aerial Vehicle (UAV) Multispectral Imagery across Years, Cultivars and Sensors

Hengbiao Zheng; Wenhan Ji; Wenhui Wang; et al. Drones 2022. doi:10.3390/drones6120423

Other claims from this paper (4)

Method / resource RENDTI was superior to other indices for regression with rice grain yield in most cases.
Method / resource GNDTI had the highest validation accuracy across rice cultivars and sensors.
Method / resource The Japonica yield model transferred to Indica rice with RMSE 1.16 t/ha, bias 0.08 and RRMSE 11.04%.
Method / resource Random forest improved transferability across years and cultivars and had the highest prediction accuracy with RMSE 0.94 t/ha, bias −0.21 and RRMSE 9.37%.

Method / resourceobservedoriginal resultpositivesignificant (as stated)measured

Claim · model-written summary

The listed drought indices showed significant correlations with yields under both stress and non-stressed conditions.

Taxon: bread wheatTriticum aestivumt0
Outcome: significant correlations with yields under both stress and non-stressed conditionse0
Qualifier: at all stress intensitiese0
Comparator: stress and non-stressed conditionse0

Verbatim

e0
“The mean productivity (MP), modified stress tolerance index (MSTIk), superiority index (Pi), mean relative performance (MRP), relative efficiency index (REI), geometric mean productivity (GMP), stress tolerance index (STI), harmonic mean (HARM) and relative decrease in yield (RDY) showed a high power of discrimination among genotypes, and expressed significant correlations with yields under both stress and non-stress…” Show full quote
✓ located verbatim in the source · abstract, characters 526–985

t0
“bread wheat”
✓ located verbatim in the source · title, characters 78–89

Title

Efficiency of drought tolerance indices under different stress severities for bread wheat selection

Sahar Bennani; Nasserlehaq Nsarellah; Mohammed Jlibene; et al. Australian Journal of Crop Science 2017. doi:10.21475/ajcs.17.11.04.pne272

Other claims from this paper (10)

Method / resource The listed drought indices showed high power of discrimination among genotypes.
Method / resource These indices selected high mean yield with low mean variance at 20% selection pressure.
Method / resource Index efficiency decreased as drought stress exceeded 35%.
Method / resource At 57% stress, only Pi and MP targeted the highest performances.
Method / resource MRP, REI, GMP, RDY and STI were interchangeable.
Observation AUS30355 was among the best performers for yield and stability.
Observation Gladius was among the best performers for yield and stability.
Observation Amir-2 was among the best performers for yield and stability.
Observation AUS30354 was among the best performers for yield and stability.
Recommendation The selected genotypes were recommended for release or breeding parents.

“yield decrease”

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