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Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Machine learning explained 93% of observed yield variability.

Outcome
observed yield variabilitye0
Value
93%e0

Verbatim

e0

“machine learning can explain 93% of observed yield variability”

✓ located verbatim in the source · abstract, characters 935–997

Title

Predicting spatial and temporal variability in crop yields: an inter-comparison of machine learning, regression and process-based models

Guoyong Leng; Jim W Hall Environmental Research Letters 2020. doi:10.1088/1748-9326/ab7b24

Other claims from this paper (9)
Method / resourceobservedoriginal resultnegativemeasured

Claim · model-written summary

CERES-Wheat and CERES-Maize failed to quantify observed within-field yield variability.

Taxon
crope0
Outcome
observed within-field yield variabilitye0
Comparator
observed within-field yield variabilitye0

Verbatim

e0

“usual crop models such as CERES-Wheat and CERES-Maize were not able to quantify the observed within-field yield variability”

✓ located verbatim in the source · abstract, characters 772–895

Title

Simulation of crop yield variability by improved root-soil-interaction modelling

Xiaoyan Duan; Sebastian Gayler; Eckart Priesack EGU General Assembly Conference Abstracts 2009

Other claims from this paper (2)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Simulated sugarcane yield showed lower interannual variability than the observed yields.

Taxon
Sugarcanet0
Outcome
interannual variabilitye0
Direction
lowere0
Comparator
observed yieldse0

Verbatim

t0

“Sugarcane”

✓ located verbatim in the source · title, characters 23–32
e0

“but exhibited a lower interannual variability than the observed yields”

✓ located verbatim in the source · abstract, characters 1397–1467

Title

A biophysical model of Sugarcane growth

S. V. CUADRA; M. H. COSTA; C. J. KUCHARIK; et al. GCB Bioenergy 2011. doi:10.1111/j.1757-1707.2011.01105.x

Other claims from this paper (4)
Associationobservedoriginal resultmeasured

Claim · model-written summary

The reduction in yield variability observed with data aggregation is specific to each crop.

Taxon
crope0
Treatment
data aggregatione0
Outcome
yield variabilitye0
Direction
reductione0

Verbatim

e0

“the degree of yield variability reduction (observed with data aggregation) is crop specific”

✓ located verbatim in the source · abstract, characters 539–630

Title

Influence of aggregation level on yield risk measures

Paweł Kobus 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 2011

Other claims from this paper (1)
Observationobservedoriginal resultmeasured

Claim · model-written summary

High genetic variability was observed for yield components in barley.

Outcome
genetic variabilitye6
Qualifier
yield componentse6

Verbatim

t0

“in barley (Hordeum vulgare)”

✓ located verbatim in the source · title, characters 78–105
e6

“A high genetic variability was also observed for yield components”

✓ located verbatim in the source · abstract, characters 1182–1247

Title

Genetic analysis of some chlorophyll fluorescence and productivity parameters in barley (Hordeum vulgare)

L. Marcial; A. Sarrafi Plant Breeding 1996. doi:10.1111/j.1439-0523.1996.tb00930.x

Other claims from this paper (8)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Large variability in climbing bean yield between fields was observed.

Taxon
climbing beant0
Outcome
variability in yield between fieldse0
Qualifier
Largee0

Verbatim

e0

“Large variability in yield between fields was observed”

✓ located verbatim in the source · abstract, characters 782–836
t0

“climbing bean”

✓ located verbatim in the source · title, characters 16–29

Title

The response of climbing bean to fertilizer and organic manure in the Northern Province of Rwanda

Edouard Rurangwa; Bernard Vanlauwe; Ken E. Giller Experimental Agriculture 2020. doi:10.1017/s0014479720000277

Other claims from this paper (12)
Observationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

Significant variability was observed for yield and its components.

Taxon
white onion (Allium cepa L.)Allium cepae0
Outcome
yield and its componentse1

Verbatim

e0

“white onion (Allium cepa L.) genotypes”

✓ located verbatim in the source · abstract, characters 72–110
e1

“Significant variability was observed for yield and its components”

✓ located verbatim in the source · abstract, characters 213–278

Title

Genetic variability and character association analysis in white onion (Allium cepa L.) genotypes

Rajshree Gayen; Kimneihchong Gangte; Jitendra Trivedi; et al. International Journal of Advanced Biochemistry Research 2025. doi:10.33545/26174693.2025.v9.i9sl.5618

Other claims from this paper (7)
Observationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

Significant variability was observed among parental cotton genotypes for yield-related traits.

Material
parental genotypese1
Outcome
variabilitye1
Qualifier
for yield-related traitse1

Verbatim

t0

“COTTON”

✓ located verbatim in the source · title, characters 66–72
e1

“Significant variability among parental genotypes was observed for yield-related traits, indicating genetic variation in the breeding material”

✓ located verbatim in the source · abstract, characters 843–984

Title

EVALUATING COMBINING ABILITIES AND HETEROTIC EFFECTS FOR ENHANCED COTTON YIELD

Z RASHEED; MR ANWAR; K HANIF; et al. Biological and Clinical Sciences Research Journal 2023. doi:10.54112/bcsrj.v2023i1.384

Other claims from this paper (6)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Maximum temporal yield variability in paddy was 14.7%, observed between 2014 and 2017.

Taxon
paddy crope0
Outcome
temporal variabilitye3
Value
14.7 %e3
Qualifier
between the year 2014 and 2017e3

Verbatim

e0

“assess yield variability of paddy crop using automatic yield monitoring (AYM) system”

✓ located verbatim in the source · abstract, characters 25–109
e3

“Maximum temporal variability (14.7 %) was observed between the year 2014 and 2017”

✓ located verbatim in the source · abstract, characters 750–831

Title

Yield Variability Assessment in Paddy Crop using Automatic Yield Monitoring System

N. S. Chandel; K. N. Agrawal Journal of Agricultural Engineering (India) 2019. doi:10.52151/jae2018551.1687

Other claims from this paper (4)
Observationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

Significant variability was observed among the crosses for yield and component traits.

Taxon
Indian mustardBrassica junceae0
Outcome
Significant variabilitye4

Not reportedDirection

Verbatim

e0

“Indian mustard [Brassica juncea (L.)] is a pivotal oilseed crop”

✓ located verbatim in the source · abstract, characters 0–63
e4

“Significant variability was observed for yield and component traits”

✓ located verbatim in the source · abstract, characters 817–884

Title

Assessment of Heterosis in Indian Mustard [Brassica juncea (L.)] Cross Combinations

M.K. Tripathi; Jagendra Singh; Ravi Yadav; et al. PLANT CELL BIOTECHNOLOGY AND MOLECULAR BIOLOGY 2025. doi:10.56557/pcbmb/2025/v26i7-89539

Other claims from this paper (7)

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