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Mechanismobservedoriginal resultmeasured

Claim · model-written summary

Yield, rather than temporal yield variability, drove stability.

Taxon
bioenergy cropst0
Outcome
Stabilitye0
Qualifier
driven by yield as opposed to temporal variability of yielde0

Verbatim

e0

“Stability was driven by yield as opposed to temporal variability of yield.”

✓ located verbatim in the source · abstract, characters 590–664
t0

“bioenergy crops”

✓ located verbatim in the source · title, characters 13–28

Title

Diversifying bioenergy crops increases yield and yield stability by reducing weed abundance

Jacob M. Jungers; Yi Yang; Christopher W. Fernandez; et al. Science Advances 2021. doi:10.1126/sciadv.abg8531

Other claims from this paper (5)
Associationobservedoriginal resultmeasured

Claim · model-written summary

High facies patchiness reduced yield or increased its temporal variability and reduced predictability.

Taxon
grain cropse1
Outcome
yielde0
Direction
reducese0
Setting
High facies patchinesse0

Verbatim

e0

“High facies patchiness either reduces yield or increases its temporal variability and reduces predictability.”

✓ located verbatim in the source · abstract, characters 1535–1644
e1

“grain crops”

✓ located verbatim in the source · abstract, characters 13–24

Title

Factors of intra-field phytomass variability in steppe agricultural landscapes of Kazakhstan

F.K. Kiryanov-Gref; A.V. Khoroshev; K.A. Anatskaya Bulletin of the Karaganda University “Biology medicine geography Series” 2024. doi:10.31489/2024bmg1/150-158

Other claims from this paper (6)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Wheat yield gaps showed temporal variability of 9 to 18%.

Outcome
temporal variabilitye0
Value
9 to 18%e0

Verbatim

e0

“High regional differences in wheat yield gaps were observed, with values ranging from 1.64 t/ha in Casablanca Settat to 4.12 t/ha in Marrakech Safi, and temporal variability ranging from 9 to 18%.”

✓ located verbatim in the source · abstract, characters 1163–1359

Title

The impact of precipitation, temperature, and soil moisture on wheat yield gap quantification: evidence from Morocco

Lahcen Ousayd; Terence Epule Epule; Salwa Belaqziz; et al. Agriculture & Food Security 2025. doi:10.1186/s40066-024-00509-w

Other claims from this paper (7)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Spatial variability was below temporal variability and frequently below 1 mm.

Outcome
Spatial variabilitye0
Direction
less thane0
Value
1 mme0

Verbatim

e0

“Spatial variability was less than temporal variability, and frequently less than 1 mm”

✓ located verbatim in the source · abstract, characters 1234–1319
t0

“crop yield”

✓ located verbatim in the source · title, characters 79–89
e1

“by corn and soybean phenological phase”

✓ located verbatim in the source · abstract, characters 1035–1073

Title

Spatial and temporal precipitation variability as a component of site-specific crop yield variability

M. R. O'Neal Purdue e-Pubs (Purdue University System) 2000

Other claims from this paper (10)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Yield gaps of the four legumes showed large spatial and temporal variability across the production zones.

Taxon
legumese3
Outcome
yield gapse3
Qualifier
Large spatial and temporal variabilitye3

Verbatim

e3

“Large spatial and temporal variability was observed in the yield gaps of the four legumes across the production zones”

✓ located verbatim in the source · abstract, characters 1683–1800

Title

Yield Gap Analysis of Soybean, Groundnut, Pigeonpea and Chickpea in India Using Simulation Modeling:Global Theme on Agroecosystems Report no. 31

Virender Singh Bhatia; P. Singh; S P Wani; et al. Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics) 2006

Other claims from this paper (13)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Temporal precipitation variability was 0.17 to 3.40 mm·day−1.

Outcome
Median absolute deviation from a reference yeare0
Value
0.17 to 3.40 mm·day−1e0

Verbatim

e0

“Median absolute deviation from a reference year was 0.17 to 3.40 mm·day−1 (temporal/year-to-year variability)”

✓ located verbatim in the source · abstract, characters 1123–1232
t0

“crop yield”

✓ located verbatim in the source · title, characters 79–89
e1

“by corn and soybean phenological phase”

✓ located verbatim in the source · abstract, characters 1035–1073

Title

Spatial and temporal precipitation variability as a component of site-specific crop yield variability

M. R. O'Neal Purdue e-Pubs (Purdue University System) 2000

Other claims from this paper (10)
Associationobservedoriginal resultmeasured

Claim · model-written summary

Spatial and temporal corn yield variability were uncorrelated.

Taxon
Corn Silaget0
Outcome
Spatial and temporal variabilitye0

Not reportedSettingDirection

Verbatim

e0

“Spatial and temporal variability were uncorrelated”

✓ located verbatim in the source · abstract, characters 1120–1170
t0

“Corn Silage”

✓ located verbatim in the source · title, characters 31–42

Title

Combining Spatial and Temporal Corn Silage Yield Variability for Management Zone Development

Tulsi P. Kharel; Angel Maresma; Karl J. Czymmek; et al. Agronomy Journal 2019. doi:10.2134/agronj2019.02.0079

Other claims from this paper (3)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Maximum temporal yield variability was 14.7% between 2014 and 2017.

Taxon
paddy cropt0
Outcome
Maximum temporal variabilitye0
Direction
Maximume0
Value
14.7 %e0
Qualifier
between the year 2014 and 2017e0

Verbatim

e0

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

✓ located verbatim in the source · abstract, characters 750–832
t0

“Paddy Crop”

✓ located verbatim in the source · title, characters 32–42

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/jae2019563.1687

Other claims from this paper (4)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Spatial and temporal cotton yield variability differed among fields.

Outcome
spatial and temporal yield variabilitye1
Qualifier
varied with the fielde1
Setting
Southern High Plainst0

Verbatim

t0

“Irrigated Cotton Yield in the Southern High Plains”

✓ located verbatim in the source · title, characters 31–81
e1

“The amount and pattern of spatial and temporal yield variability varied with the field”

✓ located verbatim in the source · abstract, characters 705–791

Title

Spatial and Temporal Trends of Irrigated Cotton Yield in the Southern High Plains

Wenxuan Guo Agronomy 2018. doi:10.3390/agronomy8120298

Other claims from this paper (8)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Temporal variability dominated spatial variability in the study.

Taxon
Cropt0
Outcome
Temporal variabilitye0
Direction
much more dominante0
Comparator
spatial variabilitye0

Verbatim

e0

“Temporal variability was much more dominant than spatial variability in this study.”

✓ located verbatim in the source · abstract, characters 1441–1524
t0

“Crop Sequences”

✓ located verbatim in the source · title, characters 50–64

Title

Fractal Analysis of Temporal Yield Variability of Crop Sequences: Implications for Site‐Specific Management

Bahman Eghball; Gary E. Varvel Agronomy Journal 1997. doi:10.2134/agronj1997.00021962008900060001x

Other claims from this paper (6)
Method / resourceobservedoriginal resultpositivesimulated

Claim · model-written summary

A theoretical model suggests precision farming can reduce temporal yield variability under plausible circumstances.

Treatment
precision farminge0
Outcome
temporal yield variabilitye0
Direction
reducee0
Qualifier
plausible circumstancese0

Not reportedTaxonComparator

Verbatim

e0

“A theoretical model is presented that suggests that there are plausible circumstances under which precision farming can reduce temporal yield variability.”

✓ located verbatim in the source · abstract, characters 345–499

Title

Risk Management Potential of Precision Farming Technologies

J. Lowenberg-DeBoer Journal of Agricultural and Applied Economics 1999. doi:10.1017/s1074070800008555

Other claims from this paper (1)
Mechanismauthor interpretationoriginal resultmeasured

Claim · model-written summary

Temporal variability may greatly influence how spatial variability is expressed in a field.

Taxon
Cropt0
Outcome
spatial variabilitye0
Qualifier
Temporal variabilitye0

Verbatim

e0

“Temporal variability may greatly influence how spatial variability is expressed in a given field.”

✓ located verbatim in the source · abstract, characters 1525–1622
t0

“Crop Sequences”

✓ located verbatim in the source · title, characters 50–64

Title

Fractal Analysis of Temporal Yield Variability of Crop Sequences: Implications for Site‐Specific Management

Bahman Eghball; Gary E. Varvel Agronomy Journal 1997. doi:10.2134/agronj1997.00021962008900060001x

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

Claim · model-written summary

A theoretical model suggests plausible conditions in which precision farming reduces temporal yield variability.

Treatment
precision farminge0
Outcome
temporal yield variabilitye0
Direction
reducee0

Not reportedTaxonComparatorValue

Verbatim

e0

“A theoretical model is presented that suggests that there are plausible circumstances under which precision farming can reduce temporal yield variability”

✓ located verbatim in the source · abstract, characters 336–489

Title

RISK MANAGEMENT POTENTIAL OF PRECISION FARMING TECHNOLOGIES

Lowenberg-DeBoer, James RePEc: Research Papers in Economics

Other claims from this paper (1)

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