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Observationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

Corn had significantly less temporal yield variability than soybean or sorghum.

Outcome
temporal yield variabilitye0
Direction
lesse0
Comparator
soybean or sorghume0

Verbatim

e0

“Corn had significantly less temporal yield variability than soybean or sorghum.”

✓ located verbatim in the source · abstract, characters 1216–1295

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)
Observationobservedoriginal resultmeasured

Claim · model-written summary

Temporal soybean yield variability was 20–22%.

Taxon
soybeanGlycine maxe7
Outcome
soybean yield variabilitye7
Value
20–22%e7
Qualifier
temporale7

Verbatim

e7

“Spatial and temporal soybean yield variability was 16–26% and 20–22%, respectively”

✓ located verbatim in the source · abstract, characters 2005–2087

Title

Soybean Spatiotemporal Yield and Economic Variability as Affected by Tillage and Crop Rotation

Mahdi M. Al‐Kaisi; Sotirios Archontoulis; David Kwaw‐Mensah Agronomy Journal 2016. doi:10.2134/agronj2015.0363

Other claims from this paper (14)
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)
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 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

Sugar and stalk yield response to applied nitrogen showed high spatial and temporal variability.

Taxon
sugarcanee1
Treatment
applied Ne0
Outcome
spatial and temporal variability in sugar and stalk yielde0

Verbatim

e0

“High spatial and temporal variability in sugar and stalk yield to applied N were observed.”

✓ located verbatim in the source · abstract, characters 1490–1580
e1

“In sugarcane”

✓ located verbatim in the source · abstract, characters 148–160

Title

Relation between Early Season–Measured Agronomic Variables and Sugar Yield Responses to Nitrogen

Yumiko Kanke; Brenda Tubaña; Marilyn Dalen; et al. Agronomy Journal 2016. doi:10.2134/agronj2015.0037

Other claims from this paper (5)
Observationobservedoriginal resultmeasured

Claim · model-written summary

The AYM system showed real-time temporal and spatial yield variability classification and quantification in paddy field.

Taxon
paddy crope0
Outcome
real-time temporal and spatial variability classification and quantificatione5
Setting
paddy fielde5

Verbatim

e0

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

✓ located verbatim in the source · abstract, characters 25–109
e5

“The AYM system could show the real-time temporal and spatial variability classification and quantification in paddy field”

✓ located verbatim in the source · abstract, characters 833–954

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 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)

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