View: List Claim type Research area Organism Taxon as written Decade Paper Taxon groups are the verbatim names found in the abstracts (case-insensitive), not normalised: maize, corn and Zea mays are separate groups here. The Organism view merges them through NCBI Taxonomy.
Observation observed original result significant (as stated) measured Claim · model-written summary
Corn had significantly less temporal yield variability than soybean or sorghum.
temporal yield variability e0 soybean or sorghum e0 Verbatim
e0 “Corn had significantly less temporal yield variability than soybean or sorghum. ”
✓ located verbatim in the source · abstract, characters 1216–1295 Other claims from this paper (6) Observation observed original result measured Claim · model-written summary
Spatial variability was below temporal variability and frequently below 1 mm.
Spatial variability e0 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 Other claims from this paper (10) Observation observed original result measured Claim · model-written summary
Temporal precipitation variability was 0.17 to 3.40 mm·day−1.
Median absolute deviation from a reference year e0 0.17 to 3.40 mm·day−1 e0 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 Other claims from this paper (10) Observation observed original result measured Claim · model-written summary
Spatial and temporal cotton yield variability differed among fields.
spatial and temporal yield variability e1 varied with the field e1 Southern High Plains t0 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 Other claims from this paper (8) Association observed original result measured Claim · model-written summary
Fields with high ECa variability showed a stronger association between spatial and temporal yield patterns and ECa.
high variability in ECa e1 association between spatial and temporal yield patterns and ECa e1 Verbatim
t0 “Irrigated Cotton Yield in the Southern High Plains ”
✓ located verbatim in the source · title, characters 31–81 e1 “Fields with high variability in ECa exhibited a stronger association between spatial and temporal yield patterns and ECa ”
✓ located verbatim in the source · abstract, characters 793–913 Other claims from this paper (8) Mechanism hypothesis original result measured Claim · model-written summary
Spatial and temporal yield patterns in low- variability cotton fields might be more influenced by weather or other factors across seasons.
spatial and temporal yield patterns e1 weather or other factors in different growing seasons e1 Verbatim
t0 “Irrigated Cotton Yield in the Southern High Plains ”
✓ located verbatim in the source · title, characters 31–81 e1 “For fields with low variability in yield , spatial and temporal yield patterns might be more influenced by weather or other factors in different growing seasons ”
✓ located verbatim in the source · abstract, characters 1217–1376 Other claims from this paper (8)
not stated 33 Method / resource author interpretation original result simulated Claim · model-written summary
A theoretical model suggests plausible conditions in which precision farming reduces temporal yield variability .
precision farming e0 temporal yield variability e0 Not reported Taxon Comparator Value
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 Other claims from this paper (1) Method / resource observed original result positive simulated Claim · model-written summary
A theoretical model suggests precision farming can reduce temporal yield variability under plausible circumstances.
precision farming e0 temporal yield variability e0 plausible circumstances e0 Not reported Taxon Comparator
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 Other claims from this paper (1) Method / resource observed original result simulated Claim · model-written summary
Agreement between simulated and observed temporal variability was lower.
agreement of simulated and observed temporal variability e0 simulated and observed e0 Not reported Taxon
Verbatim
e0 “The agreement of simulated and observed temporal variability is lower due to non-climatic factors ”
✓ located verbatim in the source · abstract, characters 1390–1487 Other claims from this paper (7) Association observed original result simulated Claim · model-written summary
Temporal variability of grain yield , nitrogen response and net revenue increased with nitrogen rate.
Temporal variability of grain yield, N response, and net revenue e0 Verbatim
e0 “Temporal variability of grain yield , N response, and net revenue increased with N rate. ”
✓ located verbatim in the source · abstract, characters 1751–1838 t0 “Maize ”
✓ located verbatim in the source · title, characters 48–53 Other claims from this paper (8) Method / resource author interpretation original result positive measured Claim · model-written summary
Multifractal methods characterized spatial and temporal leaf area variation and its multiscale yield relation.
spatial and temporal variability of maize leaf area and multiscale relationship between leaf area and yield e0 Not reported Comparator Value
Verbatim
e0 “Multifractal theory can effectively characterize spatial and temporal variability of maize leaf area and multiscale relationship between leaf area and yield ”
✓ located verbatim in the source · abstract, characters 734–890 Other claims from this paper (5) Method / resource observed original result positive simulated Claim · model-written summary
Models reproduced temporal yield variability for maize with correlation up to 0.888.
time series correlation coefficients (r) e0 observed temporal variability e0 Verbatim
e0 “maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) ”
✓ located verbatim in the source · abstract, characters 839–1089 Other claims from this paper (10) Observation observed original result measured Claim · model-written summary
Sugar and stalk yield response to applied nitrogen showed high spatial and temporal variability .
spatial and temporal variability in sugar and stalk yield e0 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 Other claims from this paper (5) Association observed original result measured Claim · model-written summary
Soil explained 15% of variation in sugarcane yield efficiency across seasons.
average of all seasons e0 Not reported Setting Direction
Verbatim
e0 “Soil explained 15% of the variability , considering the average of all seasons ”
✓ located verbatim in the source · abstract, characters 909–986 t0 “sugarcane ”
✓ located verbatim in the source · title, characters 31–40 Other claims from this paper (5) Method / resource observed original result positive measured Claim · model-written summary
The heteroskedastic gamma regression model outperformed the other models for explaining sugarcane yield variability in commercial fields, with R2 of 0.89.
explaining yield variability e0 other methods e0 commercial sugarcane fields e0 Verbatim
e0 “The results indicate that the heteroskedastic gamma regression model outperformed the other methods in explaining yield variability , particularly in commercial sugarcane fields, achieving a Coefficient Determination (R2) of 0.89. ”
✓ located verbatim in the source · abstract, characters 921–1150 Method / resource observed original result positive measured Claim · model-written summary
Clustering identified stable spatial and temporal yield clusters.
stable, physically meaningful clusters with recognizable spatial and temporal structure e0 Not reported Comparator
Verbatim
e0 “The clustering procedure successfully identified stable, physically meaningful clusters with recognizable spatial and temporal structure ”
✓ located verbatim in the source · abstract, characters 954–1090 e1 “rice fields ”
✓ located verbatim in the source · abstract, characters 547–558 Other claims from this paper (2) Method / resource author interpretation original result positive measured Claim · model-written summary
The approach generated spatial rice yield maps capturing within-field variability .
spatially explicit rice yield maps e0 within-field variability e0 Verbatim
e0 “the proposed approach provides accurate, spatially explicit rice yield maps that capture within-field variability ”
✓ located verbatim in the source · abstract, characters 1371–1484 t0 “Rice Yield Prediction ”
✓ located verbatim in the source · title, characters 0–21 Other claims from this paper (10) Association observed original result negative significant (as stated) measured Claim · model-written summary
Heat episode variability was negatively associated with observed rice grain yield across all subregions.
observed grain yield e0 Verbatim
e0 “Significant negative ( p < 0.05) impacts of the variability of high‐temperature episodes on the observed grain yield were found in all subregions. ”
✓ located verbatim in the source · abstract, characters 1594–1740 t0 “Rice Yield in China ”
✓ located verbatim in the source · title, characters 81–100 Other claims from this paper (6) Observation observed original result measured Claim · model-written summary
Temporal soybean yield variability was 20–22%.
soybean yield variability e7 Verbatim
e7 “Spatial and temporal soybean yield variability was 16–26% and 20–22%, respectively ”
✓ located verbatim in the source · abstract, characters 2005–2087 Other claims from this paper (14) Association observed original result significant (as stated) simulated Claim · model-written summary
Temporal variability across sowing times significantly affected soybean yield .
different sowing times e0 Not reported Direction
Verbatim
e0 “temporal variability associated with different sowing times significantly impacts soybean yield . ”
✓ located verbatim in the source · abstract, characters 1077–1173 Other claims from this paper (2) Observation observed original result measured Claim · model-written summary
Organic soybean yield variability was highest, at 48%.
Temporal yield variability e1 Verbatim
e0 “was highest in the ORG system during the soybean (CV = 48%) ”
✓ located verbatim in the source · abstract, characters 1735–1794 e1 “Temporal yield variability differed among management systems and rotation phases and was highest in the ORG system during the soybean (CV = 48%) and winter wheat (CV = 33%) phases of the rotation ”
✓ located verbatim in the source · abstract, characters 1650–1845 Other claims from this paper (10) Observation observed original result measured Claim · model-written summary
Temporal variability dominated spatial variability in the study.
Temporal variability e0 much more dominant e0 spatial variability e0 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 Other claims from this paper (6) Recommendation author interpretation original result basis n/a Claim · model-written summary
Temporal variability of crop yield and soil attributes should be considered to delineate management zones accurately.
take into account the temporal variability of crop yield and soil attributes e0 Verbatim
e0 “it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately ”
✓ located verbatim in the source · abstract, characters 1245–1383 Other claims from this paper (3) Mechanism author interpretation original result measured Claim · model-written summary
Temporal variability may greatly influence how spatial variability is expressed in a field.
spatial variability e0 Temporal variability e0 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 Other claims from this paper (6) Observation observed original result measured Claim · model-written summary
Wheat yield gaps showed temporal variability of 9 to 18%.
temporal variability 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 Other claims from this paper (7) Association observed original result measured Claim · model-written summary
Post-heading heat stress and average temperature explained about 29% of the observed spatial and temporal yield variability .
post-heading heat stress and average temperature e0 yield variability e0 Not reported Direction
Verbatim
e0 “The correlation between measured grain yield s and post-heading heat stress and average temperature were statistically significant in the entire wheat-producing region, and explained about 29% of the observed spatial and temporal yield variability ”
✓ located verbatim in the source · abstract, characters 1148–1394 Other claims from this paper (5) Method / resource observed original result positive simulated Claim · model-written summary
Models reproduced temporal yield variability for wheat with correlation up to 0.673.
time series correlation coefficients (r) e0 observed temporal variability e0 Verbatim
e0 “maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) ”
✓ located verbatim in the source · abstract, characters 839–1089 Other claims from this paper (10) Observation observed original result measured Claim · model-written summary
Organic winter wheat yield variability was highest, at 33%.
yield variability e1 Verbatim
e0 “winter wheat (CV = 33%) phases of the rotation ”
✓ located verbatim in the source · abstract, characters 1799–1845 e1 “Temporal yield variability differed among management systems and rotation phases and was highest in the ORG system during the soybean (CV = 48%) and winter wheat (CV = 33%) phases of the rotation ”
✓ located verbatim in the source · abstract, characters 1650–1845 Other claims from this paper (10) Recommendation author interpretation original result basis n/a Claim · model-written summary
The authors caution that nutrient response experiments may not predict next-year nitrogen needs.
estimate next year's N fertilizer requirement e0 apparent temporal variability in the results e0 Verbatim
e0 “it is not always appropriate to use results of nutrient response experiments to estimate next year's N fertilizer requirement due to apparent temporal variability in the results. ”
✓ located verbatim in the source · abstract, characters 1237–1415 t0 “winter wheat ”
✓ located verbatim in the source · title, characters 33–45 Other claims from this paper (4) Observation observed original result no effect measured Claim · model-written summary
No-till wheat yield variability was similar to conventional.
yield variability e1 Verbatim
e0 “similar in the NT (corn and winter wheat phases) systems ”
✓ located verbatim in the source · abstract, characters 1970–2026 e1 “Compared to the CT system, yield variability was 40% lower in the LI (corn phase), 33% lower in the NT (soybean phase) and similar in the NT (corn and winter wheat phases) systems ”
✓ located verbatim in the source · abstract, characters 1847–2026 Other claims from this paper (10) 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.
Zea mays subsp. mayse0
Gossypium hirsutum
Zea mays
Oryza sativa
Glycine max
Triticum aestivum