View: List Claim type Research area Organism Taxon as written Decade Paper Response of Corn Grain Yield to Spatial and Temporal Variability in Emergence 7 Show all 7 → Intervention effect observed original result significant (as stated) measured Claim · model-written summary
Emergence variability significantly affected corn height, leaf area index, dry matter accumulation, and grain yield .
plant emergence variability e0 plant height, leaf area index (LAI), dry matter accumulation e0 Not reported Taxon Comparator Direction
Verbatim
e0 “Only plant emergence variability significantly affected plant height, leaf area index (LAI), dry matter accumulation, and grain yield . ”
✓ located verbatim in the source · abstract, characters 940–1074 Other claims from this paper (6) Association observed original result no effect not significant (as stated) measured Claim · model-written summary
The interaction between emergence and spacing variability was not significant.
interactions between the two factors e0 Not reported Taxon Treatment Direction
Verbatim
e0 “interactions between the two factors were not significant ”
✓ located verbatim in the source · abstract, characters 1661–1718 Other claims from this paper (6) Intervention effect observed original result no effect measured Claim · model-written summary
Within-row spacing variation did not affect corn yield .
variation in within-row spacing e0 did not affect e0 Not reported Taxon Comparator
Verbatim
e0 “variation in within-row spacing did not affect yield ”
✓ located verbatim in the source · abstract, characters 1603–1655 Other claims from this paper (6) Exploration of spatial and temporal variability of rainfall and their impact on rice production in Burma in 1901–1939 during the colonial period 7 Show all 7 → Association author interpretation original result measured Claim · model-written summary
Annual and monthly rainfall variability likely influenced rice production.
Not reported Direction
Verbatim
e0 “not only the annual variability of rainfall, but also its monthly variability within a particular year likely influenced rice production ”
✓ located verbatim in the source · abstract, characters 1311–1447 e1 “rice yield reduction in Burma during the colonial period ”
✓ located verbatim in the source · abstract, characters 1594–1650 Other claims from this paper (6) Observation observed original result positive measured Claim · model-written summary
Coastal Zone rice yield was mostly above average before 1910.
average rice yield e0 Verbatim
e0 “Mostly higher than average rice yield was observed before 1910 in the Coastal Zone ”
✓ located verbatim in the source · abstract, characters 1880–1962 Other claims from this paper (6) Observation observed original result measured Claim · model-written summary
Rice yield anomalies distinguished periods of above- and below-average yield despite variable rainfall anomalies.
rice yield anomalies e0 higher or lower e0 Verbatim
e0 “although rainfall anomalies widely differed from period to period, rice yield anomalies clearly showed the distinction of periods with higher or lower rice yield s than average rice yield ”
✓ located verbatim in the source · abstract, characters 1692–1878 Other claims from this paper (6) Spatial–Temporal Analysis of Impacts of Climate Variability on Maize Yield in Kenya 7 Show all 7 → Association author interpretation original result significant (as stated) measured Claim · model-written summary
Climate variability had a significant impact on maize yield in four of six climatological zones.
climate variability e0 four out of six climatological zones e0 Not reported Direction
Verbatim
e0 “climate variability has a significant impact on maize yield for four out of six climatological zones ”
✓ located verbatim in the source · abstract, characters 1060–1160 Other claims from this paper (6) Observation observed original result not significant (as stated) measured Claim · model-written summary
Maximum temperature increased spatially in dry areas without statistical significance.
maximum temperature e0 Not reported Taxon
Verbatim
e0 “increasing trend in maximum temperature in dry areas, albeit not statistically significant ”
✓ located verbatim in the source · abstract, characters 723–813 Other claims from this paper (6) Observation observed original result measured Claim · model-written summary
Maximum temperature, minimum temperature and precipitation showed no trend in the overall data.
maximum temperature, minimum temperature and precipitation e0 Not reported Taxon
Verbatim
e0 “no trend in the data for maximum temperature, minimum temperature and precipitation ”
✓ located verbatim in the source · abstract, characters 375–458 Other claims from this paper (6) Spatial and temporal corn yield variability in the US Corn Belt during the hybrid era 7 Show all 7 → Observation observed original result positive measured Claim · model-written summary
Corn yield stability improved in recent years.
earlier periods e0 Verbatim
e0 “corn yield s demonstrated greater variability in earlier periods, stability has improved in recent years ”
✓ located verbatim in the source · abstract, characters 1213–1316 t0 “corn ”
✓ located verbatim in the source · title, characters 21–25 Other claims from this paper (6) Method / resource observed original result negative measured Claim · model-written summary
NCCPI became less robust for predicting corn yield since 1960.
predicting corn yield e0 Not reported Comparator
Verbatim
e0 “the NCCPI has become less robust for predicting corn yield since 1960 ”
✓ located verbatim in the source · abstract, characters 1136–1205 t0 “corn ”
✓ located verbatim in the source · title, characters 21–25 Other claims from this paper (6) Association observed original result measured Claim · model-written summary
Several Nebraska districts had weaker precipitation-index relationships.
weaker relationships e0 Verbatim
e0 “several CRDs in Nebraska showed weaker relationships ”
✓ located verbatim in the source · abstract, characters 1513–1565 t0 “corn ”
✓ located verbatim in the source · title, characters 21–25 Other claims from this paper (6) UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability 7 Show all 7 → Method / resource observed original result measured Claim · model-written summary
Cross-year baseline prediction had R² −2.9 in 2023.
baseline model e0 Verbatim
e0 “the baseline model (from 2022) performed poorly ( R 2 = −2.9 in 2023) ”
✓ located verbatim in the source · abstract, characters 1120–1189 t0 “winter wheat across temporal and spatial variability ”
✓ located verbatim in the source · title, characters 70–122 Other claims from this paper (6) Method / resource observed original result positive measured Claim · model-written summary
With 20% fine tuning, cross-year prediction improved to R² 0.83.
20% fine‐tuning e0 Not reported Comparator
Verbatim
e0 “DTL improved prediction to an R 2 of 0.83 with 20% fine‐tuning ”
✓ located verbatim in the source · abstract, characters 1197–1259 t0 “winter wheat across temporal and spatial variability ”
✓ located verbatim in the source · title, characters 70–122 Other claims from this paper (6) Method / resource observed original result measured Claim · model-written summary
Cross-location baseline R² ranged from −15.3 to −0.4.
baseline model performance e0 R 2 ranging from −15.3 to −0.4 e0 baseline model e0 Verbatim
e0 “baseline model performance was poor ( R 2 ranging from −15.3 to −0.4) ”
✓ located verbatim in the source · abstract, characters 1345–1414 t0 “winter wheat across temporal and spatial variability ”
✓ located verbatim in the source · title, characters 70–122 Other claims from this paper (6) Maize Temporal Yield Variability under Long‐Term Manure and Fertilizer Application: Fractal Analysis 6 Show all 6 → Intervention effect observed original result no effect measured Claim · model-written summary
Soil fertility amendments did not alleviate yearly maize yield variability .
Soil fertility amendments e0 year‐to‐year variability observed in the corn ( Zea mays L.) yield e0 did not alleviate e0 Not reported Comparator
Verbatim
e0 “Soil fertility amendments did not alleviate year‐to‐year variability observed in the corn ( Zea mays L.) yield ”
✓ located verbatim in the source · abstract, characters 1372–1482 Other claims from this paper (5) Intervention effect observed original result positive measured Claim · model-written summary
Grain yield increased as nitrogen application rose without manure.
increasing N application rate e0 without manure e0 Verbatim
e0 “Grain yield increased with increasing N application rate without manure ”
✓ located verbatim in the source · abstract, characters 966–1037 t0 “Maize ”
✓ located verbatim in the source · title, characters 0–5 Other claims from this paper (5) Intervention effect observed original result no effect measured Claim · model-written summary
Fertilizer did not elicit a yield response where manure was applied.
fertilizer application e0 where manure had been applied e0 Not reported Direction
Verbatim
e0 “no response to fertilizer application was observed where manure had been applied ”
✓ located verbatim in the source · abstract, characters 1043–1123 e1 “Grain yield increased with increasing N application rate without manure ”
✓ located verbatim in the source · abstract, characters 966–1037 t0 “Maize ”
✓ located verbatim in the source · title, characters 0–5 Other claims from this paper (5) Spatio-temporal variability of sugarcane yield efficiency in the state of São Paulo, Brazil 6 Show all 6 → 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) Observation observed original result positive measured Claim · model-written summary
The sugarcane yield gap fell from 58 to 42%.
Verbatim
e0 “yield gap consequently decreased from 58 to 42% ”
✓ located verbatim in the source · abstract, characters 640–687 t0 “sugarcane ”
✓ located verbatim in the source · title, characters 31–40 Other claims from this paper (5) Association observed original result measured Claim · model-written summary
Climatic factors explained 43% of variation in sugarcane yield efficiency, with solar radiation ranked first.
variability of sugarcane yield efficiency e0 solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature e0 Not reported Setting Direction
Verbatim
e0 “Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature ”
✓ located verbatim in the source · abstract, characters 689–907 Other claims from this paper (5) Temporal and Spatial Relationships between Within‐Field Yield Variability in Cotton and High‐Spatial Hyperspectral Remote Sensing Imagery 6 Show all 6 → Association observed original result measured Claim · model-written summary
Within-field variability of yield monitor data collected at harvest was correlated with hyperspectral indices of crop growth, canopy structure, chlorophyll and water content.
yield monitor spatial data e7 Verbatim
e0 “a cotton ( Gossypium hirsutum L.) field ”
✓ located verbatim in the source · abstract, characters 499–538 e7 “variability of yield monitor spatial data collected during harvest was correlated with hyperspectral indices related to crop growth and canopy structure, chlorophyll concentration, and water content ”
✓ located verbatim in the source · abstract, characters 639–837 Other claims from this paper (5) Association observed original result measured Claim · model-written summary
Structural indices related to LAI gave the best relationships with cotton yield and field segmentation at early growth stages.
early growth stages e1 relationships with yield and field segmentation e1 Verbatim
e0 “a cotton ( Gossypium hirsutum L.) field ”
✓ located verbatim in the source · abstract, characters 499–538 e1 “obtained the best relationships with yield and field segmentation at early growth stages ”
✓ located verbatim in the source · abstract, characters 1403–1491 Other claims from this paper (5) Method / resource observed original result measured Claim · model-written summary
The MCARI index reached an overall accuracy of 51% at late preharvest stage, with kappa 0.22.
late preharvest stage e7 overall accuracy e6 Verbatim
e0 “a cotton ( Gossypium hirsutum L.) field ”
✓ located verbatim in the source · abstract, characters 499–538 e6 “obtaining overall accuracy of 51% (κ = 0.22) ”
✓ located verbatim in the source · abstract, characters 1980–2024 e7 “at late preharvest stage ”
✓ located verbatim in the source · abstract, characters 1954–1978 Other claims from this paper (5) Spatio-temporal variability of climatic variables and its impacts on rice yield in Bangladesh 6 Show all 6 → Association observed original result measured Claim · model-written summary
Aus rice yield was influenced by maximum temperature and relative humidity.
maximum temperature and relative humidity e0 Not reported Direction
Verbatim
e0 “the rice yield of Aus (summer) and Aman (wet) seasons were influenced by maximum temperature and relative humidity ”
✓ located verbatim in the source · abstract, characters 1408–1522 Other claims from this paper (5) Association observed original result measured Claim · model-written summary
Aman rice yield was influenced by maximum temperature and relative humidity.
maximum temperature and relative humidity e0 Not reported Direction
Verbatim
e0 “the rice yield of Aus (summer) and Aman (wet) seasons were influenced by maximum temperature and relative humidity ”
✓ located verbatim in the source · abstract, characters 1408–1522 Other claims from this paper (5) Association observed original result measured Claim · model-written summary
Boro rice yield was affected by maximum temperature, rainfall and relative humidity.
maximum temperature, rainfall, and relative humidity e0 Not reported Direction
Verbatim
e0 “the rice yield of the Boro (dry) season was affected by maximum temperature, rainfall, and relative humidity. ”
✓ located verbatim in the source · abstract, characters 1532–1641 Other claims from this paper (5) Predicting spatial and temporal variability in soybean yield using deep learning and open source data 6 Show all 6 → Method / resource observed original result negative measured Claim · model-written summary
Deep learning architectures encountered more challenges in temporal extrapolation of soybean yield , with RRMSE 51% across years.
temporal extrapolation e2 Verbatim
e0 “predicting within-field soybean yield s ”
✓ located verbatim in the source · abstract, characters 208–246 e2 “The DL architectures encountered more challenges with temporal extrapolation (RRMSE 51 % in across-years) ”
✓ located verbatim in the source · abstract, characters 1000–1105 Other claims from this paper (5) Method / resource observed original result no effect measured Claim · model-written summary
There were no substantial differences in soybean yield prediction performance among the deep learning architectures.
no substantial differences e3 DL architectures e3 Verbatim
e0 “predicting within-field soybean yield s ”
✓ located verbatim in the source · abstract, characters 208–246 e3 “There were no substantial differences in performance among the DL architectures ”
✓ located verbatim in the source · abstract, characters 1107–1186 Other claims from this paper (5) Method / resource observed original result positive measured Claim · model-written summary
Deep learning architectures outperformed the process-based baseline in across-field testing of soybean yield prediction (RRMSE 35% vs 40%).
across-fields only e1 Verbatim
e0 “predicting within-field soybean yield s ”
✓ located verbatim in the source · abstract, characters 208–246 e1 “DL architectures outperformed the baseline in testing across-fields only (RRMSE 35 % vs 40 %) ”
✓ located verbatim in the source · abstract, characters 905–998 Other claims from this paper (5) 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.
Oryza sativa
Zea mays
Zea mays subsp. mays
Triticum aestivum
Gossypium hirsutum
Glycine max