View: List Claim type Research area Organism Taxon as written Decade Paper 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.
Outcometake 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) Recommendation author interpretation original result basis n/a Claim · model-written summary
Yield maps may be unhelpful for future management when temporal variability is great.
Outcomemay not be useful in making future management decisions e0 Qualifierwhen temporal variability is great e0 Verbatim
e0 “Yield maps, which are used as an indication of past management in site‐specific cases, may not be useful in making future management decisions when temporal variability is great. ”
✓ located verbatim in the source · abstract, characters 1623–1801 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
Fields with high spatial variability and a clear temporal stability pattern have great potential for long-term site-specific management of crop inputs.
Outcomelong-term site-specific management of crop inputs e1 Qualifierhigh spatial variability and a clear temporal stability pattern e1 Verbatim
t0 “Irrigated Cotton Yield in the Southern High Plains ”
✓ located verbatim in the source · title, characters 31–81 e1 “Fields with high spatial variability and a clear temporal stability pattern have great potential for long-term site-specific management of crop inputs ”
✓ located verbatim in the source · abstract, characters 1378–1528 Other claims from this paper (8) 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.
Outcomeestimate next year's N fertilizer requirement e0 Qualifierapparent 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) Recommendation author interpretation original result basis n/a Claim · model-written summary
ECa-based site-specific management is limited to cotton fields with high spatial variability and a strong association between yield and ECa patterns.
Outcomeapplication of ECa for site-specific management e1 Qualifierlimited to fields with high spatial variability e1 Verbatim
t0 “Irrigated Cotton Yield in the Southern High Plains ”
✓ located verbatim in the source · title, characters 31–81 e1 “The application of ECa for site-specific management is limited to fields with high spatial variability and with a strong association between yield spatial and temporal patterns and ECa variation patterns ”
✓ located verbatim in the source · abstract, characters 1012–1215 Other claims from this paper (8) Recommendation author interpretation original result positive basis n/a Claim · model-written summary
The authors recommend region-specific fertilizer rates based on spatial and temporal soil nutrient variation.
Outcomeconfirm the optimal fertilizer level e0 Verbatim
e0 “different ecological regions should follow the spatial and temporal variability of soil available nutrient in cotton field at flower and boll stage to confirm the optimal fertilizer level ”
✓ located verbatim in the source · abstract, characters 2302–2489 Other claims from this paper (15) Observation Soil alkali-hydrolyzable nitrogen under N0 decreased then increased during growth. Observation In other nitrogen treatments, soil alkali-hydrolyzable nitrogen fell, rose after topdressing, fell again, then rose after boll opening. Observation Soil available phosphorus fell and then rose at both locations. Observation Soil available potassium fell and then rose at both locations. Observation Available soil nutrients decreased with soil depth. Observation In Nanjing fertilized plots, soil alkali-hydrolyzable nitrogen decreased farther from cotton plants. Observation In Nanjing fertilized plots, soil available phosphorus decreased farther from cotton plants. Observation Under N0, soil alkali-hydrolyzable nitrogen and phosphorus had no significant horizontal variation. Observation Soil alkali-hydrolyzable nitrogen varied more across space and time in Nanjing than Anyang. Observation Soil available phosphorus varied more across space and time in Anyang than Nanjing. Observation Soil available potassium decreased farther from cotton plants in Nanjing 0–60 cm layers and Anyang 20–60 cm layers. Observation Soil available potassium increased farther from cotton plants in Anyang 0–20 cm layers. Intervention effect At 360 kg ha-1 in Anyang, cotton yield components were relatively optimal and yield maximal. Intervention effect At 240 kg ha-1 in Nanjing, cotton yield was maximal. Intervention effect At the stated regional nitrogen levels, cotton fiber length and strength were better. Recommendation author interpretation original result basis n/a Claim · model-written summary
The authors conclude that site-specific yield -map fertilizer recommendations may not be possible without identifying causes of yield variability .
Outcomefertilizer recommendations on a site specific basis e7 Qualifierwithout identifying agents causing the grain yield variability e7 Verbatim
t0 “Corn Grain Yield s ”
✓ located verbatim in the source · title, characters 34–51 e7 “Using grain yield maps for fertilizer recommendations on a site specific basis may not be possible without identifying agents causing the grain yield variability ”
✓ located verbatim in the source · abstract, characters 6419–6580 Other claims from this paper (7) Recommendation author interpretation original result basis n/a Claim · model-written summary
Such variability should be considered for effective application of nutrients in agroforestry.
Outcomeeffective application of nutrients e5 Verbatim
e5 “Such variability should be considered for effective application of nutrients in agroforestry ”
✓ located verbatim in the source · abstract, characters 2404–2496 e0 “maize height, grain yield , and leaf nitrogen (N) concentrations were significantly higher at the upslope than downslope side of tree-grass rows ”
✓ located verbatim in the source · abstract, characters 1023–1166 Other claims from this paper (6) Recommendation author interpretation original result basis n/a Claim · model-written summary
Yield data can be used to delineate zones for variable management.
Outcomedelineate zones for variable management e4 Verbatim
t0 “crop yield zones on hummocky terrain ”
✓ located verbatim in the source · title, characters 66–102 e4 “Yield data can be used to delineate zones for variable management ”
✓ located verbatim in the source · abstract, characters 1686–1751 Other claims from this paper (3) Recommendation author interpretation original result positive basis n/a Claim · model-written summary
The authors recommend supplemental irrigation to improve sugarcane yield under future climate change.
Treatmentsupplemental irrigation e0 Outcomeimprove sugarcane yield e0 Verbatim
e0 “supplemental irrigation can be used to increase soil moisture content to improve sugarcane yield ”
✓ located verbatim in the source · abstract, characters 2832–2928 Other claims from this paper (17) Observation Projected sugarcane dry-matter yield increases under RCP4.5 were 3.6, 4.7 and 5.8 t ha−1 for the 2030s, 2060s and 2090s against baseline. Observation Projected sugarcane dry-matter yield increases under RCP8.5 were 2.9, 5.4 and 8.5 t ha−1 for the 2030s, 2060s and 2090s against baseline. Observation Projected sugarcane sucrose yield increases under RCP4.5 were 5.2, 7.0 and 8.3 t ha−1 across the future periods. Observation Projected sugarcane sucrose yield increases under RCP8.5 were 4.3, 7.2 and 10.8 t ha−1 across the future periods. Association Sugarcane yield had no significant relationship with solar radiation changes. Association Sugarcane yield was significantly correlated with rainfall changes. Association Sugarcane yield was significantly correlated with temperature changes. Association Combined radiation, rainfall, temperature and elevated CO2 changes may explain 69% of sugarcane DM yield changes. Association Combined radiation, rainfall, temperature and elevated CO2 changes may explain 76% of sugarcane sucrose yield changes. Association Increased temperature caused a small increase in sugarcane yield. Association Increased rainfall significantly increased sugarcane yield until a limit was exceeded. Association Sugarcane yield decreased when rainfall exceeded a certain limit. Association Sucrose yield increased with temperature at constant radiation. Association Sucrose yield decreased when radiation exceeded a certain limit. Association Temperature changes increased sucrose yield only when radiation and temperature increased together. Association Rainfall increased sucrose yield, though the amplitude was limited. Association Radiation increased sucrose yield, though the amplitude was limited. 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.