View: List Claim type Research area Organism Taxon as written Decade Paper Method / resource observed original result positive measured Claim · model-written summary
Midday SWP was sometimes accurately predicted from midmorning SWP and VPD change.
Almonds, Walnuts, and Prunes t0 midday SWP was accurately predicted e0 On some occasions e0 midmorning SWP e0 Verbatim
e0 “On some occasions, midday SWP was accurately predicted from midmorning SWP and the change in air vapor pressure deficit (VPD) from midmorning to midday ”
✓ located verbatim in the source · abstract, characters 1648–1799 t0 “Almonds, Walnuts, and Prunes ”
✓ located verbatim in the source · title, characters 79–107 Other claims from this paper (7) Method / resource observed original result positive measured Claim · model-written summary
Random forest regression estimated SWP better than the linear model.
RMSE = 3.3742 (-1*swp (bars)) e0 Verbatim
e0 “random forest regression to estimate SWP and received even better results (R2 = 0.6709; RMSE = 3.3742 (-1* swp (bars))) ”
✓ located verbatim in the source · abstract, characters 1026–1144 t0 “Cotton ”
✓ located verbatim in the source · title, characters 25–31 Other claims from this paper (6) Method / resource observed original result positive measured Claim · model-written summary
Quadratic fits between SWP and the four vegetation indices gave R2 around 0.7.
Verbatim
e0 “around 0.7 in all cases ”
✓ located verbatim in the source · abstract, characters 1753–1776 t0 “grapefruit trees ”
✓ located verbatim in the source · title, characters 85–101 e1 “SWP and aforementioned indices ”
✓ located verbatim in the source · abstract, characters 1673–1703 Other claims from this paper (7) Method / resource observed original result positive measured Claim · model-written summary
SWP -LeafNET was distributable and faster than other methods.
distributable and considerably faster e0 other methods e0 Verbatim
e0 “SWP -LeafNET is distributable and considerably faster than other methods because of using shallower models with fewer parameters asynchronously ”
✓ located verbatim in the source · abstract, characters 1725–1867 Other claims from this paper (3) Method / resource observed original result measured Claim · model-written summary
CWSI_T33% produced similar SWP –CWSI models across extraction methods.
similar SWP–CWSI models e0 canopy extraction method e0 Not reported Direction
Verbatim
e0 “The CWSI_T33% dataset produced similar SWP –CWSI models irrespective of the canopy extraction method used ”
✓ located verbatim in the source · abstract, characters 1611–1715 t0 “commercial peach orchard ”
✓ located verbatim in the source · abstract, characters 869–893 Other claims from this paper (9) Method / resource observed original result measured Claim · model-written summary
A linear regression of midday SWP on the 940 nm band reached R2 0.61.
in a range between -0.7 and -1.6 MPa of SWP e4 Verbatim
e0 “the midday SWP in mandarin trees submitted to severe water stress in different phenological phases ”
✓ located verbatim in the source · abstract, characters 1236–1334 e2 “=0.61) and SWP (MPa) = -13.043 ”
✓ located verbatim in the source · abstract, characters 2495–2525 e4 “These relationships were obtained with three different fruit diameters (35, 50 and 65 mm) and in a range between -0.7 and -1.6 MPa of SWP ”
✓ located verbatim in the source · abstract, characters 2577–2714 Other claims from this paper (4) Method / resource observed original result positive measured Claim · model-written summary
NDI45 was the best linear-regression predictor of cotton SWP .
best performance e0 RMSE = 3.6802 (-1*swp (bars)) e0 Verbatim
e0 “normalized difference index 45 (NDI45) achieved the best performance (R2 = 0.6269; RMSE = 3.6802 (-1* swp (bars))) ”
✓ located verbatim in the source · abstract, characters 864–977 t0 “Cotton ”
✓ located verbatim in the source · title, characters 25–31 Other claims from this paper (6) Method / resource observed original result positive measured Claim · model-written summary
Random Forest predicted almond SWP with R² 0.79 in independent Plot A.
Verbatim
e0 “Plot A: R² = 0.79 for SWP , 0.78 for TGR, and 0.87 for yield ”
✓ located verbatim in the source · abstract, characters 802–861 t0 “almond orchards ”
✓ located verbatim in the source · title, characters 55–70 Other claims from this paper (7) Method / resource observed original result measured Claim · model-written summary
A linear regression of midday SWP on the 1250 nm band reached R2 0.69.
in a range between -0.7 and -1.6 MPa of SWP e4 Verbatim
e0 “the midday SWP in mandarin trees submitted to severe water stress in different phenological phases ”
✓ located verbatim in the source · abstract, characters 1236–1334 e3 “=0.69) ”
✓ located verbatim in the source · abstract, characters 2569–2575 e4 “These relationships were obtained with three different fruit diameters (35, 50 and 65 mm) and in a range between -0.7 and -1.6 MPa of SWP ”
✓ located verbatim in the source · abstract, characters 2577–2714 Other claims from this paper (4) Method / resource observed original result positive measured Claim · model-written summary
The best SWP prediction fit used NDGI and had R2 0.749 over -0.5 to -2.3 MPa.
between -0.5 and -2.3 MPa e1 Verbatim
e0 “0.749 ”
✓ located verbatim in the source · abstract, characters 1878–1883 t0 “grapefruit trees ”
✓ located verbatim in the source · title, characters 85–101 e1 “to predict SWP values between -0.5 and -2.3 MPa ”
✓ located verbatim in the source · abstract, characters 1885–1932 Other claims from this paper (7) 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.
Gossypium hirsutum_Pompelino_Grapefruit_002.jpg?width=60){kind=small}
Citrus
Prunus persica
Prunus dulcis