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Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The four-strain Bacillus consortium showed endo-β-1,4-glucanase of 154.67 U/mL.

Outcome: endo-β-1,4-glucanasee1
Value: 154.67 U/mLe1

Not reportedComparator

Verbatim

e1
“endo-β-1,4-glucanase (154.67 U/mL)”
✓ located verbatim in the source · abstract, characters 616–650

Title

Construction and Functional Validation of a Cross-Niche Multifunctional Microbial Consortium for Straw-Returning Agricultural Systems

Shu Jia; Hang Qu; Bo Li; et al. Microorganisms 2026. doi:10.3390/microorganisms14010135

Other claims from this paper (9)

Method / resource The four-strain Bacillus consortium showed manganese peroxidase of 7709.33 U/L.
Method / resource The four-strain Bacillus consortium showed laccase of 450.65 U/L.
Method / resource The four-strain Bacillus consortium showed filter paper activity of 309.18 U/L.
Intervention effect The consortium significantly enhanced rice straw degradation by 37.18% relative to the control.
Intervention effect The consortium increased nitrogen release from rice straw by 16.13% relative to the control.
Intervention effect The consortium inhibited Magnaporthe oryzae with a 67.56% inhibition rate.
Intervention effect The consortium reduced the incidence rate and disease index of leaf blast and panicle blast.
Intervention effect In field trials the consortium applied alone increased rice grain yield by 9.63% and 6.94%.
Intervention effect In field trials the consortium co-applied with straw residues increased rice grain yield by 6.75% and 5.18%.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The four-strain Bacillus consortium showed filter paper activity of 309.18 U/L.

Outcome: filter paper activitye1
Value: 309.18 U/Le1

Not reportedComparator

Verbatim

e1
“filter paper activity (309.18 U/L)”
✓ located verbatim in the source · abstract, characters 656–690

Title

Construction and Functional Validation of a Cross-Niche Multifunctional Microbial Consortium for Straw-Returning Agricultural Systems

Shu Jia; Hang Qu; Bo Li; et al. Microorganisms 2026. doi:10.3390/microorganisms14010135

Other claims from this paper (9)

Method / resource The four-strain Bacillus consortium showed manganese peroxidase of 7709.33 U/L.
Method / resource The four-strain Bacillus consortium showed laccase of 450.65 U/L.
Method / resource The four-strain Bacillus consortium showed endo-β-1,4-glucanase of 154.67 U/mL.
Intervention effect The consortium significantly enhanced rice straw degradation by 37.18% relative to the control.
Intervention effect The consortium increased nitrogen release from rice straw by 16.13% relative to the control.
Intervention effect The consortium inhibited Magnaporthe oryzae with a 67.56% inhibition rate.
Intervention effect The consortium reduced the incidence rate and disease index of leaf blast and panicle blast.
Intervention effect In field trials the consortium applied alone increased rice grain yield by 9.63% and 6.94%.
Intervention effect In field trials the consortium co-applied with straw residues increased rice grain yield by 6.75% and 5.18%.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The fine-tuned EfficientNetB0 model achieved 99.51% test accuracy in detecting crop diseases.

Outcome: test accuracye0
Value: 99.51%e0

Verbatim

e0
“It achieved 99.51% test accuracy with a loss of 0.0165”
✓ located verbatim in the source · abstract, characters 797–851

Title

Crop disease detection using EfficientNetB0 deep learning approach for precision agriculture

Muhammad Subhan; Nadim Rana; Farhan Qamar; et al. Discover Computing 2026. doi:10.1007/s10791-025-09881-y

Other claims from this paper (1)

Method / resource The model had a test loss of 0.0165.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The model had a test loss of 0.0165.

Outcome: losse0
Value: 0.0165e0

Verbatim

e0
“It achieved 99.51% test accuracy with a loss of 0.0165”
✓ located verbatim in the source · abstract, characters 797–851

Title

Crop disease detection using EfficientNetB0 deep learning approach for precision agriculture

Muhammad Subhan; Nadim Rana; Farhan Qamar; et al. Discover Computing 2026. doi:10.1007/s10791-025-09881-y

Other claims from this paper (1)

Method / resource The fine-tuned EfficientNetB0 model achieved 99.51% test accuracy in detecting crop diseases.

Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

The 3K array and GBS-based SNPs performed similarly for training population optimization, forward prediction, and univariate and multivariate genomic prediction of forage yield in oat.

Taxon: oatAvena sativat0
Outcome: performancee0
Direction: similare0
Comparator: GBS-based SNPse0

Verbatim

e0
“similar performance of both the 3K array and GBS-based SNPs in terms of training population optimization, forward prediction, and univariate and multivariate genomic prediction of forage yield”
✓ located verbatim in the source · abstract, characters 702–894

t0
“biomass yield in oat”
✓ located verbatim in the source · title, characters 114–134

Title

Effectiveness of low‐density high‐throughput marker platform and easy‐to‐measure traits for genomic prediction of biomass yield in oat ( Avena sativa L.)

Samuel A. Adewale; Md Ali Babar; Diego Jarquin; et al. The Plant Genome 2026. doi:10.1002/tpg2.70179

Other claims from this paper (4)

Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

GBLUP, Bayes-B and random forest models gave similar predictive ability for dry matter yield across harvest-year combinations and both marker platforms.

Taxon: oatAvena sativat0
Outcome: predictive ability for dry matter yield (DMY)e0
Direction: similare0
Comparator: Bayes-Be0

Verbatim

e0
“The genomic best linear unbiased prediction (GBLUP), Bayes-B, and random forest models gave similar predictive ability for dry matter yield (DMY)”
✓ located verbatim in the source · abstract, characters 896–1041

t0
“biomass yield in oat”
✓ located verbatim in the source · title, characters 114–134

Title

Effectiveness of low‐density high‐throughput marker platform and easy‐to‐measure traits for genomic prediction of biomass yield in oat ( Avena sativa L.)

Samuel A. Adewale; Md Ali Babar; Diego Jarquin; et al. The Plant Genome 2026. doi:10.1002/tpg2.70179

Other claims from this paper (4)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Multivariate models with secondary traits gave more than twofold higher predictive abilities than univariate models.

Taxon: oatAvena sativat0
Outcome: predictive abilitiese0
Direction: increasese0
Value: more than twofolde0
Comparator: univariate modelse0

Verbatim

e0
“The multivariate models involving various combinations of secondary traits (simple breeders' field notes and data) resulted in more than twofold increases in predictive abilities compared to the univariate models”
✓ located verbatim in the source · abstract, characters 1112–1324

t0
“biomass yield in oat”
✓ located verbatim in the source · title, characters 114–134

Title

Effectiveness of low‐density high‐throughput marker platform and easy‐to‐measure traits for genomic prediction of biomass yield in oat ( Avena sativa L.)

Samuel A. Adewale; Md Ali Babar; Diego Jarquin; et al. The Plant Genome 2026. doi:10.1002/tpg2.70179

Other claims from this paper (4)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The overlap between top 25% observed and predicted genotypes was higher for multivariate GBLUP models (30.10%-66.99%) than univariate models (27.18%-51.46%).

Taxon: oatAvena sativat0
Outcome: overlap percentagee0
Direction: highere0
Value: 30.10%-66.99%e0
Qualifier: 27.18%-51.46%e0
Comparator: univariate modelse0

Verbatim

e0
“a higher overlap percentage (30.10%-66.99%) for multivariate GBLUP models compared to the univariate models (27.18%-51.46%)”
✓ located verbatim in the source · abstract, characters 1403–1526

t0
“biomass yield in oat”
✓ located verbatim in the source · title, characters 114–134

Title

Effectiveness of low‐density high‐throughput marker platform and easy‐to‐measure traits for genomic prediction of biomass yield in oat ( Avena sativa L.)

Samuel A. Adewale; Md Ali Babar; Diego Jarquin; et al. The Plant Genome 2026. doi:10.1002/tpg2.70179

Other claims from this paper (4)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The point-based UAV counting method gave its highest accuracy, within ±12% of ground-truth with R 2 = 0.81, when imagery was collected 14 to 20 DAP at 15.2-m altitude.

Taxon: soybeanGlycine maxt0
Outcome: accuracye1
Direction: higheste1
Value: within ±12% of ground‐truth; R 2 = 0.81e1
Qualifier: between 14 and 20 DAP at 15.2‐m altitudee1

Verbatim

t0
“stand counts in soybean”
✓ located verbatim in the source · title, characters 41–64

e1
“The point‐based method provided the highest accuracy (within ±12% of ground‐truth; R 2 = 0.81) when imagery was collected between 14 and 20 DAP at 15.2‐m altitude”
✓ located verbatim in the source · abstract, characters 853–1015

Title

Optimizing unmanned aerial vehicle–based stand counts in soybean: Effects of flight timing, altitude, and analytical method

Salem Ermish; Rachel Vann; Jason Ward; et al. Agronomy Journal 2026. doi:10.1002/agj2.70303

Other claims from this paper (7)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

On-ground calibration areas improved accuracy by an average of 28% and up to 48% for the line-based approach in narrow rows.

Taxon: soybeanGlycine maxt0
Treatment: on‐ground calibration arease1
Outcome: accuracye1
Direction: improvede1
Value: an average of 28% and up to 48%e1

Verbatim

t0
“stand counts in soybean”
✓ located verbatim in the source · title, characters 41–64

e1
“Incorporating on‐ground calibration areas improved accuracy by an average of 28% and up to 48% for the line‐based approach in narrow rows”
✓ located verbatim in the source · abstract, characters 1254–1391

Title

Optimizing unmanned aerial vehicle–based stand counts in soybean: Effects of flight timing, altitude, and analytical method

Salem Ermish; Rachel Vann; Jason Ward; et al. Agronomy Journal 2026. doi:10.1002/agj2.70303

Other claims from this paper (7)

Method / resource 684,532 claims

684,532 claims