Exobasidiaceae 251 claims

family · order Exobasidiales · 30 taxa · NCBI Taxonomy ↗

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251 claims

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Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The ANN outperformed other machine learning models, with a training accuracy of 83% for blister blight classification.

Taxon: Camellia sinensisCamellia sinensise0
Interactor: Exobasidium vexansExobasidium vexanse1pathogen
Outcome: training accuracye2
Value: 83%e2
Qualifier: kappa coefficient = 0.78e2
Comparator: other machine learning modelse2

Verbatim

e0
“Camellia sinensis is a widely cultivated crop”
✓ located verbatim in the source · abstract, characters 9–54

e1
“infection known as Exobasidium vexans”
✓ located verbatim in the source · abstract, characters 157–194

e2
“the ANN outperformed other machine learning models, achieving a training accuracy of 83% (kappa coefficient = 0.78)”
✓ located verbatim in the source · abstract, characters 921–1036

Title

High‐performance hyperspectral remote sensing and machine learning algorithms for detection of blister blight in Camellia sinensis

Manisha; Kishor Chandra Kandpal; Meenakshi; et al. Agronomy Journal 2025. doi:10.1002/agj2.70060

Other claims from this paper (2)

Method / resource The ANN reached a testing accuracy of 92% for blister blight classification.
Method / resource The classification model reached 90% accuracy on Kangra Asha tea leaves not used for training.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The ANN reached a testing accuracy of 92% for blister blight classification.

Taxon: Camellia sinensisCamellia sinensise0
Interactor: Exobasidium vexansExobasidium vexanse1pathogen
Outcome: testing accuracye3
Value: 92%e3
Qualifier: kappa coefficient = 0.90e3

Verbatim

e0
“Camellia sinensis is a widely cultivated crop”
✓ located verbatim in the source · abstract, characters 9–54

e1
“infection known as Exobasidium vexans”
✓ located verbatim in the source · abstract, characters 157–194

e3
“a testing accuracy of 92% (kappa coefficient = 0.90)”
✓ located verbatim in the source · abstract, characters 1041–1093

Title

High‐performance hyperspectral remote sensing and machine learning algorithms for detection of blister blight in Camellia sinensis

Manisha; Kishor Chandra Kandpal; Meenakshi; et al. Agronomy Journal 2025. doi:10.1002/agj2.70060

Other claims from this paper (2)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The classification model reached 90% accuracy on Kangra Asha tea leaves not used for training.

Taxon: Camellia sinensisCamellia sinensise0
Material: Kangra Ashae4
Interactor: Exobasidium vexansExobasidium vexanse1pathogen
Outcome: classification accuracye4
Value: 90%e4
Qualifier: kappa coefficient = 0.86e4

Verbatim

e0
“Camellia sinensis is a widely cultivated crop”
✓ located verbatim in the source · abstract, characters 9–54

e1
“infection known as Exobasidium vexans”
✓ located verbatim in the source · abstract, characters 157–194

e4
“The classification model was tested on another set of Kangra Asha tea leaves, resulting in a classification accuracy of 90% (kappa coefficient = 0.86)”
✓ located verbatim in the source · abstract, characters 1095–1245

Title

High‐performance hyperspectral remote sensing and machine learning algorithms for detection of blister blight in Camellia sinensis

Manisha; Kishor Chandra Kandpal; Meenakshi; et al. Agronomy Journal 2025. doi:10.1002/agj2.70060

Other claims from this paper (2)

Method / resource The ANN outperformed other machine learning models, with a training accuracy of 83% for blister blight classification.
Method / resource The ANN reached a testing accuracy of 92% for blister blight classification.

Intervention effectobservedoriginal resultpositivesignificant (as stated)measured

Claim · model-written summary

Vermi-derma bioformulation treatments significantly reduced blister blight in trial plots.

Taxon: Camellia sinensis (L.) O. KuntzeCamellia sinensist0
Treatment: various treatments of Vermi-derma bioformulationse0
Interactor: Exobasidium vexansExobasidium vexanse1pathogene0
Outcome: blister blight diseasee0
Direction: reductione0
Setting: trail plotse0

Not reportedComparator

Verbatim

e0
“there was a significant reduction in blister blight disease in the trail plots after imposing various treatments of Vermi-derma bioformulations.”
✓ located verbatim in the source · abstract, characters 806–950

t0
“Camellia sinensis (L.) O. Kuntze”
✓ located verbatim in the source · title, characters 76–108

e1
“Blister blight disease caused by an obligate fungal pathogen, Exobasidium vexans”
✓ located verbatim in the source · abstract, characters 0–80

Title

Evaluation of Vermi-Derma bioformulations against blister blight disease of Camellia sinensis (L.) O. Kuntze

Sappanimuthu Parathiraj; Ponnusamy Ponmurugan; Devaraj Mounika; et al. Current Botany 2025. doi:10.25081/cb.2025.v16.9454

Other claims from this paper (5)

Intervention effect Copper oxychloride plus Contaf provided 72.42±2.08% disease protection.
Intervention effect T. harzianum amended Vermi-derma at 1:20 gave the highest green leaf yield, 5401±2.27 kg ha-1.
Intervention effect The same treatment increased biometric traits, physiological traits and biochemical constituents.
Intervention effect P. fluorescens amended Vermi-derma matched S. sannanensis amended Vermi-derma for disease control and green leaf yield.
Mechanism The authors attributed improved parameters to recovery of leaves from E. vexans infection through the bioformulations.

Mechanismhypothesisoriginal resultmeasured

Claim · model-written summary

The authors attributed improved parameters to recovery of leaves from E. vexans infection through the bioformulations.

Taxon: Camellia sinensis (L.) O. KuntzeCamellia sinensist0
Organ / stage: leavese0
Treatment: Vermi-derma bioformulationse0
Interactor: E. vexansExobasidium vexanse0pathogen
Outcome: recovery of leaves from E. vexans infectione0

Verbatim

e0
“Increasing all these parameters might be due to the recovery of leaves from E. vexans infection by the action of Vermi-derma bioformulations.”
✓ located verbatim in the source · abstract, characters 1563–1704

t0
“Camellia sinensis (L.) O. Kuntze”
✓ located verbatim in the source · title, characters 76–108

Title

Evaluation of Vermi-Derma bioformulations against blister blight disease of Camellia sinensis (L.) O. Kuntze

Sappanimuthu Parathiraj; Ponnusamy Ponmurugan; Devaraj Mounika; et al. Current Botany 2025. doi:10.25081/cb.2025.v16.9454

Other claims from this paper (5)

Intervention effect Vermi-derma bioformulation treatments significantly reduced blister blight in trial plots.
Intervention effect Copper oxychloride plus Contaf provided 72.42±2.08% disease protection.
Intervention effect T. harzianum amended Vermi-derma at 1:20 gave the highest green leaf yield, 5401±2.27 kg ha-1.
Intervention effect The same treatment increased biometric traits, physiological traits and biochemical constituents.
Intervention effect P. fluorescens amended Vermi-derma matched S. sannanensis amended Vermi-derma for disease control and green leaf yield.

Observationobservedoriginal resultbasis n/a

Claim · model-written summary

Exobasidium setsutaiense was proposed as the agent of leaf blister on Rhododendron semibarbatum.

Taxon: Rhododendron semibarbatumRhododendron semibarbatume0
Interactor: Exobasidium setsutaienseExobasidium setsutaiensee0pathogen
Outcome: leaf blistere0

Verbatim

e0
“Exobasidium setsutaiense sp. nov. is proposed to accommodate the causal agent of leaf blister on Rhododendron semibarbatum”
✓ located verbatim in the source · abstract, characters 0–122

Title

Exobasidium setsutaiense sp. nov. (Exobasidiaceae) causing leaf blister on Rhododendron semibarbatum in Japan

HIDEYUKI NAGAO; TAKAMICHI ORIHARA; TAIGA KASUYA Phytotaxa 2025. doi:10.11646/phytotaxa.684.1.4

Other claims from this paper (2)

Observationobservedoriginal resultmeasured

Claim · model-written summary

The leaf blister presented chlorotic spots and thickened lesions caused by spongy mesophyll hyperplasia.

Taxon: Rhododendron semibarbatumRhododendron semibarbatumt0
Organ / stage: spongy mesophyll cellse0
Interactor: Exobasidium setsutaienseExobasidium setsutaienset0pathogen
Outcome: chlorotic leaf spote0

Verbatim

e0
“The leaf blister was characterized by chlorotic leaf spot where the lesion was slightly thickened by the hyperplasia of spongy mesophyll cells”
✓ located verbatim in the source · abstract, characters 562–704

t0
“Exobasidium setsutaiense sp. nov. (Exobasidiaceae) causing leaf blister on Rhododendron semibarbatum in Japan”
✓ located verbatim in the source · title, characters 0–109

Title

Exobasidium setsutaiense sp. nov. (Exobasidiaceae) causing leaf blister on Rhododendron semibarbatum in Japan

HIDEYUKI NAGAO; TAKAMICHI ORIHARA; TAIGA KASUYA Phytotaxa 2025. doi:10.11646/phytotaxa.684.1.4

Other claims from this paper (2)

Mechanismhypothesisoriginal resultnegativebasis n/a

Claim · model-written summary

The authors propose that dominant pathogenic genera interact with other fungi and exacerbate damage and microbiome change.

Taxon: Larix sibirica Ledeb.Larix sibiricat0
Interactor: FusariumFusariume0pathogen
Second interactor: ExobasidiumExobasidiume0other
Outcome: exacerbating damage and altering the microbiomee0
Qualifier: particularly under pollution-induced stresse0

Verbatim

e0
“The dominant pathogenic genera detected – Fusarium, Alternaria, Valsa, and Cytospora – likely interact with other fungi such as Exobasidium, Ophiognomonia, Sarocladium, Phomopsis, and Taphrina, exacerbating damage and altering the microbiome, particularly under pollution-induced stress.”
✓ located verbatim in the source · abstract, characters 1328–1615

t0
“Larix sibirica Ledeb.”
✓ located verbatim in the source · title, characters 34–55

Title

Fungal microbiome biodiversity in Larix sibirica Ledeb. needles under biotic and technogenic stress in the Arctic

Miroshnikova, Ksenia A.; Litovka, Yulia A.; Timofeev, Anton A.; et al. Zenodo (CERN European Organization for Nuclear Research) 2025. doi:10.5281/zenodo.17983022

Other claims from this paper (4)

Observationobservedoriginal resultmeasured

Claim · model-written summary

Colonies of E. vexans emerged from 13 of 180 tea lesion leaf pieces examined (8.1%) by tissue isolation.

Taxon: Teat0
Interactor: E. vexansExobasidium vexanse0pathogen
Outcome: emerged from 13 leaf pieces in 180 leaf pieces examinede0
Value: 8.1%e0

Verbatim

e0
“colonies of E. vexans emerged from 13 leaf pieces in 180 leaf pieces examined (8.1%)”
✓ located verbatim in the source · abstract, characters 160–244

t0
“Tea”
✓ located verbatim in the source · title, characters 70–73

Title

Isolation of Exobasidium vexans from the Lesions of Blister Blight of Tea and the Prevalence of Anamorphic Structures in Culture

Hideyuki Nagao; Takamichi Orihara; Taiga Kasuya Chagyo Kenkyu Hokoku (Tea Research Journal) 2024. doi:10.5979/cha.2024.138_23

Other claims from this paper (5)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

For red leaf disease, the combination dataset gave the highest mAP 50 (0.848 ± 0.140), against 0.615 ± 0.092 for ground truth.

Taxon: wild blueberryt0
Material: combination datasete4
Interactor: Exobasidium vacciniiExobasidium vacciniie3pathogen
Outcome: mAP 50e4
Value: 0.848 ± 0.140e4
Comparator: ground truthe4

Verbatim

t0
“wild blueberry automation”
✓ located verbatim in the source · title, characters 71–96

e3
“hair fescue weeds ( Festuca filiformis Pourr.), and red leaf disease ( Exobasidium vaccinii )”
✓ located verbatim in the source · abstract, characters 1028–1121

e4
“In detecting red leaf disease, the combination dataset showed the best performance (mAP 50 : 0.848 ± 0.140, mAP 50–95 : 0.607 ± 0.219), compared to the ground truth (mAP 50 : 0.615 ± 0.092, mAP 50–95 : 0.417 ± 0.045) and generated datasets (mAP 50 : 0.245 ± 0.088, mAP 50–95 : 0.144 ± 0.059)”
✓ located verbatim in the source · abstract, characters 1893–2184

Title

Optimizing data collection requirements for machine learning models in wild blueberry automation through the application of DALL-E 2

Connor C. Mullins; Travis J. Esau; Qamar U. Zaman; et al. Smart Agricultural Technology 2024. doi:10.1016/j.atech.2024.100764

Other claims from this paper (7)