Try:droughtFusariumnitrogen fertilizerArabidopsisseed germination
Claim · model-written summary
A tiered system architecture framework for IoT-based precision irrigation and crop monitoring has been developed.
Not reportedComparator
Verbatim
e0“A tiered system architecture framework has been developed”
Title
Mohamed Elhoseny; Khadija Jahid; Rachid Latif; et al. Scientific African 2026. doi:10.1016/j.sciaf.2026.e03222
Claim · model-written summary
Case studies illustrate that IoT technologies can address resource usage and improve yield outcomes.
Not reportedComparator
Verbatim
e0“case studies illustrate how these technologies can address resource usage and improve yield outcomes”
Title
Mohamed Elhoseny; Khadija Jahid; Rachid Latif; et al. Scientific African 2026. doi:10.1016/j.sciaf.2026.e03222
Claim · model-written summary
EUKARYOME detected more mycorrhizal taxa than MaarjAM for SSU (AM fungi).
Verbatim
e0“EUKARYOME detected more mycorrhizal taxa compared to MaarjAM for SSU (AM fungi) and UNITE for ITS2 (ectomycorrhizal fungi)”
Title
Camille Truong; Adriana Corrales; Bethan Manley; et al. Biodiversity and Conservation 2026. doi:10.1007/s10531-026-03277-0
Claim · model-written summary
EUKARYOME detected more mycorrhizal taxa than UNITE for ITS2 (ectomycorrhizal fungi).
Verbatim
e0“EUKARYOME detected more mycorrhizal taxa compared to MaarjAM for SSU (AM fungi) and UNITE for ITS2 (ectomycorrhizal fungi)”
Title
Camille Truong; Adriana Corrales; Bethan Manley; et al. Biodiversity and Conservation 2026. doi:10.1007/s10531-026-03277-0
Claim · model-written summary
GL-MobFormer achieved a classification accuracy of 95.13% on the tea leaf image dataset.
Verbatim
t0“tea leaf phytopathogen diagnosis”
e0“GL-MobFormer achieved a classification accuracy of 95.13%”
Title
Bridging CNNs and vision transformers for efficient tea leaf phytopathogen diagnosis: GL-MobFormer
Yuntong Yang; Xiaosong Li; Qinzi Li; et al. Frontiers in Plant Science 2026. doi:10.3389/fpls.2026.1814962
Claim · model-written summary
GL-MobFormer reached a Matthews Correlation Coefficient of 0.9417.
Verbatim
t0“tea leaf phytopathogen diagnosis”
e0“a Matthews Correlation Coefficient (MCC) of 0.9417”
Title
Bridging CNNs and vision transformers for efficient tea leaf phytopathogen diagnosis: GL-MobFormer
Yuntong Yang; Xiaosong Li; Qinzi Li; et al. Frontiers in Plant Science 2026. doi:10.3389/fpls.2026.1814962
Claim · model-written summary
GL-MobFormer maintained its performance with a low computational footprint of 0.33 G FLOPs.
Verbatim
t0“tea leaf phytopathogen diagnosis”
e0“a low computational footprint of merely 0.33 G FLOPs”
Title
Bridging CNNs and vision transformers for efficient tea leaf phytopathogen diagnosis: GL-MobFormer
Yuntong Yang; Xiaosong Li; Qinzi Li; et al. Frontiers in Plant Science 2026. doi:10.3389/fpls.2026.1814962
Claim · model-written summary
Masking only the top 5% of critical activation regions reduced classification confidence by an average of 70.61%, indicating the model relies on lesion features rather than background.
Verbatim
t0“tea leaf phytopathogen diagnosis”
e0“systematically masking only the top 5% of critical activation regions led to an average reduction of 70.61% in classification confidence”
Title
Bridging CNNs and vision transformers for efficient tea leaf phytopathogen diagnosis: GL-MobFormer
Yuntong Yang; Xiaosong Li; Qinzi Li; et al. Frontiers in Plant Science 2026. doi:10.3389/fpls.2026.1814962
Claim · model-written summary
The automated fluorescence microscopy method reliably separated monocot and dicot plants by genome size, with accuracy close to flow cytofluorometry for dicots and comparable for monocots.
Verbatim
e0“enables reliable separation of both monocotyledonous and dicotyledonous plants by genome size with an accuracy close (for dicots) or comparable (for monocots) to flow cytofluorometry”
Title
Dmitriy A. Serov; Dmitry A. Zakharov; Natalia A. Semenova; et al. Inventions 2026. doi:10.3390/inventions11030056
Claim · model-written summary
The hyperspectral imaging plus improved YOLOv5 pipeline detected early latent bruises on mangoes with mAP_0.5 of 98.2%, with balanced precision and recall and fast inference at 320×320 resolution.
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Mangifera indicat0Verbatim
t0“mangoes”
e1“The resulting pipeline detected early latent bruises with high accuracy, achieving mAP_0.5 = 98.2% with balanced precision/recall and fast inference at 320×320 resolution”
Title
Shang-tao Ou-yang; Chi Yao; Yan-bing Li; et al. Journal of Future Foods 2026. doi:10.1016/j.jfutfo.2025.12.017
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