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“processing time”

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Associationobservedoriginal resultno effectmeasured

Claim · model-written summary

Processing time did not affect blueberry hardness.

Taxon: blueberriest0
Treatment: processing timee0
Outcome: Hardnesse0
Direction: not affectede0

Verbatim

e0
“Hardness was not affected by the processing time and was similar just after HPP and one-week storage.”
✓ located verbatim in the source · abstract, characters 691–792

t0
“blueberries”
✓ located verbatim in the source · title, characters 40–51

Title

High pressure processing and storage of blueberries: effect on fruit hardness

Tiago B. Scheidt; Filipa V. M. Silva High Pressure Research 2017. doi:10.1080/08957959.2017.1402895

Other claims from this paper (6)

Observation Water immersion was the best packaging option for whole blueberry.
Intervention effect Sensory texture did not differ between pressure-treated and fresh blueberry.
Intervention effect Instrumental hardness declined significantly after pressure processing.
Intervention effect Hardness was similar immediately after treatment and after one week of storage.
Observation Pressure-treated blueberry hardness persisted over 28 days.
Intervention effect Pressure-treated blueberries avoided considerable weight loss over 28 days, unlike collapsing fresh fruit.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Average image processing time was 976.3ms.

Taxon: cottonGossypium hirsutumt0
Outcome: time of processing an imagee0
Value: 976.3mse0

Verbatim

e0
“The average time of processing an image is 976.3ms”
✓ located verbatim in the source · abstract, characters 564–614

t0
“cotton field”
✓ located verbatim in the source · title, characters 54–66

Title

Experiment study of real-time recognition of weeds in cotton field based on DSP

Yin Dongfu; Shuren Chen; Pei Wenchao; et al. 2011 International Conference on New Technology of Agricultural 2011. doi:10.1109/icae.2011.5943798

Other claims from this paper (4)

Method / resource The DSP weed recognition system achieved a recognition rate of 86.7% in cotton fields.
Method / resource DSP processing increased real-time weed recognition in cotton fields.
Method / resource The image processing rate supports a weed platform speed faster than 0.2m/s.
Method / resource Tests found the system met precision target spraying requirements in cotton fields.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Average processing time was 0.2 seconds per mango.

Taxon: mangoMangifera indicae0
Outcome: processing timee0
Value: 0.2 secondse0

Not reportedComparator

Verbatim

e0
“Average processing time for each mango is 0.2 seconds”
✓ located verbatim in the source · abstract, characters 1078–1131

Title

Weight Estimation of Mango from Single Visible Fruit Surface using Computer Vision

Waiyar Aung; Theint Theint Thu; Hnin Thi Dar Aye; et al. 2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) 2020. doi:10.23919/sice48898.2020.9240422

Other claims from this paper (2)

Method / resource The image algorithm estimated mango volume with 95% average accuracy.
Method / resource The image algorithm estimated mango weight with 95% average accuracy.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Total processing time was 50.15 ms.

Taxon: sugar oranget0
Outcome: total processing timee0
Value: 50.15 mse0

Verbatim

e0
“the total processing time was 50.15 ms”
✓ located verbatim in the source · abstract, characters 1323–1361

t0
“Sugar Orange”
✓ located verbatim in the source · title, characters 45–57

Title

YOLO-FSEP: An Improved YOLOv8n Algorithm for Sugar Orange Detection in Orchards

Tianfa Deng; Jinchao Sun; Qingjuan Zhao; et al. Sensors 2026. doi:10.3390/s26123848

Other claims from this paper (7)

Method / resource YOLO-FSEP increased detection accuracy by 0.9% over YOLOv8n.
Method / resource YOLO-FSEP increased recall by 1.3% over YOLOv8n.
Method / resource YOLO-FSEP increased mAP50-95 by 3.2% over YOLOv8n.
Method / resource The model maintained inference speed of 62.6 FPS.
Method / resource A continuous 3D localization test gave average YOLO inference time of 49.90 ms.
Method / resource Post-processing took 0.24 ms.
Method / resource The authors judged processing speed sufficient for dynamic harvesting localization.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Average frame processing time was 45ms.

Outcome: average processing time of framese0
Value: 45mse0
Setting: farmlande1

Not reportedTaxon

Verbatim

e0
“The average processing time of frames is 45ms”
✓ located verbatim in the source · abstract, characters 1178–1223

e1
“The experiments in farmland”
✓ located verbatim in the source · abstract, characters 1086–1113

Title

Navigation Path Curve Extraction Method Based on Depth Image for Combine Harvester

Wenjun Jiang; Pengfei Wang; Qixin Cao 2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA) 2020. doi:10.1109/iciea48937.2020.9248212

Other claims from this paper (2)

Method / resource The depth-image method detected farmland boundary points with 99.0% average accuracy.
Method / resource Experimental results met navigation accuracy and real-time requirements.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Image processing time was 71.4 ms.

Taxon: CabbageBrassica oleracea var. capitatat0
Outcome: processing timee0
Value: 71.4 mse0

Verbatim

t0
“Cabbage Seedling”
✓ located verbatim in the source · title, characters 18–34

e0
“The processing time was 71.4 ms”
✓ located verbatim in the source · abstract, characters 2172–2203

Title

Identification of Cabbage Seedling Defects in a Fast Automatic Transplanter Based on the maxIOU Algorithm

Gan Zhang; Yongshuang Wen; Yuzhi Tan; et al. Agronomy 2020. doi:10.3390/agronomy10010065

Other claims from this paper (8)

Method / resource The substrate segmentation color component interval was [0, 24] in the G channel.
Method / resource The seedling segmentation color component interval was [21, 255] in the excess green channel.
Method / resource Mean intersection over union for substrate segmentation was 0.854.
Method / resource Mean intersection over union for seedling segmentation was 0.820.
Method / resource Cabbage seedling defect identification accuracy was 97.6%.
Method / resource Cabbage seedling defect identification precision was 97.4%.
Method / resource Cabbage seedling defect identification recall was 99.8%.
Recommendation The authors concluded that the algorithm can be applied to high speed field transplanters.

Associationobservedoriginal resultnegativemeasured

Claim · model-written summary

Catalpol content decreased as processing time increased.

Taxon: Radix Rehmanniaee1
Treatment: processing timee0
Outcome: content of catalpole0
Direction: decreasede0

Verbatim

e0
“the content of catalpol decreased while the processing time prolonged”
✓ located verbatim in the source · abstract, characters 1013–1082

e1
“Radix Rehmanniae”
✓ located verbatim in the source · title, characters 29–45

Title

Determination of Catalpol in Radix Rehmanniae by Capillary Zone Electrophoresis

Zhao Xin Yaowu fenxi zazhi 2002

Other claims from this paper (6)

Method / resource Average catalpol assay recovery was 98.2% for dried Rehmannia root.
Method / resource Average catalpol assay recovery was 99.5% for prepared Rehmannia root.
Method / resource Assay RSD was 2.1% for dried Rehmannia root.
Method / resource Assay RSD was 2.4% for prepared Rehmannia root.
Method / resource The method was characterized as simple, rapid, sensitive and reproducible for catalpol determination.
Recommendation The authors considered catalpol an unsuitable quality index for prepared Rehmannia root.

Associationobservedoriginal resultnegativemeasured

Claim · model-written summary

Succulence and toughness decreased over prolonged processing time.

Taxon: Palmyra palmt0
Treatment: prolonged processing timee0
Outcome: succulence and toughnesse0
Direction: decreasede0

Verbatim

e0
“succulence and toughness decreased over the prolonged processing time.”
✓ located verbatim in the source · abstract, characters 1162–1232

t0
“Palmyra palm (Borassus flabellifer)”
✓ located verbatim in the source · title, characters 44–79

Title

Shelf-life extension of tender endosperm of Palmyra palm (Borassus flabellifer) through retort processing

S. K. Mathanghi; S. Kanchana; G. Hemalatha; et al. Journal of Applied and Natural Science 2022. doi:10.31018/jans.v14isi.3614

Other claims from this paper (5)

Intervention effect Processed tender endosperm had a shelf life of six months under ambient storage.
Intervention effect Time to reach lethality was longer in nontransparent pouches than transparent pouches.
Association Hardness, gumminess and chewiness decreased with longer processing and storage.
Intervention effect Tender endosperm in metalized pouches had a higher overall acceptability score than in transparent pouches.
Observation Retorted pouches remained microbiologically safe through six months, with the named bacteria absent.

Associationobservedoriginal resultmeasured

Claim · model-written summary

Processing and storage time affected melon T2.

Taxon: melonCucumis melot0
Treatment: processing and storage timee0
Outcome: T2e0

Not reportedDirection

Verbatim

e0
“T2, a measure of this fluidity, is affected by the processing and storage time.”
✓ located verbatim in the source · abstract, characters 833–912

t0
“melon”
✓ located verbatim in the source · title, characters 10–15

Title

Fresh-cut melon quality during storage: An NMR study of water transverse relaxation time

Joana F. Fundo; Ana L. Amaro; Ana Raquel Madureira; et al. Journal of Food Engineering 2015. doi:10.1016/j.jfoodeng.2015.03.028

Other claims from this paper (5)

Observation Processed melon cells showed one class of water fluidity.
Association T2 was closely related to total colour difference, firmness and water activity.
Association Total colour difference increased as T2 increased.
Association Firmness and water activity declined as T2 increased.
Method / resource NMR T2 was useful for evaluating fresh-cut melon quality.

Intervention effectobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

Processing time significantly affected early flowering of tobacco.

Taxon: tobaccoNicotiana tabacume0
Treatment: different processing timee0
Outcome: early floweringe0

Not reportedComparatorDirection

Verbatim

e0
“the effects of different processing time on early flowering of tobacco were significant”
✓ located verbatim in the source · abstract, characters 354–441

Title

Effects of Temperature-light Factor on Budding Time and Hormones of Tobacco in Seedling Period

Qingming Zhou Hunan Agricultural Sciences 2010

Other claims from this paper (4)

Intervention effect Low temperature significantly affected tobacco budding time.
Intervention effect Low temperature significantly affected tobacco gibberellin content.
Intervention effect The combined temperature and light effect was greater.
Association Short day length was identified as a factor affecting early tobacco flowering.

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