NIR spectral models for early detection of bitter pit in asymptomatic 'Fuji' apples

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dc.contributor.authorRene Mogollon, Miguel
dc.contributor.authorContreras, Carolina
dc.contributor.authorde Freitas, Sergio Tonetto
dc.contributor.authorZoffoli, Juan Pablo
dc.date.accessioned2025-01-20T23:53:06Z
dc.date.available2025-01-20T23:53:06Z
dc.date.issued2021
dc.description.abstractBitter pit (BP) is a physiological disorder that develops in apples, mainly during storage. This study sought to develop NIR spectral models for prediction of future BP incidence and severity in 'Fuji' apples using spectral data collected at harvest and during storage. Partial Least Square classification models obtained from spectra reflectance between 950 and 1200 nm were compared, starting at harvest, at 10 days postharvest and every 20 days thereafter over 110 days at 0 degrees C in relation to BP severity (number of pits per fruit) after 150 days at 0 degrees C. The models used data from a total of 3000 fruit, collected over two seasons (2018 and 2019) from two orchards. All models were evaluated for Accuracy, Sensitivity, Specificity, Positive Predicted Value (PPV) and Negative Predicted Value (NPV). In the validation dataset, Accuracy, Specificity and NPV values varied between 60 and 80 % and were independent of the time of evaluation during storage. Sensitivity and PPV values did not exceed 60 % in the same dataset. Here, BP incidences in fruit with severities of <8 pits per fruit, achieved accuracies and NPVs between 60 and 70 % in the calibration and validation datasets using spectral data collected at harvest. For comparison, the detection of high BP severities (8-9 pits per fruit), these same metrics achieved between 80 and 90 % using spectral data collected during the first 10 days of storage.
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.scienta.2021.109945
dc.identifier.eissn1879-1018
dc.identifier.issn0304-4238
dc.identifier.urihttps://doi.org/10.1016/j.scienta.2021.109945
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/94942
dc.identifier.wosidWOS:000615164300023
dc.language.isoen
dc.revistaScientia horticulturae
dc.rightsacceso restringido
dc.subjectPhysiological disorder
dc.subjectClassification model
dc.subjectNear infrared
dc.subjectNon-destructive assessment
dc.titleNIR spectral models for early detection of bitter pit in asymptomatic 'Fuji' apples
dc.typeartículo
dc.volumen280
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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