Phenotypic diversity and alternative methods for characterization and prediction of pulp yield in passion fruit (Passiflora spp.) germplasm

Jesus, O. N. de; Lima, Lucas Kennedy Silva; Soares, Taliane Leila; Silva, Luana Nascimento da; Santos, Idália Souza dos; Sampaio, S. R.; Oliveira, E. J. de

doi:10.1016/j.scienta.2021.110573

Cited by 13 publications

(7 citation statements)

References 59 publications

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“…The PCA is used to characterize accessions from germplasm banks for different plant species (Smýkal et al, 2017;Maeda et al, 2018;Hashemi and Khadivi, 2020). It is also used to identify the characteristics of higher or lower contribution and/or to discard characteristics with less relevance (Silveira et al, 2019;Jesus et al, 2022). As expected, our study showed there were divergences between the methodologies for selecting and/or discarding characteristics.…”

Section: Discussionsupporting

confidence: 57%

Characterization and genetic diversity in Paspalum notatum Flügge accessions: Morphological and geographical distance

Steiner¹,

Weiler²,

Brunes³

et al. 2022

Revista Brasileira De Zootecnia

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The objective of this work was to describe morphology and grouping of Paspalum notatum accessions, based on multicategorical data which discards the redundant variables for quantification of genetic diversity. We also tested the hypothesis that geographical distance was correlated with morphological divergence. In our study, multivariate analyzes successfully demonstrated the geographic and morphological variability of the P. notatum accessions characterized. Many of these evaluated accessions can be included in future genetic improvement programs. Based on two methodologies for discarding variables, it was possible to identify the potentially important morphological characteristics from genetic diversity studies and characterize new accessions aimed at improving forage and seed production. The methodologies used to discard variables are biometric tools that can be used successfully in future plant breeding programs, especially when a large number of traits and accessions are being evaluated. Although significant, geographic distance had a low association with morphological traits. This indicated the need to use other characteristics, such as forage and seed yield, in addition to molecular analysis. Our analyzes showed genetic variability in P. notatum for all the characteristics studied.

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Section: Discussionsupporting

confidence: 57%

Characterization and genetic diversity in Paspalum notatum Flügge accessions: Morphological and geographical distance

Steiner¹,

Weiler²,

Brunes³

et al. 2022

Revista Brasileira De Zootecnia

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“…Passion fruit belongs to the category of leapfrog fruits, exhibiting rapid post-harvest changes and manifesting characteristics of short shelf life, quick wrinkling, and post-ripening [ 1 , 2 ]. Research on the quality changes of passion fruit during storage primarily focuses on comparing the effectiveness of various packaging technologies.…”

Section: Introductionmentioning

confidence: 99%

“…This research intends to investigate the non-destructive detecting capabilities of near-infrared diffuse reflectance spectroscopy for epicarp hardness of passion fruit during storage. The objectives of this study were as follows: (1) to analyze the variation patterns of epicarp hardness on both sides of passion fruit during different storage periods; (2) to select the optimal feature wavelength combinations that characterize the hardness of the epicarp on both sides; (3) to establish the optimal prediction model for epicarp hardness based on near-infrared spectroscopy.…”

Section: Introductionmentioning

confidence: 99%

Nondestructive Determination of Epicarp Hardness of Passion Fruit Using Near-Infrared Spectroscopy during Storage

Wang,

Fu,

et al. 2024

Foods

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The hardness of passion fruit is a critical feature to consider when determining maturity during post-harvest storage. The capacity of near-infrared diffuse reflectance spectroscopy (NIRS) for non-destructive detection of outer and inner hardness of passion fruit epicarp was investigated in this work. The passion fruits’ spectra were obtained using a near-infrared spectrometer with a wavelength range of 10,000–4000 cm−1. The hardness of passion fruit’s outer epicarp (F1) and inner epicarp (F2) was then measured using a texture analyzer. Moving average (MA) and mean-centering (MC) techniques were used to preprocess the collected spectral data. Competitive adaptive reweighted sampling (CARS), successive projection algorithm (SPA), and uninformative variable elimination (UVE) were used to pick feature wavelengths. Grid-search-optimized random forest (Grids-RF) models and genetic-algorithm-optimized support vector regression (GA-SVR) models were created as part of the modeling process. After MC preprocessing and CARS selection, MC-CARS-Grids-RF model with 7 feature wavelengths had the greatest prediction ability for F1. The mean square error of prediction set (RMSEP) was 0.166 gN. Similarly, following MA preprocessing, the MA-Grids-RF model displayed the greatest predictive performance for F2, with an RMSEP of 0.101 gN. When compared to models produced using the original spectra, the R2P for models formed after preprocessing and wavelength selection improved. The findings showed that near-infrared spectroscopy may predict the hardness of passion fruit epicarp, which can be used to identify quality during post-harvest storage.

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“…There are also some scholars who use the visible light camera to obtain the color and other information of passion fruit, combined with physical and chemical descriptors digital image analysis, and then use the methods of principal component analysis and cluster analysis to predict the flesh quality of passion fruit. However, some indexes, such as pericarp thickness, still need to destroy the passion fruit sample for measurement, which will cause some measurement errors and be unfavorable to the inference of the final model ( Jesus et al., 2022 ). Near-infrared (NIR) spectroscopy has also been applied to predict the total soluble solids, titratable acidity, and pulp content of passion fruit ( Maniwara et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning

Wang

et al. 2023

Front. Plant Sci.

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Passion fruit is a tropical liana of the Passiflora family that is commonly planted throughout the world due to its abundance of nutrients and industrial value. Researchers are committed to exploring the relationship between phenotype and genotype to promote the improvement of passion fruit varieties. However, the traditional manual phenotyping methods have shortcomings in accuracy, objectivity, and measurement efficiency when obtaining large quantities of personal data on passion fruit, especially internal organization data. This study selected samples of passion fruit from three widely grown cultivars, which differed significantly in fruit shape, size, and other morphological traits. A Micro-CT system was developed to perform fully automated nondestructive imaging of the samples to obtain 3D models of passion fruit. A designed label generation method and segmentation method based on U-Net model were used to distinguish different tissues in the samples. Finally, fourteen traits, including fruit volume, surface area, length and width, sarcocarp volume, pericarp thickness, and traits of fruit type, were automatically calculated. The experimental results show that the segmentation accuracy of the deep learning model reaches more than 0.95. Compared with the manual measurements, the mean absolute percentage error of the fruit width and length measurements by the Micro-CT system was 1.94% and 2.89%, respectively, and the squares of the correlation coefficients were 0.96 and 0.93. It shows that the measurement accuracy of external traits of passion fruit is comparable to manual operations, and the measurement of internal traits is more reliable because of the nondestructive characteristics of our method. According to the statistical data of the whole samples, the Pearson analysis method was used, and the results indicated specific correlations among fourteen phenotypic traits of passion fruit. At the same time, the results of the principal component analysis illustrated that the comprehensive quality of passion fruit could be scored using this method, which will help to screen for high-quality passion fruit samples with large sizes and high sarcocarp content. The results of this study will firstly provide a nondestructive method for more accurate and efficient automatic acquisition of comprehensive phenotypic traits of passion fruit and have the potential to be extended to more fruit crops. The preliminary study of the correlation between the characteristics of passion fruit can also provide a particular reference value for molecular breeding and comprehensive quality evaluation.

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Phenotypic diversity and alternative methods for characterization and prediction of pulp yield in passion fruit (Passiflora spp.) germplasm

Cited by 13 publications

References 59 publications

Characterization and genetic diversity in Paspalum notatum Flügge accessions: Morphological and geographical distance

Characterization and genetic diversity in Paspalum notatum Flügge accessions: Morphological and geographical distance

Nondestructive Determination of Epicarp Hardness of Passion Fruit Using Near-Infrared Spectroscopy during Storage

Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning

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