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Cultivar and Year Rather than Agricultural Practices Affect Primary and Secondary Metabolites in Apple Fruit.

Le Bourvellec C, Bureau S, Renard CM, Plenet D, Gautier H, Touloumet L, Girard T, Simon S - PLoS ONE (2015)

Bottom Line: The main factors affecting primary and secondary metabolites, in both apple skin and flesh, were by far the cultivar and the yearly conditions, while the management system had a very limited effect.When considering the three cultivars and the year 2011 to investigate the effect of the management system per se, only few compounds differed significantly between the three systems and in particular the total phenolic content did not differ significantly between systems.Finally, when considering orchards grown in the same pedoclimatic conditions and of the same age, instead of the usual organic vs. conventional comparison, the effect of the management system on the apple fruit quality (Fruit weight, dry matter, soluble solids content, titratable acidity, individual sugars, organic acids, and phenolics) was very limited to non-significant.

View Article: PubMed Central - PubMed

Affiliation: UMR408 Sécurité et Qualité des Produits d'Origine Végétale, Institut National de la Recherche Agronomique, Avignon, France.

ABSTRACT
Many biotic and abiotic parameters affect the metabolites involved in the organoleptic and health value of fruits. It is therefore important to understand how the growers' decisions for cultivar and orchard management can affect the fruit composition. Practices, cultivars and/or year all might participate to determine fruit composition. To hierarchize these factors, fruit weight, dry matter, soluble solids contents, titratable acidity, individual sugars and organics acids, and phenolics were measured in three apple cultivars ('Ariane', 'Melrose' and 'Smoothee') managed under organic, low-input and conventional management. Apples were harvested at commercial maturity in the orchards of the cropping system experiment BioREco at INRA Gotheron (Drôme, 26) over the course of three years (2011, 2012 and 2013). The main factors affecting primary and secondary metabolites, in both apple skin and flesh, were by far the cultivar and the yearly conditions, while the management system had a very limited effect. When considering the three cultivars and the year 2011 to investigate the effect of the management system per se, only few compounds differed significantly between the three systems and in particular the total phenolic content did not differ significantly between systems. Finally, when considering orchards grown in the same pedoclimatic conditions and of the same age, instead of the usual organic vs. conventional comparison, the effect of the management system on the apple fruit quality (Fruit weight, dry matter, soluble solids content, titratable acidity, individual sugars, organic acids, and phenolics) was very limited to non-significant. The main factors of variation were the cultivar and the year of cropping rather than the cropping system. More generally, as each management system (e.g. conventional, organic…) encompasses a great variability of practices, this highlights the importance of accurately documenting orchard practices and design beside the generic type of management in such studies.

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Related in: MedlinePlus

PCA results on mid-infrared spectral data of apple skin and pulp. A: spectral area between 1500–1000 cm-1, B: spectral area between 2000–1500 cm-1 and C: spectral area between 3000–2500 cm-1.The code corresponds to the cultivar (M: Melrose, S: Smoothee, A: Ariane), to the management system (C: conventional, O: organic, L: low-input) and to the year 2011, 2012 and 2013.
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pone.0141916.g001: PCA results on mid-infrared spectral data of apple skin and pulp. A: spectral area between 1500–1000 cm-1, B: spectral area between 2000–1500 cm-1 and C: spectral area between 3000–2500 cm-1.The code corresponds to the cultivar (M: Melrose, S: Smoothee, A: Ariane), to the management system (C: conventional, O: organic, L: low-input) and to the year 2011, 2012 and 2013.

Mentions: In the fingerprint region (1500 and 900 cm-1), i.e. the absorption range of different molecular vibrations such as OH-bending, C-O and C-C stretching, the MIR spectra differ in absorbance in relation to the variability of the apples composition [23]. This spectral range also contains quantitative information a.o. about the sugars, organic acids and phenolics present, as demonstrated in Bureau et al. (2012) [23]. They integrate the composition of the apple samples, and are a suitable signal for to evaluate the variability within such sample sets. ANOVA performed on spectral data allowed to classify the studied factors according to their global effect. The Fisher values (F) decreased in the order: cultivar (F = 120) > year (F = 55) > system (F = 7) (results not shown). The effect of ‘cultivar’ was significantly higher than that of ‘year’, itself much higher than the effect of ‘system’. ANOVA also identified specific spectral areas showing variation for each factor. The specific spectral areas were 1500–1000 cm-1 for cultivar, 2000–1500 cm-1 for year and 3000–2500 cm-1 for system. These areas were used to discriminate the apple samples using principal component analyses (PCA, only the two first principal components (PC)) shown in Fig 1. The three cultivars appeared relatively well discriminated by PCA using the most discriminating spectral area, 1500–1000 cm-1 (Fig 1A). As regards the year, 2011 and 2013 were fairly well discriminated by PCA using the spectral area 2000–1500 cm-1, forming two separate clusters. In contrast, 2012 was distributed in three clusters that partly overlapped the 2011 and 2013 years. The three management systems completely overlapped, even when the most discriminating spectral area was used, 3000–2500 cm-1 (Fig 1C). Whereas the variability given by cultivars and years was large enough to be observed in mid-infrared, differences due to the management systems were too small to discriminate the samples by their mid-infrared spectra.


Cultivar and Year Rather than Agricultural Practices Affect Primary and Secondary Metabolites in Apple Fruit.

Le Bourvellec C, Bureau S, Renard CM, Plenet D, Gautier H, Touloumet L, Girard T, Simon S - PLoS ONE (2015)

PCA results on mid-infrared spectral data of apple skin and pulp. A: spectral area between 1500–1000 cm-1, B: spectral area between 2000–1500 cm-1 and C: spectral area between 3000–2500 cm-1.The code corresponds to the cultivar (M: Melrose, S: Smoothee, A: Ariane), to the management system (C: conventional, O: organic, L: low-input) and to the year 2011, 2012 and 2013.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664253&req=5

pone.0141916.g001: PCA results on mid-infrared spectral data of apple skin and pulp. A: spectral area between 1500–1000 cm-1, B: spectral area between 2000–1500 cm-1 and C: spectral area between 3000–2500 cm-1.The code corresponds to the cultivar (M: Melrose, S: Smoothee, A: Ariane), to the management system (C: conventional, O: organic, L: low-input) and to the year 2011, 2012 and 2013.
Mentions: In the fingerprint region (1500 and 900 cm-1), i.e. the absorption range of different molecular vibrations such as OH-bending, C-O and C-C stretching, the MIR spectra differ in absorbance in relation to the variability of the apples composition [23]. This spectral range also contains quantitative information a.o. about the sugars, organic acids and phenolics present, as demonstrated in Bureau et al. (2012) [23]. They integrate the composition of the apple samples, and are a suitable signal for to evaluate the variability within such sample sets. ANOVA performed on spectral data allowed to classify the studied factors according to their global effect. The Fisher values (F) decreased in the order: cultivar (F = 120) > year (F = 55) > system (F = 7) (results not shown). The effect of ‘cultivar’ was significantly higher than that of ‘year’, itself much higher than the effect of ‘system’. ANOVA also identified specific spectral areas showing variation for each factor. The specific spectral areas were 1500–1000 cm-1 for cultivar, 2000–1500 cm-1 for year and 3000–2500 cm-1 for system. These areas were used to discriminate the apple samples using principal component analyses (PCA, only the two first principal components (PC)) shown in Fig 1. The three cultivars appeared relatively well discriminated by PCA using the most discriminating spectral area, 1500–1000 cm-1 (Fig 1A). As regards the year, 2011 and 2013 were fairly well discriminated by PCA using the spectral area 2000–1500 cm-1, forming two separate clusters. In contrast, 2012 was distributed in three clusters that partly overlapped the 2011 and 2013 years. The three management systems completely overlapped, even when the most discriminating spectral area was used, 3000–2500 cm-1 (Fig 1C). Whereas the variability given by cultivars and years was large enough to be observed in mid-infrared, differences due to the management systems were too small to discriminate the samples by their mid-infrared spectra.

Bottom Line: The main factors affecting primary and secondary metabolites, in both apple skin and flesh, were by far the cultivar and the yearly conditions, while the management system had a very limited effect.When considering the three cultivars and the year 2011 to investigate the effect of the management system per se, only few compounds differed significantly between the three systems and in particular the total phenolic content did not differ significantly between systems.Finally, when considering orchards grown in the same pedoclimatic conditions and of the same age, instead of the usual organic vs. conventional comparison, the effect of the management system on the apple fruit quality (Fruit weight, dry matter, soluble solids content, titratable acidity, individual sugars, organic acids, and phenolics) was very limited to non-significant.

View Article: PubMed Central - PubMed

Affiliation: UMR408 Sécurité et Qualité des Produits d'Origine Végétale, Institut National de la Recherche Agronomique, Avignon, France.

ABSTRACT
Many biotic and abiotic parameters affect the metabolites involved in the organoleptic and health value of fruits. It is therefore important to understand how the growers' decisions for cultivar and orchard management can affect the fruit composition. Practices, cultivars and/or year all might participate to determine fruit composition. To hierarchize these factors, fruit weight, dry matter, soluble solids contents, titratable acidity, individual sugars and organics acids, and phenolics were measured in three apple cultivars ('Ariane', 'Melrose' and 'Smoothee') managed under organic, low-input and conventional management. Apples were harvested at commercial maturity in the orchards of the cropping system experiment BioREco at INRA Gotheron (Drôme, 26) over the course of three years (2011, 2012 and 2013). The main factors affecting primary and secondary metabolites, in both apple skin and flesh, were by far the cultivar and the yearly conditions, while the management system had a very limited effect. When considering the three cultivars and the year 2011 to investigate the effect of the management system per se, only few compounds differed significantly between the three systems and in particular the total phenolic content did not differ significantly between systems. Finally, when considering orchards grown in the same pedoclimatic conditions and of the same age, instead of the usual organic vs. conventional comparison, the effect of the management system on the apple fruit quality (Fruit weight, dry matter, soluble solids content, titratable acidity, individual sugars, organic acids, and phenolics) was very limited to non-significant. The main factors of variation were the cultivar and the year of cropping rather than the cropping system. More generally, as each management system (e.g. conventional, organic…) encompasses a great variability of practices, this highlights the importance of accurately documenting orchard practices and design beside the generic type of management in such studies.

Show MeSH
Related in: MedlinePlus