Variation in the fruit characteristics of local pear (Pyrus spp.) in the Northwest of Iran

Alizadeh, Khalil; Fatholahi, Soleiman; Silva, Jaime A. Teixeira da

doi:10.1007/s10722-015-0241-7

Cited by 8 publications

(3 citation statements)

References 21 publications

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“…CV is usually used as the main indicator to characterize the genetic differences between germplasm, representing the diversity of related traits. Generally speaking, the CV of traits with rich genetic backgrounds is also large, which has a high reference significance for germplasm identification and evaluation [ 46 ]. CV was used to describe the genetic variation of the mineral element content of 36 cabbage cultivars [ 47 ] and 100 Indian banana germplasm [ 48 ].…”

Section: Resultsmentioning

confidence: 99%

Comprehensive Evaluation of Amino Acids and Polyphenols in 69 Varieties of Green Cabbage (Brassica oleracea L. var. capitata L.) Based on Multivariate Statistical Analysis

Jin

Luo

et al. 2021

Molecules

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The biological activities of the primary metabolites and secondary metabolites of 69 green cabbage varieties were tested. The LC-MS detection method was used to determine the content of 19 free amino acids (lysine, tryptophan, phenylalanine, methionine, threonine, isoleucine, leucine, valine, arginine, asparagine, glycine, proline, tyrosine, glutamine, alanine, aspartic acid, serine, and glutamate). The content of 10 polyphenols (chlorogenic acid, gallic acid, 4-coumaric acid, ferulic acid, gentisic acid, cymarin, erucic acid, benzoic acid, rutin, and kaempferol) was determined by the HPLC detection method. Considering the complexity of the data obtained, variance analysis, diversity analysis, correlation analysis, hierarchical cluster analysis (HCA), and principal component analysis (PCA) were used to process and correlate amino acid or polyphenol data, respectively. The results showed that there were significant differences between the different amino acids and polyphenols of the 69 cabbage varieties. The most abundant amino acids and polyphenols were Glu and rutin, respectively. Both amino acids and polyphenols had a high genetic diversity, and multiple groups of significant or extremely significant correlations. The 69 cabbage varieties were divided into two groups, according to 19 amino acid indexes, by PCA. Among them, seven varieties with high amino acid content all fell into the fourth quadrant. The HCA of amino acids also supports this view. Based on 10 polyphenols, the 69 cabbage varieties were divided into two groups by HCA. Based on 29 indexes of amino acids and polyphenols, 69 cabbage varieties were evaluated and ranked by PCA. Therefore, in this study, cabbage varieties were classified in accordance with the level of amino acids and polyphenols, which provided a theoretical basis for the genetic improvement of nutritional quality in cabbage.

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Section: Resultsmentioning

confidence: 99%

Comprehensive Evaluation of Amino Acids and Polyphenols in 69 Varieties of Green Cabbage (Brassica oleracea L. var. capitata L.) Based on Multivariate Statistical Analysis

Jin

Luo

et al. 2021

Molecules

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“…There were 36 variant types of morphological traits, with CVs ranging from 21.10% to 201.5%. The CVs, which can reflect the variation range of phenotypic traits [28,29], showed that the dispersion degree was highest for the FA among the examined morphological traits of apple germplasm resources. The Shannon-Wiener genetic diversity index can also reflect phenotypic trait diversity [30].…”

Section: Genetic Diversity Associated With the Phenotypic Traits Of A...mentioning

confidence: 98%

Comprehensive Evaluation of Apple Germplasm Genetic Diversity on the Basis of 26 Phenotypic Traits

Tian,

Li,

Wang

et al. 2024

Agronomy

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We used 256 apple germplasm resources for a thorough examination of the genetic diversity associated with 26 phenotypic traits (i.e., genetic diversity analysis, cluster analysis, correlation analysis, principal component analysis, and membership function). The average coefficient of variation for 12 morphological traits was 66.39% (21.10–201.5%). The coefficient of variation was highest and lowest for the fruit arris and the width of the eye basin, respectively. Additionally, the diversity index ranged from 0.54 to 1.33. Moreover, the coefficient of variation for 14 numerical traits varied from 5.37% to 50%. The titratable acid content had the highest coefficient of variation, with a diversity index ranging from 2.01 to 2.08 (average of 2.045). A cluster analysis categorized 256 germplasms into four groups, among which Group I included germplasms with large fruits and the best comprehensive performance. Of the top 10 principal components revealed by the principal component analysis, principal component 1 was mainly related to fruit size and flavor. The top 10 germplasms were selected on the basis of comprehensive scores using the membership function method. Furthermore, a stepwise regression analysis identified 15 key traits for identifying apple germplasms, including the vegetative growth day, fruit weight, and the firmness of the fruit without skin. These results can serve as the foundation for future analyses of the phenotypic diversity of apple germplasms, while also providing a theoretical basis for screening, characterizing, and further improving excellent apple germplasms.

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“…For example, in some mangoes, total soluble solids content (TSS) at the point of harvest are approximately 8.7% while the sugar content is only 6.1% [ 14 ]. Similarly, the TSS of certain pears can be as high as 23.0% while the total sugar content is only 10.4% [ 15 ]. Furthermore, fruits contain sugars other than sucrose which lead to additional errors in Brix measurements.…”

Section: Chemistry Of Interest In Farm-to-table Operationsmentioning

confidence: 99%

Chemical Sensors for Farm-to-Table Monitoring of Fruit Quality

Wilson

2021

Sensors

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Farm-to-table operations produce, transport, and deliver produce to consumers in very different ways than conventional, corporate-scale agriculture operations. As a result, the time it takes to get a freshly picked fruit to the consumer is relatively short and the expectations of the consumer for freshness and quality are high. Since many of these operations involve small farms and small businesses, resources to deploy sensors and instruments for monitoring quality are scarce compared to larger operations. Within stringent power, cost, and size constraints, this article analyzes chemical sensor technologies suitable for monitoring fruit quality from the point of harvest to consumption in farm-to-table operations. Approaches to measuring sweetness (sugar content), acidity (pH), and ethylene gas are emphasized. Not surprisingly, many instruments developed for laboratory use or larger-scale operations are not suitable for farm-to-table operations. However, there are many opportunities still available to adapt pH, sugar, and ethylene sensing to the unique needs of localized farm-to-table operations that can help these operations survive and expand well into the future.

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Variation in the fruit characteristics of local pear (Pyrus spp.) in the Northwest of Iran

Cited by 8 publications

References 21 publications

Comprehensive Evaluation of Amino Acids and Polyphenols in 69 Varieties of Green Cabbage (Brassica oleracea L. var. capitata L.) Based on Multivariate Statistical Analysis

Comprehensive Evaluation of Amino Acids and Polyphenols in 69 Varieties of Green Cabbage (Brassica oleracea L. var. capitata L.) Based on Multivariate Statistical Analysis

Comprehensive Evaluation of Apple Germplasm Genetic Diversity on the Basis of 26 Phenotypic Traits

Chemical Sensors for Farm-to-Table Monitoring of Fruit Quality

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