Turkish
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Food Chemistry 2016-Dec

A comprehensive and comparative GC-MS metabolomics study of non-volatiles in Tanzanian grown mango, pineapple, jackfruit, baobab and tamarind fruits.

Sadece kayıtlı kullanıcılar makaleleri çevirebilir
Giriş yapmak kayıt olmak
Bağlantı panoya kaydedilir
Bekzod Khakimov
Richard J Mongi
Klavs M Sørensen
Bernadette K Ndabikunze
Bernard E Chove
Søren Balling Engelsen

Anahtar kelimeler

Öz

Tropical fruits contribute significantly to the total fruit intake worldwide. However, their metabolomes have not yet been investigated comprehensively, as most previous studies revealed only volatile and bulk compositions. This study compares non-volatile metabolites of five fruits grown in Tanzania. A new methodology is developed for broad-spectrum GC-MS metabolomics in fruits using a new derivatization and a two dimensional peak deconvolution techniques. A total of 92 peaks were detected from fruits of which 45 were identified. Jackfruits contained the highest amount of carbohydrates, while baobab contained the highest amount of fatty acids. The highest content of organic acids was detected in tamarind. Principal component analysis revealed insights into metabolic differences and similarities, while hierarchical cluster analysis correctly grouped the fruits according to their relationships in plants' phylogenetic tree. The developed methodology could potentially be applied in large-scale studies on fruit quality, authenticity/variety, optimization of post-harvest processing and storage.

Facebook sayfamıza katılın

Bilim tarafından desteklenen en eksiksiz şifalı otlar veritabanı

  • 55 dilde çalışır
  • Bilim destekli bitkisel kürler
  • Görüntüye göre bitki tanıma
  • Etkileşimli GPS haritası - bölgedeki bitkileri etiketleyin (yakında)
  • Aramanızla ilgili bilimsel yayınları okuyun
  • Şifalı bitkileri etkilerine göre arayın
  • İlgi alanlarınızı düzenleyin ve haber araştırmaları, klinik denemeler ve patentlerle güncel kalın

Bir belirti veya hastalık yazın ve yardımcı olabilecek bitkiler hakkında bilgi edinin, bir bitki yazın ve karşı kullanıldığı hastalıkları ve semptomları görün.
* Tüm bilgiler yayınlanmış bilimsel araştırmalara dayanmaktadır

Google Play badgeApp Store badge