Indonesian
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)
Environmental Pollution 2004-Oct

Prediction of phenanthrene uptake by plants with a partition-limited model.

Hanya pengguna terdaftar yang dapat menerjemahkan artikel
Masuk daftar
Tautan disimpan ke clipboard
Lizhong Zhu
Yanzheng Gao

Kata kunci

Abstrak

The performance of a partition-limited model on prediction of phenanthrene uptake by a wide variety of plant species was evaluated using a greenhouse study. The model predictions of root or shoot concentrations for tested plant species were all within an order of magnitude of the observed values. Modeled root concentrations appeared to be more accurate than modeled shoot concentrations. The differences of simulated and experimented concentrations of phenanthrene in roots and shoots of three representative plant species, including ryegrass, flowering Chinese cabbage, and three-colored amaranth, were less than 81% for roots and 103% for shoots. Results are promising in that the alpha(pt) values of the partition-limited model for root uptake of phenanthrene correlate well with root lipid contents. Additionally, a significantly positive correlation is also observed between root concentration factors (RCFs, defined as the ratio of contaminant concentrations in root and in soil on a dry weight basis) of phenanthrene and root lipid contents. Results from this study suggest that the partition-limited model may have potential applications for predicting the plant PAH concentration in contaminated sites.

Bergabunglah dengan
halaman facebook kami

Database tanaman obat terlengkap yang didukung oleh sains

  • Bekerja dalam 55 bahasa
  • Pengobatan herbal didukung oleh sains
  • Pengenalan herbal melalui gambar
  • Peta GPS interaktif - beri tag herba di lokasi (segera hadir)
  • Baca publikasi ilmiah yang terkait dengan pencarian Anda
  • Cari tanaman obat berdasarkan efeknya
  • Atur minat Anda dan ikuti perkembangan berita, uji klinis, dan paten

Ketikkan gejala atau penyakit dan baca tentang jamu yang mungkin membantu, ketik jamu dan lihat penyakit dan gejala yang digunakan untuk melawannya.
* Semua informasi didasarkan pada penelitian ilmiah yang dipublikasikan

Google Play badgeApp Store badge