تأثیر تنش شوری و روشهای مختلف پرایمینگ بذر بر سبز شدن و خصوصیات گیاهچه کینوا (Chenopodium quinoa Willd.)
Notice bibliographique
Résumé
]Introduction The main limiting factor for food security in Iran and world is water qualitative and quantitative. Agriculture sector is the main consumer of water and more vulnerable section from water crisis. In order to improve food security calorie requirement of growing population should be provided from nonsaline water resources. Quinoa (Chenopodium quinoa) is diploeid, allotetraploied, C3 and facultative halophyte from Amaranthace family and categorized in pseudo cereal group. This plant has cultivated 5000 years in Ands, and the highest cultivated area is in Bolivia near salt flats. This plant can grow successfully in different countries such as, Europe countries, USA, Canada, Africa, Morocco, Pakistan and India. Protein content is between 13.81-21.9% and flour is gluten free and provides all essential amino acid of human. Because of high potential of quinoa for providing human calories and high salt and drought tolerance it could be considered for saline and marginal area. Quinoa was selected for cultivation with saline water because of salt tolerance and economic production with saline water which are not use for conventional crop. The main problem of quinoa is emergence and stand establishment with saline water. The aim of this study is evaluation of salinity stress on plant emergence and priming effect of emergence improvement under saline condition. Materials and methods In order to evaluate salinity stress on emergence and establishment of quinoa an experiment was conducted based on CRD design with 5 levels of salinity (0, 4, 8, 12 and 16 dS/m) with four replication in soil and cocopit. Emergence recorded daily and finally plant height and dry weight was measured. Two piece and modified discount function model was fitted to emergence percent. In order to improve emergence under saline condition an experiment was conducted with three treatments (Gibberlic acid (10 ppm), H2O and Ascorbic acid (3 ppm)) and four levels of salinity (0, 4 and 8 dS/m) with three replications based on CRD design with factorial arrangement. Coefficent of equation was estimated with SAS software based on NLIN and REG procedure. Results and discussion Result showed that quinoa is sensitive in emergence stage is depends to substrate and 50 % of emergence reduction in soil and cocopit occurred at 6.35 and 15.04 dS/m. Threshold in soil and cocopit was 9.52 and 0.03 dS/m. Emergence rate and percentage of seeds under saline condition in cocpit did not have significant differences up to 12 dS/m and salinity above 4 dS/m delay emergence. Seedling emergence index under nonsaline condition was 0.96 but at 4, 8 and 12 dS/m in soil had 24, 48 and 84 % reduction. Seedling height in soil and cocopit at 12 dS/m reduced 91 and 30 %, respectively. Priming could not improve quinoa emergence although hydroprime improve emergence to some extent (8%). Quinoa is sensitive to salinity at seedling stage but after this stage could produce 2-3 t ha-1 seed yield with 15 dS/m saline water in Yazd. Since, in saline area farmers don’t have fresh water and quinoa is sensitive to saline water during emergence and early establishment. It would be better use transplanting method or not coverage of seed with soil.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,008 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,084 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».