Effect of Soil Moisture on Growth and Dry Matter Accumulation of Rice in Cold Region
Notice bibliographique
Résumé
To study the effect of soil moisture on growth and dry matter accumulation of rice in cold region,controlling water treatments(CWT) for the two rice varieties(Shangyu 397 and Suijing 3) at-30 to-35 kPa and-60 to-65 kPa of soil water potential were carried out during tillering stage,panicle initiation stage,1-10 days after heading,11-20 days after heading,respectively.When soil water potential(SWP) during tillering stage was kept at-30~-35kPa,the effect on plant height was very little,the culms of the two varieties were decreased apparently,and areas of three leaves from the top in two varieties were reduced differently.While SWP during panicle initiation stage was kept at-30~-35kPa,the height of the two varieties was decreased obviously and its main reason was that the internodes length from the second node to the forth node were decreased significantly,and areas of three leaves from the top in two varieties were reduced,but the culms and panicles per hill of the two varieties were increased significantly.While SWP before heading stage was kept at-30~-35kPa,the stem dry matter weight(SDM),the sheath dry matter weight(SHDM) and the panicle dry matter weight(PDM) of the two varieties during full heading stage were lower than those of CK,and exportation percentage(EP) of dry matter in every organ of two varieties also were reduced and reduced range at-60~-65kPa was greater than that at-30~-35kPa.While SWP during the beginning of heading stage was kept at-30~-35kPa,EP of dry matter in every organ of Shangyu 397 on the numerous tests was lower than that of CK,but Suijing 3 was opposite.The response of growth and development and accumulation of dry matter of different rice varieties is different on the different developing stage under the different treatmens.The effect of soil moisture on growth and dry matter accumulation of rice during tillering stage and panicle initiation stage is more serious than that in other treatments.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 ».