Forage yield performance and nutritive value of selected wild soybean ecotypes
Bibliographic record
Abstract
Field experiments were conducted to evaluate the yield, yield components and quality of three wild soybean (Glycine soja Sieb. and Zucc.) ecotypes (FJW-9, SDW-12 and HLW-18) as forage in Dongying Forage Experiment Station of China in 2004 and 2005. Biomass yield and nutritional quality were observed using leaf, stem and whole plant taken from five harvest dates. The results show that the harvest dates had significant effects on leaf, stem, pod and whole-plant dry matter yields and forage quality (P < 0.01). Wild soybean ecotypes included in the study produced whole-plant drymatter from 2.3 to 6.5 Mg ha -1 at different harvest dates. The highest dry matter yield came from the Sep. 17 harvest date, with average crude protein (CP) concentration of 191 g kg -1 , neutral detergent fiber (NDF) concentration of 355 g kg -1 and acid detergent fiber (ADF) concentration of 254 g kg -1 . Ecotype FJW-9 had higher dry matter yields of leaf, stem and whole plant than SDW-12 and HLW-18 (P < 0.05). Mean CP concentration in whole plant of FJW-9 was higher (212 g kg -1 ) compared with the other two ecotypes (205 and 199 g kg -1 ), while the mean NDF and ADF concentrations of FJW-9 were lower than HLW-18 and SDW-12. Dry matter partitioning of wild soybean plant parts was greatly affected by harvest dates. There were statistically significant differences between wild soybean ecotypes in leaf, stem and whole-plant yields. The correlation between whole-plant dry matter yield and pod yield was not statistically significant (r = 0.13). These results suggest that wild soybeans have the potential to provide forage of high quality and adequate quantity for animals. Key words: Wild soybean, yield, nutritive value
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".