Effects of Various Nitrogen Regimes on the Ability of Rapeseed (Brassica napus L.) to Suppress Littleseed Canarygrass (Phalaris minor Retz.)
Bibliographic record
Abstract
Using crops to control invasive weeds is an important approach for the long-term management of invasive species in agroecosystems. Nitrogen application can improve the yield and quality of crops, but may shift interactions of invasive weeds and crops, potentially affecting grass control ability. To explore the yield of a crop and its control efficacy of invasive weed under different nitrogen conditions, we studied the competitive effects of the high-value crop rapeseed (Brassica napus L.) on growth and photosynthetic characteristics of invasive species littleseed canarygrass in the field experiments. The results showed that the rapeseed yield and its control efficacy on littleseed canarygrass were significantly affected (p < 0.05) under different N regimes, and the control efficacy of littleseed canarygrass by rapeseed increased first and then decreased with the increase of basal nitrogen rates, while increasing topdressing N rates increased control efficacy of littleseed canarygrass by rapeseed. In fact, yield and weed control efficacy of rapeseed was most ideal when both basal and topdressing N was 90 kg·ha−1. We also found that N significantly impacted the competitive ability of rapeseed toward littleseed canarygrass, and rapeseed had the highest competitive ability when both basal and topdressing N was 90 kg·ha−1. With the increase of basal nitrogen rates, competitive balance index (CB) of rapeseed increased initially but decreased beyond an optimal level. CB continually increased with increasing topdressing N rates. Our research also showed level and period of N application had a significant effect (p < 0.01) on the photosynthetic rate (Pn) and chlorophyll content (Chl) of both rapeseed and littleseed canarygrass. Under the same N application regime, the Pn and Chl of littleseed canarygrass were higher than that of rapeseed in December, while the Pn and Chl of rapeseed was higher than that of littleseed canarygrass in February. Our study indicated that photosynthetic characteristics of rapeseed and littleseed canarygrass in different growth stages differ in their sensitivity to N regimes, creating a dynamic competitive relationship. Together, our results demonstrated that optimal application of fertilizer N could help rapeseed produce higher yields and greater weed control efficacy, suggesting that future modeling or experimental studies on utilizing crops to control invasive weeds should carefully consider both timing and placement of N.
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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 | 0.001 | 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 | 0.001 | 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".