Effects of Nitrogen on Growth, Yield and Postharvest Quality of Selected Cauliflower (Brassica oleracea) Varieties
Bibliographic record
Abstract
Cauliflower (Brassica oleracea var. botrytis L.) is one of the most popular vegetable crops. An experiment was conducted to study the response of late season varieties of cauliflower to different sources of nitrogen on growth, yield and postharvest quality at Rampur, Chitwan, Nepal during October 2018 to March 2019. Four late season varieties of cauliflower viz. NS 106, Snow Moon, Yukon, and Candid Charm and three different sources of nitrogen viz. 100% Nitrogen (N) through Farm yard manure, 50% N through FYM and 50% N through urea, and 100% N through urea. The two-factor experiment was laid in RCBD with three replications and twelve treatment combinations. All the recorded growth, yield and postharvest quality parameters were significantly higher and statistically similar in NS 106 and Yukon and significantly lower in Candid Charm. Similarly, significantly higher plant height, canopy diameter, leaf number, curd height, economic yield and biological yield were recorded in 50% N through FYM and 50% N through urea. Significantly lower plant height, canopy diameter, leaf number, economic yield and biological yield, titrable acidity and significantly higher days to curd maturity, vitamin C and dry matter content of leaf and curd, and TSS content were recorded in 100% N through FYM. Results revealed that for higher and postharvest quality of cauliflower during late season at Rampur, Chitwan Yukon or NS 106 both varieties were superior along with 50% N through FYM and 50% N than those of the other varieties. SAARC J. Agric., 19(2): 195-205 (2021)
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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 | 0.001 |
| 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".