Response of Watermelon Pulp (Citrullus colocynthoides) to Intercropped Maize (Zea mays L.) With Plants Distributions Under Different Nitrogen Fertilization Levels
Bibliographic record
Abstract
Two field experiments were carried out at the Experimental Farm of Gemmeiza Agriculture Research Station, Agricultural Research Center (ARC), Egypt after 2018 and 2019 summer growing seasons to determine the effect of intercropping pattern of yellow maize hybrid (single cross 168: “SC 168”) with watermelon pulp at three plant distributions (20 cm between hills and one plant/hill, 40 cm between hills and two plants/hill and 60 cm between hills and three plants/hill) and different levels of nitrogen fertilizer (25, 50, 75 and 100% of the recommended dose “120 kg N fad-1”) as well as their interactions on maize and watermelon pulp growth, yield and its attributes as well as competitive relationships and yield advantages. The experiments were carried out in split-plot design with four replicates. The main-plots were assigned to plant distributions of maize, the sub-plots were allocated to levels of nitrogen fertilizer for maize. The obtained results showed that planting maize plants on one side of terraces of 140 cm width with 20 cm between hills and leaving one plant/hill and planting watermelon pulp on the other side of the terraces produced the highest values of plant height, ear height, number of kernels row-1, 100-kernel weight and grain yield fad-1, at the same time the lowest values of ear leaf area, ear length, ear diameter and number of rows ear-1 of maize as well as the lowest values of growth, yield and its attributes of watermelon pulp during the both seasons. Mineral fertilizing maize plants with 75% of the recommended dose (90 kg N/fad) and watermelon pulp with the recommended dose produced the highest values of all studied growth characters, yield and its attributes of maize and watermelon pulp in both seasons. The highest values of land equivalent ratio (LER), relative crowding coefficient (RCC), area time equivalent ratio (ATER), land equivalent coefficient (LEC), aggressivity index (AI), monetary advantage index (MAI), actual yield (L.E.) of watermelon, Total income (L.E.) and economic return (L.E.) were obtained from planting maize plants on one side of terraces of 140 cm width with 60 cm between hills and leaving three plants/hill and planting watermelon pulp on the other side of the terraces besides fertilizing maize plants with 75% of the recommended dose (90 kg N/fad) and watermelon pulp with the recommended dose in both seasons. It can be recommended that planting maize on 60 cm between hills and leaving three plants/hill and planting watermelon pulp on the other side of the terraces besides fertilizing maize plants with 90 kg N/fad and watermelon pulp with the recommended dose to obtain the maximum values growth, yield and its attributes of watermelon pulp and competitive relationships and yield advantages of both crops under the climates conditions of Middle Delta, Egypt.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".