FLORA RIBEREÑA Y CALIDAD DE AGUA DE USO AGRÍCOLA EN LA CUENCA BAJA DEL RÍO VIRÚ, LA LIBERTAD
Bibliographic record
Abstract
The present investigation had as aim determine the riverside flora and the water quality of agricultural use of the basin goes down the river Viru, La Libertad. Six stations of sampling were established along the low basin of the river Viru, it was evaluated by a fortnightly frequency for two months November and December. The riverside flora was gathered in a botanical press and one took the herbalist of the National University of Trujillo for his determination taxonomica, obtuvo 35 especimenes of riverside flora. 72 water samples were collected for chemical, physical and microbiological analysis. The waters of the river Viru from 7.3 to 7.7 presented in agreement to the analyses the following average ranges for every parameter Temperature of the water 20.75°C to 23.75°C, Temperature of the environment 21.5°C to 27.25°C, pH, electrical Conductivity (Us/cm) 0.785 to 1.2, Turbidity of 20 to 138.25mg/L, total Hardness (CaCO3) from 211.57 to 265.375, Calcic Hardness of 105.465 to 139.33mg/L, Calcium 41.257 to 56.59mg/L, Magnesium 21.95 to 30.63 mg/L, Chlorides 38.345 to 55.92, Solid Total 502.5 to 787mg/L, DBO5 0.2525 to 0.67 mg/L, Nitrates 0.0222 to 0.117 mg/L, Nitrites 0.0147 to 0.1995 mg/L, total Coliformes from 150 to 2400 NMP/ml and Coliformes termotolerantes 20.5 to 1100 NMP/ml. In the evaluation of the quality of the water one used the standards of water quality national ECA-MINAM 002-2008 and the international ones as that of Canada and Economic Community Europea-CEE. he analysis of variance (ANOVA) of the physical, chemical parameters and microbiologicos and the test Tukey, presenting significant differences (p =0.05) in the time as in the space. The riverside flora contributes to the ecosystem and in spite of the presence of the activities antropogenicas the waters of the low basin of the river Viru are suitable for the agricultural use. Key words. riverside flora, water Quality,agricultural use, Viru.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".