Journal of Sciences and Engineering 2022-06-29T14:03:36+00:00 Luz Gonzales Open Journal Systems <p><em>Journal of Sciences and Engineering</em> is a peer-reviewed, international and interdisciplinary research journal that focuses on all aspects of Sciences and Engineering. <em>Journal of Sciences and Engineering</em> publishes issues twice a year since 2017. </p> <p>All articles published are Open Access for readers and an article processing charge (APC) applies to papers accepted after Editor and peer review. </p> Nitrogen dose and sowing density in pea (Pisum sativum L.) crops, to obtain higher yields in Barranca [Dosis de nitrógeno y densidad de siembra del cultivo de arveja (Pisum sativum L.), para obtener mayor rendimiento en Barranca] 2022-01-06T12:51:09+00:00 Mily Yolanda Ramírez Quiñones Alberto Martin Medina Villacorta Ritza Consuelo Collas Alva Jaime Braulio Cahuana Flores Andrea Rosario Pari Soto Andrea Luisa Pari Soto Javier Eugenio Gómez Gamarra Dante Daniel Cruz Nieto José Yovera saldarriaga <p>The research deals with nitrogen doses and sowing densities in peas. The objective was to determine which nitrogen dose and planting density obtained the highest yield. The methodology is based on applied research; Therefore, the statistical model of the Completely Random Block Design was used, which consisted of 3 blocks and 6 treatments. The doses were applied at 17 days 1/2 N, 100% P<sub>2</sub>O<sub>5</sub> and 100% K<sub>2</sub>O and 62 days after sowing 1/2 N, it was evaluated from sowing to harvest and the data were processed by analysis of variance of two factors and Duncan, took leaf samples for foliar analysis and determined the total amount of nitrogen used. It was determined that T5 stood out in stem length with 128.42 cm, commercial yield with 12.53 tn/ha, T4 in weight of pods with 620 g, number of pods per plant with 48, T6 in nitrogen concentration with 6.60 g/ 100 g of dry matter and T5 in the amount of nitrogen used with 154.3 kg/ha that obtained the highest yield. It is concluded that the higher dose of nitrogen and less distance that is T5 obtained higher performance exceeding by 24.52% in relation to T1.</p> 2022-01-06T00:00:00+00:00 Copyright (c) 2022 Journal of Sciences and Engineering Multigaussian and plurigaussian simulation to quantify uncertainty in estimating ore grades and rock types in copper deposits [Simulación multigaussiana y plurigaussiana para cuantificar incertidumbre en la estimación de leyes de mineral y tipos de rocas en yacimientos cupríferos] 2022-01-24T15:01:21+00:00 Marco Antonio Cotrina Teatino Juan Antonio Vega González <p>The main objective of this researching was to quantify the uncertainty of a copper deposit using multigaussian simulation of grades of rock types. The developed algorithms for simulation of categorical variables, usgsim for continuous variables and algorithms programmed in Python 3.0. The dimensions of a block are 20x20x15m indexed 81x109x58 in xyz; making a total of 512 082 blocks. The results of the categorical simulations show that there is a probability (p.v. ≥ 0.8) of 19 987, 227 387 and 49 036 blocks for rock type 1, 2 and 3, respectively. Consequently, the quantified uncertainty for this threshold (0.8) is 20 %; representing 58 % of the blocks. On the other hand, the quantification of the uncertainty of continuous variables (associated with grades of Cu and Mo), not less than 90, 80 and 70 %, based on cut-off thresholds of variance per block, resulted in lithology One 353, 1900 and 7553 blocks with Cu grades, which represents 0.07, 0.37 and 1.49 % of the total blocks, respectively; a total of 24, 139 and 582 blocks with grades of Mo, representing 0.006, 0.027 and 0.114 % of the total blocks; for lithology Two there were 106, 648 and 2739 blocks with Cu grades, which represents 0.021, 0.127 and 0.535 % of the total blocks; a total of 32, 129 and 357 blocks with grades of Mo, which represents 0.006, 0.025 and 0.070 % of the total blocks; finally for lithology 3 there were 478, 2324 and 8804 blocks with Cu grades, which represents 0.093, 0.454 and 1.719 % of the total blocks; a total of 93, 355 and 982 blocks with grades of Mo, which represents 0.018, 0.069 and 0.192 % of the total blocks. </p> <p>Finally, it is concluded that it was possible to quantify the uncertainty in the estimation of mineral grades and rock types in a copper deposit.</p> 2022-01-24T00:00:00+00:00 Copyright (c) 2022 Journal of Sciences and Engineering Characterization of gold-bearing tailings by diagnostic leaching for reprocessing by flotation and leaching [Caracterización de relave aurífero mediante lixiviación diagnóstica para reproceso mediante flotación y lixiviación] 2022-06-29T14:03:36+00:00 Juan Antonio Vega Gonzalez Nilthon Emerson Zavaleta Gutiérrez Jheri Anderson Quispe Cueva <p>The purpose of the present investigation is the evaluation to reprocess the Sayapullo tailings, to extract the gold and silver that it still has, for which an initial chemical analysis, granulometric analysis and mineral flotation tests for gold and silver were made, then The percentage of gold extraction was performed by diagnosis of oxidative leaching (DLT).</p> <p>The DLT consists of the quantification of the percentage of gold extraction by cyanidation as the oxidation state of the mineral increases. For this, progressive chemical attacks were carried out with oxidizing agents for each stage in the following order: Sodium Carbonate (Na<sub>2</sub>CO<sub>3</sub>), Hydrochloric Acid (HCl), Sulfuric Acid (H<sub>2</sub>SO<sub>4</sub>) and Nitric Acid (HNO<sub>3</sub>). The gold content in the solutions was determined by ICP-OES and in the solids by fire assay.</p> <p>It is concluded that the Sayapullo tailings have 44.68% free gold, 3.47% gold associated with sulfates, 11.64% gold associated with carbonates, 6.13% gold associated with Cu-Zn sulfides, 31.49% associated with pyrites and arsenopyrites; and 2.60% gold associated with silicates.</p> 2022-06-29T00:00:00+00:00 Copyright (c) 2022 Journal of Sciences and Engineering