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3 articles for “variance and environment.”

• Published Subscription 14 Jan 2025

  Evaluation of Improved Sorghum Varieties (Sorghum Bicolor L. Moench) for GrainYield at Midland Areas of Derashe and Gerese Districts, South Ethiopia

  By Tariku Simion Dojamo, Selamawit Markos Takiso, Melese Lema Tessema

  Abstract: One of the main elements restricting a variety's ability to respond in a breeding program is the environment. This is why, in 2021 and 2022 at Derashe and in 2022 at Gerese, five improved sorghum varieties and one standard check were assessed to find more productive midland sorghum types. A randomized complete block with three replications was used in the experiment. Significant differences between treatments of the investigated variables were …

  Published in International Journal of Analytical and Applied Chemistry · Vol. 11, Issue 1, 2025 · pp. 16–21 Read article →

• Published Subscription 1 Nov 2019

  Assessment of the Physiochemical Parameters of Aluu Crude Oil Polluted Soil Environment in Niger Delta.

  By Chukwuemeke. P Ukpaka, C. B. Wecheonwu, T. Y. Puyate, O. E. Ehirim

  Abstract: Investigation was carried out to examine the effect of Crude oil contamination of Aluu soil and some of the physiochemical parameters. The physiochemical parameters studied were temperature, pH value, electrical conductivity and available phosphorus. The result obtained revealed the significant effect of the crude oil contamination on the physicochemical parameter investigated. The statistical analyses used were analysis of variance (ANOVA) and regression analysis. The time has effect on temperature and …

  Published in International Journal of Environmental Chemistry · Vol. 5, Issue 2, 2019 · pp. 30–37 Read article →

• Published Subscription 18 Feb 2026

  A Study on CNN-Based Image Mosaicing

  By Kazi Kutubuddin Sayyad Liyakat, Heena T Shaikh

  Abstract: The intricate tapestry of image mosaicing, while a cornerstone of computer vision, has long been constrained by the rigidity of classical, geometry-driven pipelines. Hand-crafted feature detectors and homography estimators, while effective in controlled environments, prove brittle when confronted with the challenges of real-world scenes: significant parallax, dynamic moving objects, repetitive textures, and illumination variance. This work introduces a fundamental paradigm shift, proposing a deep convolutional neural network (CNN) architecture designed …

  Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article →