Response of Two Cotton Genotypes to Organic and Inorganic Fertilizers in Two Locations in Sulaymaniyah Province

Cotton plants have a broad range of uses in industry. However, various factors affect their quality leading to the employment of different approaches to achieve optimal production of the crop. In this study, the BM 455 and Golda genotypes were cultivated in two locations (TazaDe and Kani Panka) to determine the impact of treating them with organic (500 kg ha-1) and inorganic (NPK-15:15:15) fertilizers at 200 kg ha-1. NPK application significantly increased growth and yield production in BM 455 while the organic fertilizer was more effective in terms of textile quality for both genotypes. The BM 455 had superior values, whereas Golda recorded the highest values in biological yield, fiber uniformity, elongation, and reflectance in both locations. There was a significant difference for all parameters, with TazaDe being more suitable for cultivation than Kani Panka, except for biological yield. Depending on phenotype and fertilizers, the growth and yield of the BM 455 genotype responded to NPK fertilizer, while both genotypes significantly showed effects on quality characteristics under organic fertilizers. The untreated plants constituted a minority in this study. These findings will aid growers in cultivating the ideal genotypes using the appropriate fertilizers in optimal environmental conditions

Authors

Institutions

Publication Details

Journal
Anbar Journal of Agricultural Sciences
Published
2025-12-31
DOI
https://doi.org/10.32649/ajas.2025.189413
Primary Topic
Research in Cotton Cultivation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Response of Two Cotton Genotypes to Organic and Inorganic Fertilizers in Two Locations in Sulaymaniyah Province

Hawar S. Halshoy, Dayan Ibrahem, S. Mahmood, Sh. Sleman
Anbar Journal of Agricultural Sciences
Research in Cotton Cultivation
article

Response of Two Cotton Genotypes to Organic and Inorganic Fertilizers in Two Locations in Sulaymaniyah Province

Hawar S. Halshoy, Dayan Ibrahem, S. Mahmood, Sh. Sleman
article en

Abstract

Cotton plants have a broad range of uses in industry. However, various factors affect their quality leading to the employment of different approaches to achieve optimal production of the crop. In this study, the BM 455 and Golda genotypes were cultivated in two locations (TazaDe and Kani Panka) to determine the impact of treating them with organic (500 kg ha-1) and inorganic (NPK-15:15:15) fertilizers at 200 kg ha-1. NPK application significantly increased growth and yield production in BM 455 while the organic fertilizer was more effective in terms of textile quality for both genotypes. The BM 455 had superior values, whereas Golda recorded the highest values in biological yield, fiber uniformity, elongation, and reflectance in both locations. There was a significant difference for all parameters, with TazaDe being more suitable for cultivation than Kani Panka, except for biological yield. Depending on phenotype and fertilizers, the growth and yield of the BM 455 genotype responded to NPK fertilizer, while both genotypes significantly showed effects on quality characteristics under organic fertilizers. The untreated plants constituted a minority in this study. These findings will aid growers in cultivating the ideal genotypes using the appropriate fertilizers in optimal environmental conditions

Anbar Journal of Agricultural SciencesVol. 23(2)
University of Sulaimani (IQ)
University of Sulaimani
Openalex Percentile: Top 23%
Research in Cotton Cultivation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.