Research Article
Growth, Seed and Essential Oil Yield Responses of Coriander (Coriandrum Sativum L.) Varieties to Different Level of Nitrogen at Jimma, South Western Ethiopia
Issue:
Volume 6, Issue 1, March 2025
Pages:
1-16
Received:
5 February 2025
Accepted:
13 May 2025
Published:
30 June 2025
DOI:
10.11648/j.scidev.20250601.11
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Abstract: Coriander productivity in Ethiopia is limited by biotic and abiotic factors, including lack of improved varieties and optimal nitrogen rates. The field experiment was conducted to evaluate the effect of Nitrogen rate on phenology, growth, seed yield and quality of coriander varieties at Jimma Ethiopia. The experiment comprised a factorial combination of four coriander varieties (Denkinesh, Indium-01, Gadisa, and Local) and four nitrogen levels (0, 23, 46, and 69 kg/ha) arranged in a split-plot design with three replications. Coriander varieties and Nitrogen rate were assigned as main plot factor and sub-plot factor respectively. The result of the study indicated that all phenological and growth parameters were significantly influenced by main effect of nitrogen levels and varieties. Most of the yield- and yield-related parameters were also significantly influenced by the main effects of nitrogen level and variety. The highest values for all growth parameters were recorded from Dinknesh variety. Nitrogen level of 69 kg/ha produced the highest value for all growth parameters. The highest number of seed per umbel was recorded from combined application of Gadisa variety with 46 and 69 kg/ha nitrogen, whereas the lowest number of seed per umbel and number of umbels per plant was recorded from combined application of local variety and 0 kg/ha of nitrogen. Gadisa variety gave the highest 1000 seed weight (10.07g), harvest index (59.74g), seed yield per plot (0.45 kg) and hectare (1.38t). Local variety produced the highest yield of essential oil (0.78%) and amount of essential oil (0.39 mL/50g). Application of Nitrogen at the rate of 69kg/ha produced the highest yield and yield components. Leaf numbers per plant, leaf fresh weight per hectare, number of seed per umbel, number of umbels per plant and amount of essential oil per hectare were significantly influenced by interaction of both factors. The highest number of seed per umbel was recorded from the use of Gadisa variety combined with 46 and 69 Kg/ha nitrogen, whereas the lowest number of seed per umbel and number of umbels per plant was recorded from combined use of local variety and 0 kg/ha of nitrogen. The highest amount of essential oil (L/ha) was recorded from Gadisa and Dinknesh variety grown under nitrogen application at the rate of 46 and 69 kg/ha. Denkinesh could be used for its highest herbal yield, whereas the Gadisa variety could be used for its highest seed yield. Nitrogen rate of 69 kg/ha could be used because it produced the highest result for all measured traits. Further research is needed on locations and seasons to determine the response of coriander varieties to different nitrogen levels before conclusions can be drawn.
Abstract: Coriander productivity in Ethiopia is limited by biotic and abiotic factors, including lack of improved varieties and optimal nitrogen rates. The field experiment was conducted to evaluate the effect of Nitrogen rate on phenology, growth, seed yield and quality of coriander varieties at Jimma Ethiopia. The experiment comprised a factorial combinati...
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Review Article
Exploring the Intricacies of Crop Yield Performance Through Genomics
Melkam Anteneh*
Issue:
Volume 6, Issue 1, March 2025
Pages:
17-24
Received:
19 May 2025
Accepted:
7 June 2025
Published:
30 June 2025
DOI:
10.11648/j.scidev.20250601.12
Downloads:
Views:
Abstract: Genomic analysis is central to our effort to decode and enhance crop yield performance, an endeavor that, while promising, comes with its challenges. Yield traits are notoriously intricate; they weave a complex tapestry of genetic and environmental interactions that require extensive datasets for meaningful analysis. This research paper explores the complicated nature of these yield traits, emphasizing the urgency of developing large-scale databases and understanding the nuanced interplay between genotype and environment. By identifying genes linked to markers associated with yields, we can streamline breeding programs, making them faster and more precise. However, we must be candid about the limitations inherent in genomic analysis. It is undeniably powerful for boosting crop productivity, but recognizing its boundaries is equally essential. It improves our data analysis techniques and fosters a comprehensive understanding of yield genetics. SNP markers on high-density arrays may indicate genetic associations with phenotypic variation, but GBS-based genotyping methods may be better suited for identifying causal genetic variants in complex crop species, influenced by rare alleles not adequately represented on SNP arrays. Only then can we promote advancements in plant breeding, ultimately ushering in an era of increased crop productivity. Techniques like genome-wide association studies (GWAS), QTL mapping, and marker-assisted selection help accelerate breeding programs by directly targeting specific genes or loci responsible for these traits. High-throughput genotyping allows for a detailed assessment of genetic variation within and between crop populations. We study genome size, heterozygosity, and identify regions of the genome associated with traits of interest such as yield, stress tolerance, or disease resistance. We detect genomic regions where natural or artificial selection has favored specific alleles, leading to reduced genetic diversity and altered patterns within and between populations. We introduce and utilize genetic variation within specific regions of the genome. Understanding the genetic mechanisms that result in increased vigor and performance in hybrids compared to their inbred parents is critical. Generally, genomic-assisted breeding (GAB) revolutionizes crop improvement by using modern molecular tools to enhance accuracy and efficiency in plant breeding. GAB leverages techniques like marker-assisted selection, association mapping, and genomic selection to identify desirable traits, genes, and genomic regions associated with specific traits, ultimately accelerating the development of new crop varieties.
Abstract: Genomic analysis is central to our effort to decode and enhance crop yield performance, an endeavor that, while promising, comes with its challenges. Yield traits are notoriously intricate; they weave a complex tapestry of genetic and environmental interactions that require extensive datasets for meaningful analysis. This research paper explores th...
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