Yazar "Mustafa, Zemran" seçeneğine göre listele

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    Contribution of landraces in wheat breeding
    (Springer International Publishing, 2021) Nadeem, Muhammad Azhar; Yeken, Mehmet Zahit; Tekin, Mehmet; Mustafa, Zemran; Hatipoğlu, Rüştü; Aktaş, Husnu; Alsaleh, Ahmad
    Agricultural production system is extremely vulnerable to climate change, and this change will heavily affect the grain yields, thereby threating the food security worldwide. People from developing countries are at greatest risk of experiencing food insecurity, and today, millions of people are going to bed hungry. Wheat is serving as a staple food for millions of people around the world. Development of high-yielding wheat varieties during the Green Revolution is considered an important event in agricultural history. However, these plant breeding activities also resulted in genetic erosion in wheat. Moreover, it is also believed that after domestication process, selection process also resulted in the loss of genetic diversity of wheat. Therefore, commercial wheat cultivars are prone to various biotic and abiotic stresses. To combat with climate changes and to serve enough quantity of food with quality, there is a need to harness wheat landraces. Landraces are considered as repository of gene pool that enhance the biodiversity and maintain and stabilize the ecosystem in a sustainable way to make it functional. Wheat landraces are traditional crop populations developed by the farmers through natural and human selection under their years of cultivations and have adaptation to local environment and management practices. Wheat landraces have more genetic diversity compared to their cultivated ones, and breeding community has utilized their potential in development of climate-resilient wheat cultivars. Here, we are exploring the role of landraces in wheat breeding and hoping that provided information will catch the attention of breeding community to collect, conserve, and perform breeding activities using wheat landraces. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved.
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    Innovation in the breeding of common bean through a combined approach of in vitro regeneration and machine learning algorithms
    (Frontiers Media SA, 2022) Aasim, Muhammad; Katırcı, Ramazan; Baloch, Faheem Shehzad; Mustafa, Zemran; Bakhsh, Allah; Çiftçi, Vahdettin
    Common bean is considered a recalcitrant crop for in vitro regeneration and needs a repeatable and efficient in vitro regeneration protocol for its improvement through biotechnological approaches. In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. Plumular apice explants pretreated with 20 mg/L BAP exerted a negative impact and resulted in minimum shoot regeneration frequency and shoot count, but produced longer shoots. All output variables (shoot regeneration frequency, shoot counts, and shoot length) increased significantly with the enhancement of BAP concentration in the post-treatment medium. Interaction of the pretreatment x post-treatment medium revealed the need for a specific combination for inducing a high shoot regeneration frequency. Higher shoot count and shoot length were achieved from the interaction of 5 mg/L BAP x 1.00 mg/L BAP followed by 10 mg/L BAP x 1.50 mg/L BAP and 20 mg/L BAP x 1.50 mg/L BAP. The evaluation of data through ML models revealed that R-2 values ranged from 0.32 to 0.58 (regeneration), 0.01 to 0.22 (shoot counts), and 0.18 to 0.48 (shoot length). On the other hand, the mean squared error values ranged from 0.0596 to 0.0965 for shoot regeneration, 0.0327 to 0.0412 for shoot count, and 0.0258 to 0.0404 for shoot length from all ML models. Among the utilized models, the multilayer perceptron model provided a better prediction and optimization for all output variables, compared to other models. The achieved results can be employed for the prediction and optimization of plant tissue culture protocols used for biotechnological approaches in a breeding program of common beans.
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    Magnesium- a forgotten element: Phenotypic variation and genome wide association study in Turkish common bean germplasm
    (Frontiers Media SA, 2022) Baloch, Faheem Shehzad; Nadeem, Muhammad Azha; Sönmez, Ferit; Habyarimana, Ephrem; Mustafa, Zemran; Çiftçi, Vahdettin
    Magnesium (Mg) is the fourth most abundant element in the human body and plays the role of cofactor for more than 300 enzymatic reactions. In plants, Mg is involved in various key physiological and biochemical processes like growth, development, photophosphorylation, chlorophyll formation, protein synthesis, and resistance to biotic and abiotic stresses. Keeping in view the importance of this element, the present investigation aimed to explore the Mg contents diversity in the seeds of Turkish common bean germplasm and to identify the genomic regions associated with this element. A total of 183 common bean accessions collected from 19 provinces of Turkey were used as plant material. Field experiments were conducted according to an augmented block design during 2018 in two provinces of Turkey, and six commercial cultivars were used as a control group. Analysis of variance depicted that Mg concentration among common bean accessions was statistically significant (p < 0.05) within each environment, however genotype x environment interaction was non-significant. A moderate level (0.60) of heritability was found in this study. Overall mean Mg contents for both environments varied from 0.33 for Nigde-Dermasyon to 1.52 mg kg(-1) for Nigde-Derinkuyu landraces, while gross mean Mg contents were 0.92 mg kg(-1). At the province level, landraces from Bolu were rich while the landraces from Bitlis were poor in seed Mg contents respectively. The cluster constellation plot divided the studied germplasm into two populations on the basis of their Mg contents. Marker-trait association was performed using a mixed linear model (Q + K) with a total of 7,900 DArTseq markers. A total of six markers present on various chromosomes (two at Pv01, and one marker at each chromosome i.e., Pv03, Pv07, Pv08, Pv11) showed statistically significant association for seed Mg contents. Among these identified markers, the DArT-3367607 marker present on chromosome Pv03 contributed to maximum phenotypic variation (7.5%). Additionally, this marker was found within a narrow region of previously reported markers. We are confident that the results of this study will contribute significantly to start common bean breeding activities using marker assisted selection regarding improved Mg contents.