Date Palm Genetic Identification and Improvement Utilizing Molecular Markers and DNA Barcoding

Mahdy, Ehab M. B.; El-Sharabasy, Sherif F.

doi:10.1007/978-3-030-73746-7_5

Cited by 4 publications

(3 citation statements)

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“…One of the key achievements in the DP genomics has been the development of the dense genetic linkage maps and high throughput genotyping platforms. Researchers have utilized the variety of molecular markers such as simple sequences repeats (SSRs) [17][18][19], single nucleotide polymorphisms (SNPs) [20,21],and diversity arrays technology (DArT) markers [22,23], to construct the detailed genetic maps of the date palm genome. These maps have enabled the identification of quantitative trait loci (QTLs) associated with economically important traits such as fruit quality, yield and biotic and abiotic stress tolerance as shown in Table 1 [24,25].…”

Section: Genetic Linkage Maps and Marker-assisted Selectionmentioning

confidence: 99%

“…Based on such genome resources DP breeders have increasingly adopted marker -assisted selection (MAS) to accelerate the development of improved cultivars (Figure 3) [28]. By using molecular markers linked to desirable traits, breeders can more effectively select for these traits and pyramid the multiple beneficial alleles in their breeding programs [29,30]. This approach has led to the development of new DP varieties with enhanced characteristics such as higher yields, larger fruit size, and improved shelf life.…”

Section: Pan-genome Analysismentioning

confidence: 99%

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Advancements in Date Palm Genomics and Biotechnology Genomic Resources to the Precision Agriculture: A Comprehensive Review

Pandey,

Tripathi,

Pandey

et al. 2024

Preprint

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In many parts of the Asia, particularly in the arid regions of the middle east the date palm i.e. Phoneix dactylifera L. is considered a significant plant both culturally and economically. Over the past decade numerous biotechnological tools have been applied to revolutionize the date palm research and its cultivation process. In this comprehensive review ,we provided the in depth overview of the cutting edge developments in the date palm biotechnology, mentioning the important areas such as genomics, genetic engineering, in vitro propagation, omics technologies, and the integration of the artificial intelligence and machine learning (AI-ML).Due to these advancements ,in the date palm production how the date palm production lead the production of superior date palm cultivars with the improved yield ,fruit quality and resilience to biotic and abiotic stresses. Also it explores the application of the biotech tools in the enhancing pest and disease management strategies, increasing date palm productivity and developing the date palm based bio-factories for the production of high value compounds. This review highlights the current challenges faced by the date palm industries ,including the limited water resources ,genetic erosion , pests and disease and the need for improved postharvest handling and processing. It examines how these tools coupled with AI-based approaches can be leveraged to address these challenges and ensure the long term sustainability of date palm cultivation.

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Section: Genetic Linkage Maps and Marker-assisted Selectionmentioning

confidence: 99%

Section: Pan-genome Analysismentioning

confidence: 99%

Advancements in Date Palm Genomics and Biotechnology Genomic Resources to the Precision Agriculture: A Comprehensive Review

Pandey,

Tripathi,

Pandey

et al. 2024

Preprint

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show abstract

“…However, date palm trees are a diverse group of plants that can be hard to tell apart by the untrained eye ( Zaid and de Wet, 2002 ). A reliable way to identify date palm species is by using DNA tests that can tell the difference between species based on their genetic code ( Al-Khalifah and Askari, 2003 ; Awan et al., 2017 ; Mahdy and El-Sharabasy, 2021 ; Rahman et al., 2022 ). However, this method is expensive, complicated, and requires specialized equipment and laboratory facilities.…”

Section: Introductionmentioning

confidence: 99%

DPXception: a lightweight CNN for image-based date palm species classification

Safran,

Alrajhi,

Alfarhood

2024

Front. Plant Sci.

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IntroductionDate palm species classification is important for various agricultural and economic purposes, but it is challenging to perform based on images of date palms alone. Existing methods rely on fruit characteristics, which may not be always visible or present. In this study, we introduce a new dataset and a new model for image-based date palm species classification.MethodsOur dataset consists of 2358 images of four common and valuable date palm species (Barhi, Sukkari, Ikhlas, and Saqi), which we collected ourselves. We also applied data augmentation techniques to increase the size and diversity of our dataset. Our model, called DPXception (Date Palm Xception), is a lightweight and efficient CNN architecture that we trained and fine-tuned on our dataset. Unlike the original Xception model, our DPXception model utilizes only the first 100 layers of the Xception model for feature extraction (Adapted Xception), making it more lightweight and efficient. We also applied normalization prior to adapted Xception and reduced the model dimensionality by adding an extra global average pooling layer after feature extraction by adapted Xception.Results and discussionWe compared the performance of our model with seven well-known models: Xception, ResNet50, ResNet50V2, InceptionV3, DenseNet201, EfficientNetB4, and EfficientNetV2-S. Our model achieved the highest accuracy (92.9%) and F1-score (93%) among the models, as well as the lowest inference time (0.0513 seconds). We also developed an Android smartphone application that uses our model to classify date palm species from images captured by the smartphone’s camera in real time. To the best of our knowledge, this is the first work to provide a public dataset of date palm images and to demonstrate a robust and practical image-based date palm species classification method. This work will open new research directions for more advanced date palm analysis tasks such as gender classification and age estimation.

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Genetic improvement of faba bean (Vicia faba L.) genotypes selected for resistance to chocolate spot disease

et al. 2022

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Inter-varietal hybridization is a powerful tool for genetic improvement and production of new genotypes for a trait of interest. Four parents of faba beans (Vicia faba L.) were hybridized using agromorphological and molecular characterization to obtain genotypes resistant to the chocolate spot disease. The study was done at the Nubaria Research Station, Giza, Egypt. Eight traits including resistance to chocolate spot, days to flowering, plant height (cm), number of branches/plant, number of pods/plant, number of seeds/plant, 100-seed weight (g), and seed yield/plant were estimated during the three growth seasons of 2016/2017, 2017/2018, and 2018/2019. Genetic parameters revealed by RAPD and ISSR markers assessed the genetic variation of genotypes with their generations. Crosses 1 (P1 “Nubaria-1” x P2 “Sakha-1”), 2 (P1 “Nubaria-1” x P3 “T.W”), and 3 (P1 “Nubaria-1” x P4 “Camolina”) revealed high resistance to disease with high yield. Markers patterned specific loci of resistant parents at a length of 360, 470, 450, 660, and 140 bp in RAPD and 1100, 810, 650, 700, 480 bp in ISSR. Inter-varietal hybridization between the resistant and susceptible genotypes is considered one of the most promising methods to obtain germplasm with resistance and high yield.

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Date Palm Genetic Identification and Improvement Utilizing Molecular Markers and DNA Barcoding

Cited by 4 publications

References 239 publications

Advancements in Date Palm Genomics and Biotechnology Genomic Resources to the Precision Agriculture: A Comprehensive Review

Advancements in Date Palm Genomics and Biotechnology Genomic Resources to the Precision Agriculture: A Comprehensive Review

DPXception: a lightweight CNN for image-based date palm species classification

Genetic improvement of faba bean (Vicia faba L.) genotypes selected for resistance to chocolate spot disease

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