The Importance of Lentils: An Overview

Agriculture, Год журнала: 2024, Номер 14(1), С. 103 - 103

Опубликована: Янв. 7, 2024

The legume family includes approximately 19,300 species across three large subfamilies, of which Papilionoideae stands out with 13,800 species. Lentils were one the first crops to be domesticated by humans, 11,000 BP. They are diploid legumes that belong Papilionoidea subfamily and agricultural importance because their resistance drought fact they grow in soil a pH range 5.5–9; therefore, cultivated various types soil, so have an important role sustainable food feed systems many countries. In addition importance, lentils rich source protein, carbohydrates, fiber, vitamins, minerals. key human nutrition since alternative animal proteins, decreasing meat consumption. Another characteristic legumes, including lentils, is ability form nodules, gives them growth advantage nitrogen-deficient soils enable plant fix atmospheric nitrogen, thus contributing nitrogen facilitating other plants during intercropping. also been applied for protection against diseases, as well phytoremediation, environmental bioindicators identify cytotoxicity. This review addresses agriculture health.

Язык: Английский

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The Prospects of gene introgression from crop wild relatives into cultivated lentil for climate change mitigation

Frontiers in Plant Science, Год журнала: 2023, Номер 14

Опубликована: Март 10, 2023

Crop wild relatives (CWRs), landraces and exotic germplasm are important sources of genetic variability, alien alleles, useful crop traits that can help mitigate a plethora abiotic biotic stresses yield reduction arising due to global climatic changes. In the pulse genus Lens , cultivated varieties have narrow base recurrent selections, bottleneck linkage drag. The collection characterization resources offered new avenues for improvement development stress-tolerant, climate-resilient lentil with sustainable gains meet future food nutritional requirements. Most breeding such as high-yield, adaptation resistance diseases quantitative require identification trait loci (QTLs) marker assisted selection breeding. Advances in diversity studies, genome mapping advanced high-throughput sequencing technologies helped identify many stress-responsive adaptive genes, other CWRs. recent integration genomics plant has resulted generation dense genomic maps, massive genotyping, large transcriptomic datasets, single nucleotide polymorphisms (SNPs), expressed sequence tags (ESTs) research substantially allowed QTLs marker-assisted (MAS) Assembly its species genomes (~4Gbp) opens up newer possibilities understanding architecture evolution this legume crop. This review highlights strides high-density high-resolution QTL mapping, genome-wide MAS, databases assemblies traditionally bred amidst impending climate change.

Язык: Английский

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Management and breeding for rust resistance in legumes

Journal of Plant Pathology, Год журнала: 2024, Номер unknown

Опубликована: Июль 3, 2024

Abstract Rust diseases are a major concern in legume production worldwide causing heavy losses especially developing countries that depend on grain legumes as staple food. Fungal species from Uromyces , Phakopsora and Puccinia genera the main causal agents of various rust diseases. They induce up to 100% yield susceptible cultivars emerging substantial threat global food security. Developing durable resistance has thus become critical breeding objective alongside efforts improve cultural disease management practices. This review specifically focuses recent advances understanding enhancing genetic across diverse crops. Key topics covered include: (i) diversity host range affecting legumes; (ii) strategies practices chemical control; (iii) available screening methods for identifying new sources resistance; (iv) basis resistance, encompassing both genes quantitative trait loci; (v) insights into gene regulation effector molecules leading legume-rust interactions; (vi) genomic-assisted techniques can accelerate development legumes. Overall, this highlights progress made date remaining challenges sustainably managing crops through integrated approaches spanning pathogen biology, advanced phenotyping, molecular breeding.

Язык: Английский

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Identification and Characterization of Resistance to Rust in Lentil and Its Wild Relatives

Plants, Год журнала: 2023, Номер 12(3), С. 626 - 626

Опубликована: Янв. 31, 2023

Lentil rust is a major disease worldwide caused by Uromyces viciae-fabae. In this study, we screened large germplasm collection of cultivated lentils (Lens culinaris ssp. culinaris) and its wild relatives, both in adult plants the field with local isolate during 2 seasons seedlings under controlled conditions four fungal isolates origin. The main results from our study were following: (1) significant number accessions resistance based on hypersensitive reaction (reduced Infection Type (IT)) identified lentil L. ervoides, nigricans L.c. orientalis. IT scores showed clear isolate-specific response suggesting race-specificity, so each might be considered different race. Resistance was against all what basis to develop standard differential set that should priority for definition monitoring. (2) Interestingly, although at lower frequency than ervoides nigricans, also observed within lentil, accession 1561 (L.c. displaying making valuable ready-to-use resource breeding. other available an manner. Accession 1308 (L. ervoides) tested, as well reduced belonging Lens species. (3) addition, screenings allowed identification several partial Disease Severity (DS) despite high IT). Adult Plant resulting severity field, susceptibility seedlings, more frequently culinaris, but

Язык: Английский

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Cell Wall–Based Machine Learning Models to Predict Plant Growth Using Onion Epidermis

International Journal of Molecular Sciences, Год журнала: 2025, Номер 26(7), С. 2946 - 2946

Опубликована: Март 24, 2025

The plant cell wall (CW) is a physical barrier that plays dual role in physiology, providing structural support for growth and development. Understanding the dynamics of CW crucial optimizing crop yields. In this study, we employed onion (Allium cepa L.) epidermis as model system, leveraging its layered organization to investigate stages. Microscopic analysis revealed proportional variations size different epidermal layers, offering insights into adaptations. Fourier transform infrared spectroscopy (FTIR) identified 11 distinct spectral intervals associated with components, highlighting modifications influence elasticity rigidity. Biochemical assays across developmental layers demonstrated cellulose, soluble sugars, antioxidant content, reflecting biochemical shifts during growth. differential expression ten enzyme (CWE) genes, analyzed via RT-qPCR, significant correlations between gene patterns composition changes layers. Notably, levels pectin methylesterase fucosidase enzymes were contents sugar, antioxidants. To complement these findings, machine learning models, including Support Vector Machines (SVM), k-Nearest Neighbors (kNN), Neural Networks, integrate FTIR data, parameters, CWE profiles. Our models achieved high accuracy predicting This underscores intricate interplay among composition, enzymatic activity, dynamics, predictive framework applications enhancing productivity sustainability.

Язык: Английский

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Genomics-Enabled Breeding for Manoeuvring Biotic Stresses in Lentil

Опубликована: Янв. 1, 2024

Язык: Английский

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Machine learning applications for plant conservation

Опубликована: Июнь 8, 2023

Citation Civantos Gómez, Iciar ORCID: https://orcid.org/0000-0003-4133-5520 (2023). Machine learning applications for plant conservation. Thesis (Doctoral), E.T.S. de Ingeniería Agronómica, Alimentaria y Biosistemas (UPM). https://doi.org/10.20868/UPM.thesis.74179.

Язык: Английский

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