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Sharma A, Hazarika M, Heisnam P, Pandey H, Devadas VASN, Kesavan AK, Kumar P, Singh D, Vashishth A, Jha R, Misra V, Kumar R. Controlled Environment Ecosystem: A Cutting-Edge Technology in Speed Breeding. ACS OMEGA 2024; 9:29114-29138. [PMID: 39005787 PMCID: PMC11238293 DOI: 10.1021/acsomega.3c09060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 05/25/2024] [Accepted: 05/31/2024] [Indexed: 07/16/2024]
Abstract
The controlled environment ecosystem is a meticulously designed plant growing chamber utilized for cultivating biofortified crops and microgreens, addressing hidden hunger and malnutrition prevalent in the growing population. The integration of speed breeding within such controlled environments effectively eradicates morphological disruptions encountered in traditional breeding methods such as inbreeding depression, male sterility, self-incompatibility, embryo abortion, and other unsuccessful attempts. In contrast to the unpredictable climate conditions that often prolong breeding cycles to 10-15 years in traditional breeding and 4-5 years in transgenic breeding within open ecosystems, speed breeding techniques expedite the achievement of breeding objectives and F1-F6 generations within 2-3 years under controlled growing conditions. In comparison, traditional breeding may take 5-10 years for plant population line creation, 3-5 years for field trials, and 1-2 years for variety release. The effectiveness of speed breeding in trait improvement and population line development varies across different crops, requiring approximately 4 generations in rice and groundnut, 5 generations in soybean, pea, and oat, 6 generations in sorghum, Amaranthus sp., and subterranean clover, 6-7 generations in bread wheat, durum wheat, and chickpea, 7 generations in broad bean, 8 generations in lentil, and 10 generations in Arabidopsis thaliana annually within controlled environment ecosystems. Artificial intelligence leverages neural networks and algorithm models to screen phenotypic traits and assess their role in diverse crop species. Moreover, in controlled environment systems, mechanistic models combined with machine learning effectively regulate stable nutrient use efficiency, water use efficiency, photosynthetic assimilation product, metabolic use efficiency, climatic factors, greenhouse gas emissions, carbon sequestration, and carbon footprints. However, any negligence, even minor, in maintaining optimal photoperiodism, temperature, humidity, and controlling pests or diseases can lead to the deterioration of crop trials and speed breeding techniques within the controlled environment system. Further comparative studies are imperative to comprehend and justify the efficacy of climate management techniques in controlled environment ecosystems compared to natural environments, with or without soil.
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Affiliation(s)
- Avinash Sharma
- Faculty of Agricultural Sciences, Arunachal University of Studies, Namsai, Arunachal Pradesh 792103, India
| | - Mainu Hazarika
- Faculty of Agricultural Sciences, Arunachal University of Studies, Namsai, Arunachal Pradesh 792103, India
| | - Punabati Heisnam
- College of Agriculture, Central Agricultural University, Iroisemba, Manipur 795004, India
| | - Himanshu Pandey
- PG Department of Agriculture, Khalsa College, Amritsar, Punjab 143002, India
| | | | - Ajith Kumar Kesavan
- Faculty of Agricultural Sciences, Arunachal University of Studies, Namsai, Arunachal Pradesh 792103, India
| | - Praveen Kumar
- Agricultural Research Station, Agriculture University, Jodhpur, Rajasthan 342304, India
| | - Devendra Singh
- Faculty of Biotechnology, Shri Ramswaroop Memorial University, Barabanki, Uttar Pradesh 225003, India
| | - Amit Vashishth
- Patanjali Herbal Research Department, Patanjali Research Institute, Haridwar, Uttarakhand 249405, India
| | - Rani Jha
- ISBM University, Gariyaband, Chhattishgarh 493996, India
| | - Varucha Misra
- Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow, Uttar Pradesh 226002, India
| | - Rajeev Kumar
- Division of Plant Physiology and Biochemistry, ICAR-Indian Institute of Sugarcane Research, Lucknow, Uttar Pradesh 226002, India
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Uddin N, Shinde H, Ali N, Zhang Q, Ullah R, Iqbal Z, Zhu D. Systematic exploration of Ziziphus species collection and gene identification influencing physiological traits using genotype-by-sequencing technology. PHYSIOLOGIA PLANTARUM 2024; 176:e14426. [PMID: 39049207 DOI: 10.1111/ppl.14426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 06/05/2024] [Accepted: 06/18/2024] [Indexed: 07/27/2024]
Abstract
The Ziziphus genus, belonging to the Rhamnaceae family, holds significant economic, nutritional, and medicinal value. However, much remains to be discovered about its diversity and physical characteristics. Factors such as growth, resilience to changes, disease resistance, and unique features contribute to the quality of Ziziphus species. This study aims to investigate the genomes of 200 genotypes from five Ziziphus species: Ziziphus jujuba (Zj), Ziziphus nummularia (Zm), Ziziphus oxyphylla (Zx), Ziziphus mauritiana (Zm), and the cultivated variety Ziziphus jujube var. jujube, collected from Pakistan and China. Our goal is to identify single nucleotide polymorphisms (SNPs) associated with eight different traits and understand the genetic diversity within the selected Ziziphus species and their genotypes. Using high-quality SNPs obtained through genotype-by-sequencing (GBS), we conducted population structure, phylogenetic, and principal coordinates analyses, identifying a total of 10,945 clean SNPs. These genotypes were categorized into two groups, A and B. Natural Ziziphus variants in Pakistan, specifically Z. jujuba and Z. nummularia, exhibited high levels of genetic diversity and polymorphic information content (PIC) of 0.46 and 0.41, respectively, compared to other species. Furthermore, we identified 15 influential candidate genes that play crucial roles in regulating agronomic traits, such as fruit width and diameter, leaf width, plant height, and stem diameter within this group. This study provides valuable insights that can be utilized in Ziziphus breeding efforts.
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Affiliation(s)
- Nisar Uddin
- Biofuels Institute, School of Emergency Management, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Harshraj Shinde
- Environmental Epigenetics and Genetics Group, Department of Horticulture, College of Agriculture, Food and Environment, University of Kentucky, United States of America
| | - Niaz Ali
- Department of Botany, Hazara University Mansehra, Mansehra, KP, Pakistan
| | - Qiongfang Zhang
- Biofuels Institute, School of Emergency Management, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
| | - Riaz Ullah
- Department of Pharmacognosy; College of Pharmacy King Saud University Riyadh, Saudi Arabia
| | - Zafar Iqbal
- Department of Surgery, College of Medicine, King Saud University P.O.Box 7805, Riyadh, Kingdom of Saudi Arabia
| | - Daochen Zhu
- Biofuels Institute, School of Emergency Management, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang, Jiangsu, China
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Ashraf H, Ghouri F, Baloch FS, Nadeem MA, Fu X, Shahid MQ. Hybrid Rice Production: A Worldwide Review of Floral Traits and Breeding Technology, with Special Emphasis on China. PLANTS (BASEL, SWITZERLAND) 2024; 13:578. [PMID: 38475425 DOI: 10.3390/plants13050578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 01/26/2024] [Accepted: 02/08/2024] [Indexed: 03/14/2024]
Abstract
Rice is an important diet source for the majority of the world's population, and meeting the growing need for rice requires significant improvements at the production level. Hybrid rice production has been a significant breakthrough in this regard, and the floral traits play a major role in the development of hybrid rice. In grass species, rice has structural units called florets and spikelets and contains different floret organs such as lemma, palea, style length, anther, and stigma exsertion. These floral organs are crucial in enhancing rice production and uplifting rice cultivation at a broader level. Recent advances in breeding techniques also provide knowledge about different floral organs and how they can be improved by using biotechnological techniques for better production of rice. The rice flower holds immense significance and is the primary focal point for researchers working on rice molecular biology. Furthermore, the unique genetics of rice play a significant role in maintaining its floral structure. However, to improve rice varieties further, we need to identify the genomic regions through mapping of QTLs (quantitative trait loci) or by using GWAS (genome-wide association studies) and their validation should be performed by developing user-friendly molecular markers, such as Kompetitive allele-specific PCR (KASP). This review outlines the role of different floral traits and the benefits of using modern biotechnological approaches to improve hybrid rice production. It focuses on how floral traits are interrelated and their possible contribution to hybrid rice production to satisfy future rice demand. We discuss the significance of different floral traits, techniques, and breeding approaches in hybrid rice production. We provide a historical perspective of hybrid rice production and its current status and outline the challenges and opportunities in this field.
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Affiliation(s)
- Humera Ashraf
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou 510642, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, College of Agriculture, South China Agricultural University, Guangzhou 510642, China
| | - Fozia Ghouri
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou 510642, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, College of Agriculture, South China Agricultural University, Guangzhou 510642, China
| | - Faheem Shehzad Baloch
- Department of Biotechnology, Faculty of Science, Mersin University, Mersin 33100, Türkiye
| | - Muhammad Azhar Nadeem
- Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas 58140, Türkiye
| | - Xuelin Fu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou 510642, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, College of Agriculture, South China Agricultural University, Guangzhou 510642, China
| | - Muhammad Qasim Shahid
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou 510642, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, College of Agriculture, South China Agricultural University, Guangzhou 510642, China
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Naqvi RZ, Mahmood MA, Mansoor S, Amin I, Asif M. Omics-driven exploration and mining of key functional genes for the improvement of food and fiber crops. FRONTIERS IN PLANT SCIENCE 2024; 14:1273859. [PMID: 38259913 PMCID: PMC10800452 DOI: 10.3389/fpls.2023.1273859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 12/08/2023] [Indexed: 01/24/2024]
Abstract
The deployment of omics technologies has obtained an incredible boost over the past few decades with the advances in next-generation sequencing (NGS) technologies, innovative bioinformatics tools, and the deluge of available biological information. The major omics technologies in the limelight are genomics, transcriptomics, proteomics, metabolomics, and phenomics. These biotechnological advances have modernized crop breeding and opened new horizons for developing crop varieties with improved traits. The genomes of several crop species are sequenced, and a huge number of genes associated with crucial economic traits have been identified. These identified genes not only provide insights into the understanding of regulatory mechanisms of crop traits but also decipher practical grounds to assist in the molecular breeding of crops. This review discusses the potential of omics technologies for the acquisition of biological information and mining of the genes associated with important agronomic traits in important food and fiber crops, such as wheat, rice, maize, potato, tomato, cassava, and cotton. Different functional genomics approaches for the validation of these important genes are also highlighted. Furthermore, a list of genes discovered by employing omics approaches is being represented as potential targets for genetic modifications by the latest genome engineering methods for the development of climate-resilient crops that would in turn provide great impetus to secure global food security.
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Affiliation(s)
- Rubab Zahra Naqvi
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Muhammad Arslan Mahmood
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Shahid Mansoor
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
- International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan
| | - Imran Amin
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Muhammad Asif
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
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Sharma N, Raman H, Wheeler D, Kalenahalli Y, Sharma R. Data-driven approaches to improve water-use efficiency and drought resistance in crop plants. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2023; 336:111852. [PMID: 37659733 DOI: 10.1016/j.plantsci.2023.111852] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 08/23/2023] [Accepted: 08/29/2023] [Indexed: 09/04/2023]
Abstract
With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.
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Affiliation(s)
- Niharika Sharma
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia.
| | - Harsh Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia
| | - David Wheeler
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia
| | - Yogendra Kalenahalli
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, Telangana 502324, India
| | - Rita Sharma
- Department of Biological Sciences, BITS Pilani, Pilani Campus, Rajasthan 333031, India
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Sinha D, Maurya AK, Abdi G, Majeed M, Agarwal R, Mukherjee R, Ganguly S, Aziz R, Bhatia M, Majgaonkar A, Seal S, Das M, Banerjee S, Chowdhury S, Adeyemi SB, Chen JT. Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals. Genes (Basel) 2023; 14:1484. [PMID: 37510388 PMCID: PMC10380062 DOI: 10.3390/genes14071484] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.
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Affiliation(s)
- Dwaipayan Sinha
- Department of Botany, Government General Degree College, Mohanpur 721436, India
| | - Arun Kumar Maurya
- Department of Botany, Multanimal Modi College, Modinagar, Ghaziabad 201204, India
| | - Gholamreza Abdi
- Department of Biotechnology, Persian Gulf Research Institute, Persian Gulf University, Bushehr 75169, Iran
| | - Muhammad Majeed
- Department of Botany, University of Gujrat, Punjab 50700, Pakistan
| | - Rachna Agarwal
- Applied Genomics Section, Bhabha Atomic Research Centre, Mumbai 400085, India
| | - Rashmi Mukherjee
- Research Center for Natural and Applied Sciences, Department of Botany (UG & PG), Raja Narendralal Khan Women's College, Gope Palace, Midnapur 721102, India
| | - Sharmistha Ganguly
- Department of Dravyaguna, Institute of Post Graduate Ayurvedic Education and Research, Kolkata 700009, India
| | - Robina Aziz
- Department of Botany, Government, College Women University, Sialkot 51310, Pakistan
| | - Manika Bhatia
- TERI School of Advanced Studies, New Delhi 110070, India
| | - Aqsa Majgaonkar
- Department of Botany, St. Xavier's College (Autonomous), Mumbai 400001, India
| | - Sanchita Seal
- Department of Botany, Polba Mahavidyalaya, Polba 712148, India
| | - Moumita Das
- V. Sivaram Research Foundation, Bangalore 560040, India
| | - Swastika Banerjee
- Department of Botany, Kairali College of +3 Science, Champua, Keonjhar 758041, India
| | - Shahana Chowdhury
- Department of Biotechnology, Faculty of Engineering Sciences, German University Bangladesh, TNT Road, Telipara, Chandona Chowrasta, Gazipur 1702, Bangladesh
| | - Sherif Babatunde Adeyemi
- Ethnobotany/Phytomedicine Laboratory, Department of Plant Biology, Faculty of Life Sciences, University of Ilorin, Ilorin P.M.B 1515, Nigeria
| | - Jen-Tsung Chen
- Department of Life Sciences, National University of Kaohsiung, Kaohsiung 811, Taiwan
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Anwar Z, Ijaz A, Ditta A, Wang B, Liu F, Khan SMUD, Haidar S, Hassan HM, Khan MKR. Genomic Dynamics and Functional Insights under Salt Stress in Gossypium hirsutum L. Genes (Basel) 2023; 14:1103. [PMID: 37239463 PMCID: PMC10218025 DOI: 10.3390/genes14051103] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 04/25/2023] [Accepted: 04/26/2023] [Indexed: 05/28/2023] Open
Abstract
The changing climate is intensifying salt stress globally. Salt stress is a menace to cotton crop quality and yield. The seedling, germination, and emergence phases are more prone to the effects of salt stress than other stages. Higher levels of salt can lead to delayed flowering, a reduced number of fruiting positions, shedding of fruits, decreased boll weight, and yellowing of fiber, all of which have an adverse effect on the yield and quality of the seed cotton. However, sensitivity toward salt stress is dependent on the salt type, cotton growth phase, and genotype. As the threat of salt stress continues to grow, it is crucial to gain a comprehensive understanding of the mechanisms underlying salt tolerance in plants and to identify potential avenues for enhancing the salt tolerance of cotton. The emergence of marker-assisted selection, in conjunction with next-generation sequencing technologies, has streamlined cotton breeding efforts. This review begins by providing an overview of the causes of salt stress in cotton, as well as the underlying theory of salt tolerance. Subsequently, it summarizes the breeding methods that utilize marker-assisted selection, genomic selection, and techniques for identifying elite salt-tolerant markers in wild species or mutated materials. Finally, novel cotton breeding possibilities based on the approaches stated above are presented and debated.
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Affiliation(s)
- Zunaira Anwar
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 45650, Pakistan; (Z.A.); (A.I.); (A.D.); (S.M.-U.-D.K.); (S.H.); (H.M.H.)
| | - Aqsa Ijaz
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 45650, Pakistan; (Z.A.); (A.I.); (A.D.); (S.M.-U.-D.K.); (S.H.); (H.M.H.)
| | - Allah Ditta
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 45650, Pakistan; (Z.A.); (A.I.); (A.D.); (S.M.-U.-D.K.); (S.H.); (H.M.H.)
- Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad 38000, Pakistan
| | - Baohua Wang
- School of Life Sciences, Nantong University, Nantong 226000, China
| | - Fang Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Science, Anyang 455000, China;
| | - Sana Muhy-Ud-Din Khan
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 45650, Pakistan; (Z.A.); (A.I.); (A.D.); (S.M.-U.-D.K.); (S.H.); (H.M.H.)
| | - Sajjad Haidar
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 45650, Pakistan; (Z.A.); (A.I.); (A.D.); (S.M.-U.-D.K.); (S.H.); (H.M.H.)
- Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad 38000, Pakistan
| | - Hafiz Mumtaz Hassan
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 45650, Pakistan; (Z.A.); (A.I.); (A.D.); (S.M.-U.-D.K.); (S.H.); (H.M.H.)
- Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad 38000, Pakistan
| | - Muhammad Kashif Riaz Khan
- Nuclear Institute for Agriculture and Biology College (NIAB-C), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 45650, Pakistan; (Z.A.); (A.I.); (A.D.); (S.M.-U.-D.K.); (S.H.); (H.M.H.)
- Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad 38000, Pakistan
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Pavani G, Malhotra PK, Verma SK. Flowering in sugarcane-insights from the grasses. 3 Biotech 2023; 13:154. [PMID: 37138783 PMCID: PMC10149435 DOI: 10.1007/s13205-023-03573-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 04/19/2023] [Indexed: 05/05/2023] Open
Abstract
Flowering is a crucial phase for angiosperms to continue their species propagation and is highly regulated. In the current review, flowering in sugarcane and the associated mechanisms are elaborately presented. In sugarcane, flowering has two effects, wherein it is a beneficial factor from the breeder's perspective and crucial for crop improvement, but commercially, it depletes the sucrose reserves from the stalks; hence, less value is assigned. Different species of Saccharum genus are spread across geographical latitudes, thereby proving their ability to grow in multiple inductive daylengths of different locations according in the habituated zone. In general, sugarcane is termed an intermediate daylength plant with quantitative short-day behaviour as it requires reduction in daylength from 12 h 55 min to 12 h or 12 h 30 min. The prime concern in sugarcane flowering is its erratic flowering nature. The transition to reproductive stage which reverts to vegetative stage if there is any deviation from ambient temperature and light is also an issue. Spatial and temporal gene expression patterns during vegetative to reproductive stage transition and after reverting to vegetative state could possibly reveal how the genetic circuits are being governed. This review will also shed a light on potential roles of genes and/or miRNAs in flowering in sugarcane. Knowledge of transcriptomic background of circadian, photoperiod, and gibberellin pathways in sugarcane will enable us to better understand of variable response in floral development.
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Affiliation(s)
- Gongati Pavani
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, 141004 India
| | - Pawan Kumar Malhotra
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, 141004 India
| | - Sandeep Kumar Verma
- Institute of Biological Science, SAGE University, Bypass Road, Kailod Kartal, Indore, Madhya Pradesh 452020 India
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Artificial Intelligence in Food Safety: A Decade Review and Bibliometric Analysis. Foods 2023; 12:foods12061242. [PMID: 36981168 PMCID: PMC10048131 DOI: 10.3390/foods12061242] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/06/2023] [Accepted: 03/09/2023] [Indexed: 03/17/2023] Open
Abstract
Artificial Intelligence (AI) technologies have been powerful solutions used to improve food yield, quality, and nutrition, increase safety and traceability while decreasing resource consumption, and eliminate food waste. Compared with several qualitative reviews on AI in food safety, we conducted an in-depth quantitative and systematic review based on the Core Collection database of WoS (Web of Science). To discover the historical trajectory and identify future trends, we analysed the literature concerning AI technologies in food safety from 2012 to 2022 by CiteSpace. In this review, we used bibliometric methods to describe the development of AI in food safety, including performance analysis, science mapping, and network analysis by CiteSpace. Among the 1855 selected articles, China and the United States contributed the most literature, and the Chinese Academy of Sciences released the largest number of relevant articles. Among all the journals in this field, PLoS ONE and Computers and Electronics in Agriculture ranked first and second in terms of annual publications and co-citation frequency. The present character, hot spots, and future research trends of AI technologies in food safety research were determined. Furthermore, based on our analyses, we provide researchers, practitioners, and policymakers with the big picture of research on AI in food safety across the whole process, from precision agriculture to precision nutrition, through 28 enlightening articles.
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