MétaCan
Menu
Back to cohort
Record W4412775058 · doi:10.3389/fgeed.2025.1632120

Editorial: Gene editing to achieve Zero Hunger

2025· editorial· en· W4412775058 on OpenAlexaboutno aff
Shakeel Ahmad, Iqrar Ahmad Rana, Kevin M. Folta, Christian Damian Lorenzo, Sultan Habibullah Khan

Bibliographic record

VenueFrontiers in Genome Editing · 2025
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersMinistry of Science and Technology, Pakistan
KeywordsZero (linguistics)Computer scienceBiologyComputational biologyGeneticsLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Ensuring universal access to nutritious and healthy food remains a pressing global challenge. In 2015, the United Nations (UN) adopted 17 Sustainable Development Goals with Goal 2 (SDG 2): Zero Hunger, aiming to ensure global food security and to improve nutrition, sustainability in food production and resilience in agricultural practices, well-being and income of small-scale food producers, biodiversity conservation, and investment in agricultural research and gene banks by 2030 (United Nations, 2015). However, several persistent and emerging factors continue to threaten these targets, specifically food security and nutrition. These include a rapidly growing global human population, yield reductions imposed by climate change, and slow-paced plant breeding techniques. Furthermore, social and economic factors have further compromised the present scenario, along with the recent geopolitical conflicts (e.g., Russia-Ukraine, Palestine-Israel, civil war in Sudan, and other countries in East and Central Africa), the COVID-19 pandemic and even ravages derived from natural disasters (e.g., Hurricane Milton) (FAO, 2023). As of now, the global population has reached nearly eight billion and is projected to grow to 8.5 billion by 2030 and 10 billion by 2050. According to the Food and Agriculture Organization (FAO), current agricultural production falls short of meeting present demands and must double by 2030 to keep pace with this growth, highlighting a significant gap between food supply and demand (FAO, 2024). To meet this challenge, the rapid development of climate-resilient, high-yielding crop varieties is essential. This demands a transformative shift in breeding strategies, accelerating the process of developing cultivars that can withstand climate stress, deliver high productivity, and meet both regulatory standards and societal expectations.While conventional breeding methods have substantially contributed to food security, indicators from the SDGs show that the current pace of progress is insufficient to meet expectations. In 2019, the FAO forewarned that continuing at the current pace in crop improvement would not suffice to eradicate hunger, which was also reported by Ahmad et al. (2021), and the same trends have been seen in the current report of 2023 (FAO, 2023). This concern urges the world to move towards innovative and efficient biotechnology and breeding tools. Gene editing technologies (GETs), notably site-directed nucleases, have revolutionized crop improvement. Since its application in plants was demonstrated in 2013 (Shan et al., 2013), CRISPR/Cas has emerged as a robust and efficient tool for developing crops with enhanced yield, stress tolerance, and nutritional quality (Ahmad et al., 2025). The acceptance, deregulation, approval, and eventual commercialization of GETs-derived products can significantly accelerate progress towards Zero Hunger, aligning agricultural innovation with the 2030 SDGs. Hence, in light of the ongoing food security crisis, this special issue aims to present the current status, key advances, and future potential of GETs in achieving SDG 2. The collection includes five articles: two original research articles and three review articles, each highlighting the potential of gene editing in the field of agriculture.Recalcitrance of tropical maize lines to genetic transformation has always limited the application of advanced biotechnological tools for improving agronomically important tropical maize lines. In this regard, Jos Hernandes-Lopes and colleagues successfully enabled gene editing in transformation-recalcitrant agronomically important tropical maize lines using morphogenic regulator (MR)-assisted, agrobacterium-mediated transformation protocol. The VIRESCENT YELLOW-LIKE (VYL) gene, encoding a proteolytic subunit of the chloroplast Clp protease complex, was targeted using the CRISPR/Cas9 system and knockout mutants of three maize lines (CML360, CML444, and PCL1) were efficiently generated. The transformation efficiency remained up to 6.63% in these responsive lines, which was also confirmed by protoplast assays and inherited edits in subsequent generations. The findings of this research will potentially open the doors for gene editing in other recalcitrant tropical maize lines that could be important for food security and nutrition.The legislation and regulatory processes regarding GETs, also referred to as new plant breeding technologies or new genomic technologies, are slow-paced in various countries, which are affecting countries' agriculture and economies, thus lagging them behind the countries that are flexible in embracing the agricultural innovations. In this regard, Stuart J. Smyth and colleagues presented the findings of a survey conducted on Canada’s Plants with Novel Traits (PNTs) regulatory framework, established in the early 1990s. The plant breeders believe the PNTs framework has been outdated and is causing hindrance in developing new varieties using GETs. Thus, the authors have concluded that Canada’s PNTs regulations need to be updated and aligned with technological advancements to foster innovations in agriculture, pertinent to regional as well as global food security and nutrition.Similarly, Ritika Kumari et al., have also summarized regulatory frameworks, guidelines, and legislations of various countries for nano-technology-based products, including the products developed through CRISPR/Cas-based gene editing system, in agriculture.Aayushi Patel and colleagues extensively reviewed the applications and methods of gene editing in various plant species. They summarized the mechanism of action of gene editing systems and their applications in agriculture for developing desirable traits in plants. This review also provides a comprehensive discussion on the regulation of gene-edited crops. Finally, it is concluded that the GETs are a cost-effective, efficient, robust, and innovative plant breeding tool that can help to meet the UN’s sustainable development goals of “zero hunger” and “good human health and well-being”.Cotton is a major and economically important crop worldwide. It directly supports Target 2.3 of SDG 2, by contributing to the economic well-being and livelihood security of small-scale food producers, which is a key pillar of the Zero Hunger goal. In this regard, to cover the potential of CRISPR/Cas-based gene editing systems in cotton, Muhammad Sulyman Saleem and colleagues have extensively reviewed their applications in cotton. They have summarized the utilization of CRISPR/Cas9, CRISPR/nCas9, and CRISPR/Cas12a systems for targeting undesirable genes and improving the 4Fs – fiber, food, feed, and fuel – of cotton, highlighting how cotton improvement can contribute to achieving Zero Hunger by 2030.In conclusion, GETs, particularly CRISPR-based systems, are evolving rapidly and demonstrating high efficiency, reliability, robustness, and effectiveness in generating new, transgene-free, desirable lines that may also bypass strict regulatory processes. As highlighted in various published reports, i.e., those by Aayushi Patel and colleagues and Muhammad Sulyman Saleem and collaborators, these systems have significantly improved a wide range of crops by targeting key traits, thereby contributing to the UN’s mission to achieve sustainable food security and nutrition, as well as to improve well-being and livelihoods of small-scale food producers globally. We hope that the articles featured in this special issue will further underscore the utility of GETs in crop improvement and pave the way for the deregulation of their products, enabling faster outcomes in support of the Zero Hunger goal.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.258
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Genome EditingSame topicCRISPR and Genetic EngineeringFrench-language works237,207