Notice bibliographique
Résumé
While our ancestors had no concept of genetics, humans have been genetically modifying organisms through selective breeding for thousands of years to suit their needs. This process of “domestication” started by trial and error and continued successively with the invention of agriculture through systematic and deliberate planting and harvesting of crops. The history of modern-day corn is one example. About 10,000 years ago, ancient farmers of South America took the first steps by domesticating one of the most important food/feed crops in the world that currently provides about 21% of human nutrition across the globe. The past advances have provided food security and allowed for larger and more permanent settlements. As defined by the FAO, “Food security exists when all people, at all times, have physical, social, and economic access to sufficient, safe, and nutritious food which meets their dietary needs and food preferences for an active and healthy life.” The need for food security is as old as the history of mankind. Thomas Malthus (1798) famously predicted that humanity was doomed to food insecurity because of the tendency of populations to grow geometrically with food production increasing only arithmetically. However, inventions and technological advancements in agriculture have allowed humans to keep ahead of the population curve so far. The human population has increased sevenfold over the past two centuries. According to FAO estimates, food production is required to increase up to 70% by 2050 in order to balance food security and the human population, which is anticipated to be 9.6 billion. For more than 80 years, diversity in agricultural crops has been promoted through indirect genetic modifications induced by exposure to radioactivity and/or chemicals. Currently, according to the FAO/IAEA, more than 3,000 plant mutants are registered; with more than 2,000 modified plants being used for food and feed production. These crops are part of our daily diet, but not many questions regarding their food safety have been asked. The most recent global transformations have merged digital, physical, and biological technologies and fundamentally alter the way, size, speed and scope we produce, consume, communicate, and are likely to influence our current thinking and behaviour (Klaus Schwab, 2016). In the past two decades, genetically modified (GM) crops, made possible by the advent and advancement of molecular biology, have brought significant benefits to both farmers and consumers. Novel traits in GM crops have reduced the use of pesticides and herbicides as well as provided higher crop yields compared with their conventional counterparts. Human consumers have benefited from the improved quality products such as canola and soybean with modified oils whereas the livestock sector has benefited from increased yields of GM crops for feed ingredients and their proven safety as livestock feed. Genetically modified crops such as corn, canola, cottonseed, soybean, and potato are largely used in livestock feed rations as sources of energy and protein. At present, more than 340 GM crop lines have been approved for feed use. With the increasing human population, the demand for livestock products is also rising. In addition, with increasing urbanization in the developing world, a 2% increase is estimated in per capita consumption of meat, milk, and eggs. Global demand for meat is anticipated to increase by more than 55% by 2020. With that, the demand for feed grain will also increase by 3.5% per annum. Another major challenge that agricultural productivity faces in the 21st century is climate change and the substantial demand for our first nutrient—water—needed to grow the major global staple crops, including corn, rice, soy, and wheat. Global warming and dwindling availability of fresh water present critical challenges to agriculture, forcing research to further enhance crop performance under suboptimal conditions. These challenges, however, are being met by rapid advances in both our knowledge of plant stress responses and improvements in molecular tools for plant modifications to develop new drought-tolerant crop varieties. Current research in GM crops also aims to improve nutritional characteristics of crops to optimize livestock productivity and performance Biotechnology is also steering towards the development and production of edible biopharmaceuticals derived from various precursors and subsequently manufactured by recombinant plants to be used as feed supplements, for example, as high-throughput vaccine factories. The cultivation of GM crops, however, remains the focus of a global controversy over their safety, trade, regulation, and implications for the environment throughout all sectors of society. Recently, the genome-editing technique CRISPR/Cas9 has revolutionized biology by the ability to modify the parental gene pool without the introduction of foreign gene constructs. Genome editing of crops currently targets: I) improving nutritional value of crops; II) modulating plant responses to environmental stress; III) protecting against novel and emerging pathogens; and IV) developing effective strategies to grow crops in unfavorable climates. DOE Joint Genome Institute “Genomics Garden (source: 2009 Lawrence Berkeley Nat'l Lab; Roy Kaltschmidt, photographer). The genome-editing tool is likely to increase the ongoing development and the commercialisation of GM animals targeting pharmaceutical products or medical application. In the livestock sector, the development and commercialisation of GM farm animals has the potential to facilitate enhanced quality, performance, or nutritional value. Another potential target of genetic engineering may be building the immunity of GM livestock to face the increasing number of globally emerging and evolving pathogens and to prevent catastrophic outbreaks with the development of disease resistance. Globally, regulatory authorities have acknowledged that genome-edited organisms are not transgenic organisms, and therefore, do not fall under the current regulatory framework, creating a legislative vacuum and likely to provoke globally varying views across societies. This technology may very well prove to be a powerful future tool that can be used toward securing the world's food supply. In the holistic picture, any tool available to safeguard the global well-being of humans and the environment should be considered in order to face our future needs and challenges and ensure the security and safety of food and feed as well as the protection of natural resources.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,008 | 0,008 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,018 | 0,027 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,009 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».