{"id":14217,"date":"2024-09-14T19:19:46","date_gmt":"2024-09-14T19:19:46","guid":{"rendered":"https:\/\/dailyai.com\/?p=14217"},"modified":"2024-09-16T10:33:41","modified_gmt":"2024-09-16T10:33:41","slug":"ai-ushers-in-bew-era-for-strawberry-farming-with-broader-agricultural-implications","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nl\/2024\/09\/ai-ushers-in-bew-era-for-strawberry-farming-with-broader-agricultural-implications\/","title":{"rendered":"AI luidt nieuw tijdperk in voor aardbeienteelt, met bredere gevolgen voor de landbouw"},"content":{"rendered":"

AI werkt misschien binnenkort samen met mensen om de perfecte aardbei te kweken.<\/b><\/p>\n

Onderzoekers van de Western University hebben een AI-systeem ontwikkeld dat de manier waarop we een van 's werelds favoriete vruchten telen - de aardbei - belooft te veranderen, met mogelijke gevolgen voor de hele landbouwsector.<\/span><\/p>\n

En nee, dit heeft niets te maken met OpenAI<\/span><\/span><\/span><\/span><\/span>o1-model<\/a>met de codenaam \"Project Strawberry.<\/span><\/p>\n

De <\/span>onderzoek<\/span><\/a>gepubliceerd in het tijdschrift Foods, toont een opmerkelijke sprong voorwaarts in landbouwtechnologie.\u00a0<\/span><\/p>\n

Met behulp van geavanceerde machine learning-technieken heeft het team een systeem ontwikkeld dat in staat is om met een nauwkeurigheid van bijna 99% aardbeirijpheid en ziekten te detecteren - en dat allemaal door middel van eenvoudige camerabewaking.<\/span><\/p>\n

\"We wilden de omvang van deze AI-modellen verkleinen om het iets haalbaars te maken voor boeren en lokale productie,\" zei Joshua Pearce, de John M. Thompson Chair in Information Technology and Innovation aan Western Engineering en Ivey Business School.\u00a0<\/span><\/p>\n

\"We wilden niet alleen de nauwkeurigheid verhogen, die boven de 98% ligt, maar ook de omvang van de modellen verkleinen.\"<\/span><\/p>\n

Wat dit onderzoek onderscheidt, is de focus op toegankelijkheid. In tegenstelling tot veel high-tech landbouwoplossingen die zich richten op grootschalige bedrijven, hebben Pearce en zijn collega Soodeh Nikan hun systeem ontworpen met kleine en middelgrote boerderijen in gedachten.<\/span><\/p>\n

De methodologie van het team combineerde innovatieve AI-technieken met praktische landbouwkennis:<\/span><\/p>\n

    \n
  1. Ze begonnen met het verzamelen van verschillende sets afbeeldingen van aardbeien, waaronder gezonde vruchten en vruchten die door verschillende ziekten zijn aangetast.<\/span><\/li>\n
  2. Deze beelden werden vervolgens verwerkt en aangevuld om een robuuste trainingsdataset te cre\u00ebren.<\/span><\/li>\n
  3. De onderzoekers verfijnden drie verschillende AI-modellen - Vision Transformer, MobileNetV2 en ResNet18 - die elk unieke sterke punten inbrengen in de taak.<\/span><\/li>\n
  4. Om ervoor te zorgen dat de AI de variabiliteit in de echte wereld aankon, gebruikten ze technieken zoals klasseweging en het genereren van synthetische beelden.<\/span><\/li>\n
  5. Misschien wel het meest cruciale was dat ze \"aandachtsmechanismen\" in de modellen integreerden, waardoor de AI zich kon richten op de meest relevante delen van elk beeld.<\/span><\/li>\n<\/ol>\n

    Het systeem blinkt uit in twee hoofdtaken:<\/p>\n

      \n
    1. Rijpheidsdetectie<\/strong>: Het kan aardbeien nauwkeurig classificeren als rijp of onrijp, waardoor boeren de oogsttijd kunnen optimaliseren.<\/li>\n
    2. Identificatie van de ziekte<\/strong>: De AI kan zeven verschillende soorten aardbeienziekten detecteren en identificeren: hoekige bladvlekkenziekte, anthracnose fruitrot, bloesemblauw, grauwe schimmel, bladvlekkenziekte, echte meeldauw fruit en echte meeldauw blad.<\/li>\n<\/ol>\n

      De resultaten spreken voor zich. Met nauwkeurigheidspercentages rond de 98% presteert het systeem veel beter dan eerdere pogingen om aardbeien automatisch te monitoren.<\/span><\/p>\n

      De implicaties van dit onderzoek reiken echter veel verder dan alleen het verbeteren van de opbrengst van aardbeien.\u00a0<\/span><\/p>\n

      Het potentieel om voedselverspilling tegen te gaan is ook evident. Volgens de Voedsel- en Landbouworganisatie van de Verenigde Naties, <\/span>ongeveer 14%<\/span><\/a> van het geproduceerde voedsel gaat verloren tussen de oogst en de detailhandel.\u00a0<\/span><\/p>\n

      Technologie\u00ebn zoals dit AI-systeem kunnen helpen om dit probleem aan te pakken door de oogsttijd te optimaliseren en verliezen door ziekte of overrijpheid te beperken.<\/span><\/p>\n

      \"Het verminderen van verspilling en de kosten van voedsel is tegenwoordig duidelijk een groot probleem. Net als iedereen ben ik altijd verbaasd als ik naar de supermarkt ga en de prijs van vers fruit en groenten zie,\" zei Nikan.\u00a0<\/span><\/p>\n

      \"Bij het kiezen van projecten kijk ik meestal naar iets dat cruciaal is voor de veiligheid of een maatschappelijke behoefte. Met mijn ervaring in andere toepassingen greep ik de kans om mijn kennis en expertise toe te passen op voedselzekerheid.\"<\/span><\/p>\n

      Vooruitkijkend is het team al van plan om hun systeem in een buitenomgeving te testen, mogelijk met behulp van drones voor een bredere veldmonitoring.\u00a0<\/span><\/p>\n

      Ze onderzoeken ook het gebruik van door AI gegenereerde synthetische beelden om de gegevens die nodig zijn voor het trainen van effectieve modellen verder te beperken.<\/span><\/p>\n

      \"In tegenstelling tot het maken van beelden van miljoenen aardbeien, wat een weinig effici\u00ebnte, dure aanpak is, gebruiken we nu synthetische beelden en open-source software om zelf miljoenen beelden te maken, met relatief weinig computerkracht, waardoor we nu zeer gedetailleerde waarnemingen kunnen doen over rijpheid en ziekte voor zeer specifieke planten,\" aldus Nikan.<\/p>\n

      Pearce voegt hieraan toe: \"De software is volledig gratis en open-source en boeren van elk type zijn vrij om het te downloaden en vervolgens aan te passen aan hun behoeften. Ze kunnen er de voorkeur aan geven dat het AI-systeem hen een e-mail stuurt of hun telefoon pingt wanneer ze een ziekte detecteren of zelfs een afbeelding doorstuurt van een specifieke plant die klaar is om geplukt te worden. Je kunt de software helemaal naar je eigen hand zetten.<\/p>","protected":false},"excerpt":{"rendered":"

      AI werkt misschien binnenkort samen met mensen om de perfecte aardbei te kweken. Onderzoekers van de Western University hebben een AI-systeem ontwikkeld dat belooft de manier waarop we een van 's werelds favoriete vruchten telen - de aardbei - te veranderen, met mogelijke gevolgen voor de hele landbouwsector. En nee, dit heeft niets te maken met OpenAI's o1-model, dat voorheen de codenaam \"Project Strawberry\" had. Het onderzoek, gepubliceerd in het tijdschrift Foods, toont een opmerkelijke sprong voorwaarts in landbouwtechnologie. Met behulp van geavanceerde machine learning-technieken heeft het team een systeem gecre\u00eberd dat in staat is om rijpheid en ziekten van aardbeien te detecteren met een nauwkeurigheid van bijna 99%.<\/p>","protected":false},"author":2,"featured_media":14218,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[307],"class_list":["post-14217","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-agriculture"],"yoast_head":"\nAI ushers in new era for strawberry farming, with broader agricultural implications | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/nl\/2024\/09\/ai-ushers-in-bew-era-for-strawberry-farming-with-broader-agricultural-implications\/\" \/>\n<meta property=\"og:locale\" content=\"nl_NL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI ushers in new era for strawberry farming, with broader agricultural implications | DailyAI\" \/>\n<meta property=\"og:description\" content=\"AI may soon work alongside humans to cultivate the perfect strawberry. Researchers at Western University have developed an AI system that promises to transform how we grow one of the world’s favorite fruits \u2013 the strawberry \u2013 with potential ripple effects across the entire agricultural sector. And no, this isn\u2019t related to OpenAI\u2019s o1 model, formerly codenamed \u201cProject Strawberry.\u201d The study, published in the journal Foods, showcases a remarkable leap forward in agricultural technology.\u00a0 Using advanced machine learning techniques, the team has created a system capable of detecting strawberry ripeness and diseases with nearly 99% accuracy \u2013 all through simple\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/nl\/2024\/09\/ai-ushers-in-bew-era-for-strawberry-farming-with-broader-agricultural-implications\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-09-14T19:19:46+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-09-16T10:33:41+00:00\" \/>\n<meta property=\"og:image\" 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