{"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\/de\/2024\/09\/ai-ushers-in-bew-era-for-strawberry-farming-with-broader-agricultural-implications\/","title":{"rendered":"AI l\u00e4utet eine neue \u00c4ra f\u00fcr den Erdbeeranbau ein und hat Auswirkungen auf die gesamte Landwirtschaft"},"content":{"rendered":"

KI k\u00f6nnte bald mit Menschen zusammenarbeiten, um die perfekte Erdbeere zu z\u00fcchten.<\/b><\/p>\n

Forscher der Western University haben ein KI-System entwickelt, das den Anbau einer der beliebtesten Fr\u00fcchte der Welt - der Erdbeere - zu ver\u00e4ndern verspricht, was sich auf den gesamten Agrarsektor auswirken k\u00f6nnte.<\/span><\/p>\n

Und nein, das hat nichts mit der OpenAI<\/span><\/span><\/span><\/span><\/span>Das Modell o1<\/a>, fr\u00fcher unter dem Codenamen \"Projekt Strawberry\" bekannt.<\/span><\/p>\n

Die <\/span>Studie<\/span><\/a>die in der Zeitschrift Foods ver\u00f6ffentlicht wurde, zeigt einen bemerkenswerten Fortschritt in der Agrartechnologie.\u00a0<\/span><\/p>\n

Mithilfe fortschrittlicher maschineller Lernverfahren hat das Team ein System entwickelt, das den Reifegrad und Krankheiten von Erdbeeren mit einer Genauigkeit von fast 99% erkennen kann - und das alles durch einfache Kamera\u00fcberwachung.<\/span><\/p>\n

\"Wir wollten die Gr\u00f6\u00dfe dieser KI-Modelle reduzieren, um sie f\u00fcr Landwirte und die lokale Produktion praktikabel zu machen\", so Joshua Pearce, Inhaber des John M. Thompson Lehrstuhls f\u00fcr Informationstechnologie und Innovation an der Western Engineering and Ivey Business School.\u00a0<\/span><\/p>\n

\"Wir wollten nicht nur die Genauigkeit erh\u00f6hen, die \u00fcber 98% liegt, sondern auch die Gr\u00f6\u00dfe der Modelle reduzieren.\"<\/span><\/p>\n

Das Besondere an dieser Forschung ist, dass sie sich auf die Zug\u00e4nglichkeit konzentriert. Im Gegensatz zu vielen Hightech-L\u00f6sungen f\u00fcr die Landwirtschaft, die sich an Gro\u00dfbetriebe richten, haben Pearce und sein Kollege Soodeh Nikan ihr System f\u00fcr kleine und mittlere Betriebe entwickelt.<\/span><\/p>\n

Die Methodik des Teams kombiniert innovative KI-Techniken mit praktischem landwirtschaftlichem Wissen:<\/span><\/p>\n

    \n
  1. Sie begannen damit, verschiedene Bilder von Erdbeeren zu sammeln, darunter gesunde Fr\u00fcchte und solche, die von verschiedenen Krankheiten betroffen sind.<\/span><\/li>\n
  2. Diese Bilder wurden dann verarbeitet und erg\u00e4nzt, um einen robusten Trainingsdatensatz zu erstellen.<\/span><\/li>\n
  3. Die Forscher haben drei verschiedene KI-Modelle - Vision Transformer, MobileNetV2 und ResNet18 - aufeinander abgestimmt, die jeweils einzigartige St\u00e4rken f\u00fcr diese Aufgabe mitbringen.<\/span><\/li>\n
  4. Um sicherzustellen, dass die KI mit den Schwankungen in der realen Welt zurechtkommt, wurden Techniken wie Klassengewichtung und synthetische Bilderzeugung eingesetzt.<\/span><\/li>\n
  5. Am wichtigsten ist vielleicht, dass sie \"Aufmerksamkeitsmechanismen\" in die Modelle integriert haben, die es der KI erm\u00f6glichen, sich auf die wichtigsten Teile jedes Bildes zu konzentrieren.<\/span><\/li>\n<\/ol>\n

    Das System zeichnet sich durch zwei Hauptaufgaben aus:<\/p>\n

      \n
    1. Erkennung des Reifegrads<\/strong>: Es kann Erdbeeren genau als reif oder unreif klassifizieren und hilft den Landwirten, den Erntezeitpunkt zu optimieren.<\/li>\n
    2. Identifizierung der Krankheit<\/strong>: Die KI kann sieben verschiedene Arten von Erdbeerkrankheiten erkennen und identifizieren: eckige Blattflecken, Anthraknose-Fruchtf\u00e4ule, Bl\u00fctenf\u00e4ule, Grauschimmel, Blattflecken, Mehltau-Frucht und Mehltau-Blatt.<\/li>\n<\/ol>\n

      Die Ergebnisse sprechen f\u00fcr sich. Mit Genauigkeitsraten von rund 98% \u00fcbertrifft das System fr\u00fchere Versuche der automatischen Erdbeer\u00fcberwachung bei weitem.<\/span><\/p>\n

      Die Auswirkungen dieser Forschung gehen jedoch weit \u00fcber die Verbesserung der Erdbeerertr\u00e4ge hinaus.\u00a0<\/span><\/p>\n

      Das Potenzial zur Verringerung der Lebensmittelverschwendung ist ebenfalls offensichtlich. Nach Angaben der Ern\u00e4hrungs- und Landwirtschaftsorganisation der Vereinten Nationen, <\/span>etwa 14%<\/span><\/a> der produzierten Lebensmittel gehen zwischen Ernte und Einzelhandel verloren.\u00a0<\/span><\/p>\n

      Technologien wie dieses KI-System k\u00f6nnten helfen, dieses Problem zu l\u00f6sen, indem sie den Erntezeitpunkt optimieren und Verluste durch Krankheiten oder \u00dcberreife reduzieren.<\/span><\/p>\n

      \"Die Verringerung von Lebensmittelverschwendung und -kosten ist heutzutage offensichtlich ein gro\u00dfes Thema. Wie jeder bin auch ich immer wieder \u00fcberrascht, wenn ich in den Supermarkt gehe und die Preise f\u00fcr frisches Obst und Gem\u00fcse sehe\", sagt Nikan.\u00a0<\/span><\/p>\n

      \"Bei der Auswahl von Projekten suche ich in der Regel nach sicherheitskritischen Projekten oder nach Projekten, die eine gesellschaftliche Notwendigkeit darstellen. Mit meiner Erfahrung in anderen Bereichen habe ich die Chance ergriffen, mein Wissen und meine Erfahrung auf die Ern\u00e4hrungssicherheit anzuwenden.<\/span><\/p>\n

      F\u00fcr die Zukunft plant das Team bereits, sein System in Au\u00dfenbereichen zu testen und m\u00f6glicherweise Drohnen f\u00fcr eine umfassendere Feld\u00fcberwachung einzusetzen.\u00a0<\/span><\/p>\n

      Sie erforschen auch die Verwendung von KI-generierten synthetischen Bildern, um die Datenanforderungen f\u00fcr das Training effektiver Modelle weiter zu reduzieren.<\/span><\/p>\n

      \"Im Gegensatz zur Aufnahme von Millionen von Erdbeeren, einem wenig effizienten und kostspieligen Ansatz, verwenden wir synthetische Bilder und Open-Source-Software, um selbst Millionen von Bildern mit relativ geringer Computerleistung zu erstellen, was es uns nun erm\u00f6glicht, sehr genaue Beobachtungen \u00fcber Reifegrad und Krankheiten f\u00fcr ganz bestimmte Pflanzen zu machen\", so Nikan.<\/p>\n

      Pearce f\u00fcgte hinzu: \"Die Software ist v\u00f6llig kostenlos und quelloffen, und Landwirte jeder Art k\u00f6nnen sie herunterladen und dann an ihre Bed\u00fcrfnisse anpassen. Sie k\u00f6nnen es vorziehen, dass das KI-System ihnen eine E-Mail schickt oder ihr Telefon anpingt, wenn sie eine Krankheit entdecken, oder sogar ein Bild einer bestimmten Pflanze weiterleitet, die bereit f\u00fcr die Ernte ist. Die Software ist so offen, dass man sie selbst gestalten kann.<\/p>","protected":false},"excerpt":{"rendered":"

      KI k\u00f6nnte bald mit Menschen zusammenarbeiten, um die perfekte Erdbeere zu z\u00fcchten. Forscher an der Western University haben ein KI-System entwickelt, das die Art und Weise, wie wir eine der beliebtesten Fr\u00fcchte der Welt - die Erdbeere - anbauen, zu ver\u00e4ndern verspricht, mit m\u00f6glichen Auswirkungen auf den gesamten Agrarsektor. Und nein, das hat nichts mit dem o1-Modell von OpenAI zu tun, das fr\u00fcher den Codenamen \"Project Strawberry\" trug. Die Studie, die in der Fachzeitschrift Foods ver\u00f6ffentlicht wurde, stellt einen bemerkenswerten Fortschritt in der Agrartechnologie dar. Mithilfe fortschrittlicher Techniken des maschinellen Lernens hat das Team ein System entwickelt, das den Reifegrad und Krankheiten von Erdbeeren mit einer Genauigkeit von fast 99% erkennen kann - und das alles durch einfache<\/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\/de\/2024\/09\/ai-ushers-in-bew-era-for-strawberry-farming-with-broader-agricultural-implications\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\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\/de\/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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