人工ニューラルネットワークに基づいて,水田の水中の獣医用薬物検出センサーの設計と予測モデリング
Junshi Huang1, Bolin Huang1, Shuanggen Huang1
1Key Laboratory of Modern Agricultural Equipment of Jiangxi, Jiangxi Agricultural University, Nanchang, 330045, China.
Scientific reports
|February 13, 2026
まとめ
新しいセンサーシステムは,稲田の水中の獣医薬残留物の迅速かつリアルタイムな検出を可能にします. この技術は,農業の安全性にとって極めて重要なスルファメタジン,オフォロキサシン,ドキシサイクリン塩化水素,テトラサイクリン塩化水素を正確にモニターします.
科学分野:
- 農業科学 農業科学とは
- アナリティカル・ケミストリー (Analytical Chemistry) とは
- センサー技術 センサー技術
背景:
- 稲田の水中の獣医薬の残留物は,生態系と人間の健康にリスクをもたらす.
- 現在の検出方法はしばしば遅いため,リアルタイムモニタリングには適していません.
- 効果的なモニタリングは,食品安全と環境保護を確保するために不可欠です.
研究 の 目的:
- 稲田の水中の特定の獣医用薬物の残留物を迅速かつリアルタイムで検出するための新しいセンサーシステムを開発する.
- 獣医薬の濃度を定量化するための正確な予測モデルを確立する.
- 農業用水システムにおける主要な獣医薬の効果的なモニタリングを可能にする.
主な方法:
- デジタル化された電極とSTM32F405RGT6マイクロコントローラを使用したセンサーシステムの開発.
- シグナル生成,検出,処理,ワイヤレス通信 (LoRa/4G) のための複数のハードウェアモジュールの統合.
- コンペティティブ・アダプティブ・リウェイト・サンプリング (CARS) の応用 特徴の選択と濃度予測のための人工ニューラルネットワークモデリング.
主要な成果:
- センサーシステムは,幅広い周波数スペクトル (200 Hz 〜 100 MHz) の測定データ (振幅比,相相差) を成功裏に取得しました.
- モデル入力としての相差データにより,R2値は0.7831から0.8713まで,RMSEPは22.0759から28.1526mg/Lまで,優れた予測性能が得られました.
- このシステムは,水サンプルでスルファメタジン,オフロクサシン,ドキシサイクリン塩化水素,テトラサイクリン塩化水素を効果的に検出することが示されました.
結論:
- 開発されたセンサーシステムは,稲畑の水中の獣医薬残留物の迅速かつリアルタイムなモニタリングのための実行可能なソリューションを提供します.
- システムの精度と効率は,農業用水質管理におけるその適用を支えています.
- この技術は,農業における食品安全と環境モニタリングの強化に貢献します.
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