基于顏色分布信息的煙葉煙堿含量預(yù)測(cè)模型評(píng)估與比較
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關(guān)鍵詞：顏色分布；煙堿預(yù)測(cè)；回歸模型； 近鄰；無(wú)損檢測(cè)中圖分類號(hào)：TP391.4；TP181 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：2096-4706（2025）08-0132-07
Abstract： This paper uses optical imaging technology to establish an image dataset of abatch oftobacco leaves with knownnicotinecontent，anduses theneuralnetworkmodelU2-Nettoaccuratelydetecttobaccoleaftargets.Byextractingthe color distributioninformationofthetobaccoleaf targets，four typicalMachineLeamingalgorithmsofRF，XGBoost，MP，and KNNareusedtomaketheregressonpredictionforthenicotinecontentof tobacco leaves，respectively.Theresults indicate that theKNNmodelcanefectivelyutilizecolordistributioninformationtoaccuratelypredictthenicotinecontentoftbaccoleaves. The value of determination coefficient is as high as 9 7 . 4 6 % ，theMSE isaslow as O.020 2，and the MAE is as low as 0.075 6，indicatingasigncantcorelationbetweentobaccoleafcolordistributioniformationandnicotinecontent，andprovidingan effective nondestructive detection method for nicotine.
Keywords： color distribution; nicotine prediction;regressionmodel; K-Nearest Neighbor;nondestructive testing
0 引言
煙草作為一種重要的農(nóng)作物，廣泛應(yīng)用于煙草制品的生產(chǎn)，對(duì)于全球經(jīng)濟(jì)和人們的日常生活有著重要的影響。（剩余6969字）