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      畜禽體溫自動(dòng)監(jiān)測(cè)技術(shù)及應(yīng)用研究進(jìn)展

      2022-11-13 07:57:22謝秋菊劉學(xué)飛劉洪貴吳夢(mèng)茹劉文洋
      關(guān)鍵詞:植入式測(cè)溫紅外

      謝秋菊,劉學(xué)飛,鄭 萍,包 軍,劉洪貴,吳夢(mèng)茹,劉文洋

      ·農(nóng)業(yè)生物環(huán)境與能源工程·

      畜禽體溫自動(dòng)監(jiān)測(cè)技術(shù)及應(yīng)用研究進(jìn)展

      謝秋菊1,劉學(xué)飛1,鄭 萍1,包 軍2,3,4,劉洪貴2,吳夢(mèng)茹1,劉文洋1

      (1. 東北農(nóng)業(yè)大學(xué)電氣與信息學(xué)院,哈爾濱 150030;2. 東北農(nóng)業(yè)大學(xué)動(dòng)物科學(xué)技術(shù)學(xué)院,哈爾濱 150030;3. 農(nóng)業(yè)農(nóng)村部生豬養(yǎng)殖設(shè)施工程重點(diǎn)實(shí)驗(yàn)室,哈爾濱 150030;4. 黑龍江省豬種質(zhì)與生產(chǎn)技術(shù)集成創(chuàng)新工程技術(shù)研究中心,哈爾濱 150030)

      體溫是衡量畜禽健康狀況的重要生理指標(biāo),快速準(zhǔn)確的測(cè)溫方法是進(jìn)行疾病監(jiān)測(cè)及診療的有效手段。該文針對(duì)目前畜禽養(yǎng)殖行業(yè)采用的體溫監(jiān)測(cè)技術(shù)及其發(fā)展進(jìn)行闡述,重點(diǎn)比較了體內(nèi)和體外兩大類(lèi)自動(dòng)化測(cè)溫技術(shù)的優(yōu)缺點(diǎn)以及應(yīng)用場(chǎng)景;詳述了紅外體表測(cè)溫、數(shù)據(jù)傳輸與網(wǎng)絡(luò)以及體溫自動(dòng)監(jiān)測(cè)等技術(shù)在畜禽生產(chǎn)性能、健康監(jiān)測(cè)以及行為監(jiān)測(cè)等方面的應(yīng)用。分析了自動(dòng)測(cè)溫技術(shù)存在著設(shè)備安裝、數(shù)據(jù)傳輸、溫度補(bǔ)償模型建立等難點(diǎn),同時(shí)表明在無(wú)創(chuàng)測(cè)溫、測(cè)量精度、測(cè)溫部位以及畜禽舍環(huán)境調(diào)控等方面應(yīng)作為改進(jìn)研究重點(diǎn),并提出體外檢測(cè)非接觸式紅外熱成像自動(dòng)測(cè)溫技術(shù)以其快速、高效、無(wú)應(yīng)激等優(yōu)點(diǎn),將成為畜禽養(yǎng)殖體溫監(jiān)測(cè)研究及應(yīng)用發(fā)展的重點(diǎn)方向。

      溫度;傳感器;畜禽體溫檢測(cè);紅外熱成像;測(cè)溫補(bǔ)償;體表測(cè)溫;非接觸式測(cè)溫

      0 引 言

      隨著現(xiàn)代畜禽養(yǎng)殖業(yè)規(guī)模化和集約化快速發(fā)展,動(dòng)物福利化養(yǎng)殖及畜禽群體健康受到廣泛關(guān)注。然而,近年來(lái)畜禽疫病頻繁暴發(fā),嚴(yán)重影響了養(yǎng)殖行業(yè)生產(chǎn)經(jīng)濟(jì)效益及中國(guó)肉類(lèi)食品穩(wěn)定供應(yīng)。如何及時(shí)、快速地檢測(cè)畜禽健康狀況是養(yǎng)殖行業(yè)長(zhǎng)期以來(lái)一直迫切需要解決的難點(diǎn)。在畜禽養(yǎng)殖生產(chǎn)中,體溫通常作為反映動(dòng)物生理狀態(tài)的一項(xiàng)重要指標(biāo),其變化直接反映著動(dòng)物的健康狀況。在大部分傳染性疾病中,體溫異常往往是重要警示,對(duì)豬、牛、雞等農(nóng)場(chǎng)動(dòng)物進(jìn)行體溫監(jiān)測(cè)和分析能有效發(fā)現(xiàn)疾病早期癥狀,可及時(shí)通知養(yǎng)殖人員處理,減少養(yǎng)殖企業(yè)的經(jīng)濟(jì)損失。因此,實(shí)現(xiàn)高效、準(zhǔn)確、及時(shí)的動(dòng)物體溫自動(dòng)檢測(cè)已成為養(yǎng)殖行業(yè)關(guān)注和研究的熱點(diǎn)之一。

      然而,體溫監(jiān)測(cè)受到現(xiàn)有生產(chǎn)系統(tǒng)的實(shí)際生產(chǎn)條件限制[1]。通常以直腸溫度反映動(dòng)物核心體溫及健康狀況,傳統(tǒng)的接觸式直腸測(cè)溫方法,使用水銀體溫計(jì)或電子測(cè)溫計(jì)進(jìn)行直腸測(cè)溫,其測(cè)溫時(shí)間長(zhǎng)、費(fèi)力、易引起應(yīng)激反應(yīng)或造成損傷,無(wú)法開(kāi)展群體批量化體溫自動(dòng)巡檢。隨著數(shù)字化、自動(dòng)化測(cè)溫技術(shù)的發(fā)展,畜禽養(yǎng)殖行業(yè)開(kāi)始應(yīng)用自動(dòng)化測(cè)溫技術(shù)開(kāi)展畜禽體溫檢測(cè),并且在生產(chǎn)性能、健康檢測(cè)以及行為監(jiān)測(cè)等方面取得了良好的效果[2]。

      本文著重介紹了體內(nèi)和體外檢測(cè)兩大類(lèi)自動(dòng)化測(cè)溫技術(shù)的發(fā)展應(yīng)用現(xiàn)狀、比較多種測(cè)溫方法的優(yōu)缺點(diǎn),詳述了紅外熱成像體表測(cè)溫技術(shù)發(fā)展應(yīng)用及存在的問(wèn)題,提出了畜禽養(yǎng)殖行業(yè)在體溫健康檢測(cè)需求及發(fā)展趨勢(shì),為開(kāi)展畜禽自動(dòng)化測(cè)溫技術(shù)研究提供參考。

      1 畜禽體溫自動(dòng)檢測(cè)技術(shù)

      近年來(lái),畜禽體溫自動(dòng)檢測(cè)技術(shù)得到大力發(fā)展,學(xué)者們圍繞自動(dòng)化測(cè)溫技術(shù)展開(kāi)了大量試驗(yàn)與研究,并取得一定成效。在畜禽體溫自動(dòng)檢測(cè)中,可分為體內(nèi)和體外兩大類(lèi)測(cè)溫方式,體內(nèi)測(cè)溫通常可統(tǒng)一為植入式方法測(cè)溫,而體外測(cè)溫根據(jù)傳感器與動(dòng)物的接觸方式可分為接觸式與非接觸式兩種測(cè)溫方法??偨Y(jié)了體內(nèi)檢測(cè)植入式和體外檢測(cè)接觸式與非接觸式3種測(cè)溫方法,其測(cè)溫方法各有優(yōu)缺點(diǎn)、適合不同的應(yīng)用場(chǎng)景及動(dòng)物種類(lèi),如表1所示。同時(shí)圍繞著測(cè)溫部位、溫度補(bǔ)償、預(yù)測(cè)模型、應(yīng)用發(fā)展等多方面對(duì)以上3種自動(dòng)測(cè)溫技術(shù)展開(kāi)論述,總體概述框架如圖1所示。

      本文在中國(guó)知網(wǎng)、Web of Science、ScienceDirect等數(shù)據(jù)庫(kù)中,以“豬”“?!薄半u”“畜禽”“體溫”“自動(dòng)”“監(jiān)測(cè)”“植入”“傳感器”“紅外熱成像”“熱應(yīng)激”“行為”等詞匯,根據(jù)標(biāo)題、摘要和關(guān)鍵詞組合使用,共計(jì)檢索了112篇體溫自動(dòng)監(jiān)測(cè)相關(guān)的文獻(xiàn)。文獻(xiàn)涉及的動(dòng)物各類(lèi)主要以豬、牛、雞3種動(dòng)物為主,其中以牛為研究對(duì)象的文獻(xiàn)數(shù)量占比高達(dá)56.7%,而豬和雞分別占比20.2%和14.4%,其他動(dòng)物(如山羊、綿羊、馬駒)僅占比8.7%。在以上畜禽自動(dòng)測(cè)溫方法中,隨著紅外技術(shù)的發(fā)展,近五年來(lái)以紅外為主的非接觸式測(cè)溫方法相關(guān)文獻(xiàn)數(shù)量逐漸攀升(如圖2所示),總占比高達(dá)48.4%??梢灶A(yù)見(jiàn),以紅外為主的非接觸式測(cè)溫將是未來(lái)畜禽養(yǎng)殖體溫監(jiān)測(cè)研究熱點(diǎn)。

      表1 3種測(cè)溫方法對(duì)比

      圖2 近年來(lái)畜禽體溫測(cè)溫方法參考文獻(xiàn)分布

      2 體內(nèi)檢測(cè)方法

      體溫監(jiān)測(cè)技術(shù)發(fā)展進(jìn)程如圖3所示,上半軸為畜禽體溫體內(nèi)檢測(cè)方法。其中,橫軸表示各大重要時(shí)間節(jié)點(diǎn),縱軸表示當(dāng)前時(shí)間節(jié)點(diǎn)到上一時(shí)間節(jié)點(diǎn)總計(jì)檢索到的文獻(xiàn)數(shù)量。早在1974年,Bligh等[3]就提出使用無(wú)線遙測(cè)技術(shù)將傳感器設(shè)備植入奶牛體內(nèi)監(jiān)測(cè)體溫。然而受限于當(dāng)時(shí)植入式測(cè)溫技術(shù),直至1988年,Hetzel等[4]第一次將無(wú)線式轉(zhuǎn)發(fā)器植入于牛右腰以監(jiān)測(cè)核心體溫。隨著無(wú)線遙測(cè)技術(shù)的發(fā)展,將微芯片通過(guò)手術(shù)方式植入耳部監(jiān)測(cè)奶牛發(fā)情得到了首次應(yīng)用。然而,手術(shù)式的植入方式給動(dòng)物帶來(lái)極大不便,通過(guò)口服瘤胃丸的體內(nèi)監(jiān)測(cè)方式極大減輕了動(dòng)物的不適感。隨著技術(shù)的不斷發(fā)展,2010年開(kāi)始通過(guò)以注射式的方式植入微芯片并得到了廣泛應(yīng)用,操作簡(jiǎn)易且提高了體溫監(jiān)測(cè)的精確性。同時(shí)RF(Radio Frequency)射頻技術(shù)在體溫?cái)?shù)據(jù)傳輸方面也逐漸得到發(fā)展應(yīng)用。時(shí)至今日,體內(nèi)溫度檢測(cè)方法日趨成熟。

      2.1 植入式測(cè)溫

      植入式測(cè)溫方法將測(cè)溫裝置植入動(dòng)物體內(nèi)(如消化道、生殖道),檢測(cè)到的溫度數(shù)據(jù)通過(guò)電磁信號(hào)發(fā)送至體外接收器,可分為植入式傳感器技術(shù)、植入式微芯片技術(shù)以及其他技術(shù)等。

      2.1.1 植入式傳感器

      目前奶牛體溫測(cè)量仍以體外測(cè)溫方式為主,研發(fā)一些小型化、高精度的奶牛植入式體溫傳感器和奶牛實(shí)時(shí)監(jiān)測(cè)系統(tǒng)[5-6]可實(shí)現(xiàn)較高的測(cè)量精度,實(shí)時(shí)、準(zhǔn)確地對(duì)奶牛體溫進(jìn)行監(jiān)測(cè)。通過(guò)在奶牛陰道植入含溫度采集、無(wú)線電接收設(shè)備無(wú)線體溫遙測(cè)系統(tǒng)[7-8],對(duì)奶牛陰道溫度進(jìn)行實(shí)時(shí)監(jiān)測(cè),可以為發(fā)情期預(yù)測(cè)、疾病預(yù)防提供重要的數(shù)據(jù)。但是,在陰道內(nèi)植入易造成傳感器滑脫等問(wèn)題,通過(guò)將與會(huì)陰肌肉組織無(wú)排斥反應(yīng)的無(wú)線溫度傳感器植入奶牛會(huì)陰部肌肉,監(jiān)測(cè)會(huì)陰部溫度,進(jìn)行發(fā)情鑒定,解決了傳感器滑脫的問(wèn)題[9-10]。通過(guò)將帶有圓形帶溫納陣列和具有無(wú)線功能的低功耗微系統(tǒng)的可植入膠囊[9]植入奶牛會(huì)陰肌肉以預(yù)測(cè)奶牛發(fā)情,有效防止傳感器位置的偏移。此外,根據(jù)奶牛陰道深處有較大穹大宆腔的特點(diǎn),在傳感器尾部設(shè)計(jì)有較好彈性的5個(gè)防滑落凸指(90°軟膠),在宆腔處形成一個(gè)固定卡位(如圖4所示),能有效防止奶牛運(yùn)動(dòng)時(shí)脫落[6]。同時(shí)有研究表明對(duì)于荷斯坦閹牛的上肩胛骨區(qū)域受環(huán)境溫度的影響較小,易于植入,是植入式熱傳感器標(biāo)簽最可靠和方便的位置[11],如圖5所示。同時(shí)環(huán)境的溫濕度也對(duì)牛體溫測(cè)量有較大影響,如何在微觀理想條件下實(shí)現(xiàn)精準(zhǔn)的體溫檢測(cè)具有極大的挑戰(zhàn)[12]。

      注:縱軸上半軸為體內(nèi)檢測(cè)方法,下半軸為體外檢測(cè)方法。

      圖4 植入式測(cè)溫傳感器實(shí)物圖[6]

      圖5 植入式溫度傳感器植入部位[11]

      2.1.2 植入式微芯片

      與通過(guò)外科手術(shù)方式將傳感器植入畜禽體內(nèi)的方法相比,植入式溫敏微芯片(如圖6所示)可以通過(guò)注射器植入體內(nèi),操作起來(lái)更加方便。植入式溫敏微芯片通常植入于生豬皮下(耳根或頸下)獲取溫度[13],一般來(lái)說(shuō),微芯片測(cè)量的皮下組織溫度比直腸溫度低1 ℃[14]。將植入式微芯片通過(guò)無(wú)線遙測(cè)技術(shù)收集溫度數(shù)據(jù),已經(jīng)應(yīng)用于測(cè)量家禽[15]、羊[16-17]和馬駒[18-19]等動(dòng)物測(cè)溫試驗(yàn)中。羊和馬駒體溫同時(shí)研究表明,皮下體溫與核心體溫存在極好的一致性。此外,通過(guò)射頻識(shí)別技術(shù)(Radio Frequency Identification,RFID)與植入式測(cè)溫相結(jié)合,大幅度提升了數(shù)據(jù)傳輸?shù)男始皽?zhǔn)確率[20]。張國(guó)鋒等[21]采用植入式感溫芯片、RFID閱讀器(如圖7所示)以及水流量傳感器,設(shè)計(jì)并實(shí)現(xiàn)了豬只體溫及飲水檢測(cè)系統(tǒng)。然而RFID閱讀器體積過(guò)大嚴(yán)重影響動(dòng)物的舒適度,由于可注射射頻植入物具有遠(yuǎn)程監(jiān)測(cè)植入部位溫度的能力,Reid等[22]將其與可植入設(shè)備相連,通過(guò)射頻數(shù)據(jù)傳輸提供實(shí)時(shí)的溫度讀數(shù)。Small等[23]利用被動(dòng)射頻識(shí)別轉(zhuǎn)發(fā)器監(jiān)測(cè)肉牛的核心體溫,該技術(shù)在無(wú)創(chuàng)監(jiān)測(cè)小母牛體溫方面具有巨大潛力。Maxwell等[24]等通過(guò)可注射射頻識(shí)別溫度傳感器評(píng)估馬的健康狀況。

      然而,由于芯片長(zhǎng)時(shí)間植入體內(nèi)難免會(huì)造成位置的遷移以及供電問(wèn)題,通過(guò)將微芯片注射進(jìn)入肉雞左胸肌3 cm深處(如圖6所示),有效避免了芯片的遷移和環(huán)境的影響[15];另外,將植入生物傳感器封裝在Bio-Bond生物相容性材料中[20],可以防止生物傳感器在皮膚下遷移,并且其電池續(xù)航時(shí)間可達(dá)38 d。大量的試驗(yàn)研究表明,畜禽動(dòng)物體內(nèi)肌肉位置的植入能有效防止芯片位置的變化,通過(guò)注射方式植入微芯片是一種可靠的替代直腸測(cè)溫的方法。

      圖6 數(shù)據(jù)記錄器和微芯片在雞體腔內(nèi)的具體位置[15]

      圖7 植入式RFID感溫芯片及配套閱讀器[21]

      2.2 其他技術(shù)

      除了上述植入式傳感器以及微芯片測(cè)量體溫,還存在著其他運(yùn)用并不多的植入式測(cè)溫方法,如植入式無(wú)線溫度計(jì)、植入式膠囊以及吞服式瘤胃丸等。Iwasaki等[25]設(shè)計(jì)了一種植入式無(wú)線溫度計(jì)探究了測(cè)溫部位之間的差異以及與奶牛核心體溫之間的關(guān)系。植入式膠囊體積較小,可監(jiān)測(cè)多項(xiàng)生理數(shù)據(jù),郭子平[26]利用無(wú)線能量傳輸技術(shù)實(shí)現(xiàn)了多項(xiàng)數(shù)據(jù)的監(jiān)測(cè)。通過(guò)食道將無(wú)線電瘤胃丸投入瘤胃,監(jiān)測(cè)奶牛瘤胃溫度變化,可實(shí)現(xiàn)對(duì)瘤胃pH值[27]的預(yù)測(cè)以及乳腺炎[28-29]和呼吸道疾病等[30]方面的早期預(yù)警。

      植入式與接觸式測(cè)溫方法相比較,能夠解決接觸式傳感器精度較低,易受畜禽日常行為干擾等問(wèn)題。目前,植入式測(cè)溫方法技術(shù)發(fā)展迅猛,通過(guò)無(wú)創(chuàng)方法將可植入微芯片注射進(jìn)畜禽體內(nèi)實(shí)現(xiàn)不同深度體表溫度的自動(dòng)監(jiān)測(cè)方法成為大部分研究的選擇。雖然植入式測(cè)溫突破了接觸式測(cè)溫設(shè)備固定瓶頸,實(shí)現(xiàn)了自動(dòng)測(cè)溫,但是植入的測(cè)定元件可能會(huì)造成動(dòng)物不適,影響動(dòng)物健康和生產(chǎn)。如何避免這種不利因素以及找到更合適的植入位點(diǎn)是該方法進(jìn)一步改進(jìn)的重點(diǎn)方向。

      3 體外檢測(cè)方法

      體外體溫檢測(cè)技術(shù)發(fā)展歷程如圖3下半軸所示。體外檢測(cè)方法根據(jù)與畜禽的接觸方式可分為接觸式與非接觸式兩種。

      接觸式測(cè)溫技術(shù)發(fā)展較早,早在1983年,Wiersma等[31]就通過(guò)熱敏電阻傳感器測(cè)定奶牛鼓膜附近溫度,其測(cè)溫時(shí)長(zhǎng)可達(dá)10 d。然而直至1998年,基于非接觸式紅外測(cè)溫技術(shù)的紅外溫度計(jì)才首次應(yīng)用于測(cè)量山羊鼓膜溫度。20世紀(jì)初,非接觸式紅外熱成像技術(shù)作為輔助診療手段開(kāi)始運(yùn)用于畜禽疾病早期監(jiān)測(cè)。隨著紅外技術(shù)的不斷發(fā)展,紅外傳感器以其成本低、便攜、易操作的特點(diǎn)在畜禽體溫監(jiān)測(cè)中廣受歡迎。然而單一的體溫?cái)?shù)據(jù)不足以支持動(dòng)物的健康檢測(cè),紅外熱成像測(cè)溫方法逐漸應(yīng)用開(kāi)來(lái)。隨著紅外圖像處理技術(shù)不斷發(fā)展,非接觸式紅外熱成像測(cè)溫方法在畜禽體溫監(jiān)測(cè)中得到大規(guī)模應(yīng)用。結(jié)合紅外熱成像技術(shù)輔助診斷畜禽疾病成為現(xiàn)如今研究熱點(diǎn)。直至今日,非接觸式紅外熱成像技術(shù)已廣泛運(yùn)用于健康監(jiān)測(cè)、疾病診斷以及行為監(jiān)測(cè)等領(lǐng)域。

      3.1 接觸式測(cè)溫

      接觸式體溫監(jiān)測(cè)是通過(guò)傳感器等電子設(shè)備與畜禽身體部位相接觸,依靠傳感器技術(shù)來(lái)獲取畜禽動(dòng)物的體溫信息,即通過(guò)電器元件的電氣參數(shù)檢測(cè)溫度變化實(shí)現(xiàn)畜禽體溫信息檢測(cè)。這種方法以結(jié)構(gòu)簡(jiǎn)單,成本低的特點(diǎn)在畜禽體溫自動(dòng)監(jiān)測(cè)中被各大農(nóng)場(chǎng)廣泛使用。

      在畜禽體溫測(cè)量中,傳感器的選擇主要有熱敏電阻,熱電偶以及數(shù)字溫度傳感器等。熱敏電阻因主要特點(diǎn)是體積小、使用方便、靈敏度高、穩(wěn)定性好、過(guò)載能力強(qiáng)等廣受歡迎。根據(jù)不同的溫度系數(shù),可分為負(fù)溫度系數(shù)熱敏電阻(Negative Temperature Coefficien,NTC)和正溫度系數(shù)熱敏電阻(Positive Temperature Coefficien,PTC),而在畜禽體溫測(cè)量方面多采用NTC(如圖8所示)作為溫度傳感器的測(cè)量探頭[32-35]。例如,Okada等[34]研發(fā)的帶有熱敏電阻和加速度計(jì)的可穿戴無(wú)線節(jié)點(diǎn),實(shí)現(xiàn)20 m內(nèi)無(wú)障得條件下對(duì)雞體溫和運(yùn)動(dòng)量監(jiān)測(cè),有助于有效地早期檢測(cè)高致病性禽流感。武彥等[33]設(shè)計(jì)了一種特殊抗環(huán)境干擾測(cè)溫模塊,將測(cè)量電路、無(wú)線射頻模塊和電源集成在一塊3 cm×6 cm的PCB(Printed Circuit Board)上,并在柔性橡膠耳塞中嵌入溫度傳感器以監(jiān)測(cè)奶牛耳溫,通過(guò)Zigbee技術(shù)傳輸數(shù)據(jù),其測(cè)定精度可達(dá)±0.1℃。

      圖8 熱敏電阻

      與熱敏電阻相比,數(shù)字溫度傳感器具有結(jié)構(gòu)簡(jiǎn)單、體積小、具有可調(diào)分辨率等特點(diǎn),且通過(guò)簡(jiǎn)單的編程便可直接讀出測(cè)溫度數(shù)據(jù)。常用的數(shù)字溫度傳感器型號(hào)有DS18B20型、Tsic型以及ADT7320型等接觸式高精度數(shù)字溫度傳感器。與傳統(tǒng)的熱敏電阻測(cè)溫相比,DS18B20溫度傳感器可直接將溫度轉(zhuǎn)化為數(shù)字信號(hào)輸出,簡(jiǎn)化了復(fù)雜的電路結(jié)構(gòu),在奶牛[35-39]以及蛋雞[40]體溫監(jiān)測(cè)上應(yīng)用廣泛。在群養(yǎng)奶牛體溫實(shí)時(shí)監(jiān)測(cè)系統(tǒng),采用DS18B20數(shù)字溫度傳感器設(shè)計(jì)的體溫監(jiān)測(cè)設(shè)備用于測(cè)量奶牛耳道邊緣溫度,其工作在溫度為30~50 ℃范圍時(shí)精度可達(dá)±0.4 ℃[38]。而劉忠超等[36]在基于安卓奶牛體溫遠(yuǎn)程監(jiān)測(cè)系統(tǒng)中,采用DS18B20數(shù)字溫度傳感器設(shè)計(jì)接觸式低功耗測(cè)溫模塊其測(cè)溫精度可達(dá)±0.1 ℃。

      為保持體溫監(jiān)測(cè)的連續(xù)性,通常對(duì)畜禽進(jìn)行24 h不間斷監(jiān)測(cè),所以在滿足測(cè)量高精度的同時(shí),低功耗的監(jiān)測(cè)也尤為重要。目前,主要應(yīng)用的低功耗的數(shù)字溫度傳感器有ADT7320和Tsic系列。ADT7320具有長(zhǎng)期穩(wěn)定性和可靠性,適合養(yǎng)殖業(yè)動(dòng)物高精度體溫監(jiān)測(cè)的要求,測(cè)溫精度可達(dá)±0.1 ℃,尤其在奶牛監(jiān)測(cè)上應(yīng)用較為廣泛[41-43]。基于Tsic506和Zigbee的蛋雞體溫?zé)o線監(jiān)測(cè)系統(tǒng)[44],其測(cè)量精度可達(dá)±0.2 ℃,測(cè)試距離小于150 m時(shí),系統(tǒng)丟包率在6%左右,雞健康系統(tǒng)平均耗電量小于1W[45]。

      在接觸式測(cè)溫方法中,傳感器的安裝以及測(cè)溫部位的選定往往是較大困擾因素。大部分畜禽動(dòng)物全身被毛,溫度傳感器較難找到最佳位置固定,且受日常行為的影響,往往容易脫落。穿戴式無(wú)線傳感器通過(guò)表帶式的設(shè)計(jì)結(jié)構(gòu)能夠緊密貼合畜禽動(dòng)物體表皮膚,有效避免動(dòng)物運(yùn)動(dòng)時(shí)傳感器的脫落[46]。穿戴式傳感器需針對(duì)特定動(dòng)物體積設(shè)計(jì)研發(fā)。例如,在蛋雞的測(cè)溫中,由于蛋雞體積較小使得傳感器固定較難,且易造成傳感器脫落,考慮易于貼合安裝,日常行為影響較小等因素,有研究開(kāi)發(fā)出硬幣大小的可穿戴式傳感器,將它貼合于雞腿上、雞胸下和雞泄殖腔部位實(shí)現(xiàn)體溫變化監(jiān)測(cè)[32],翼下也通常作為測(cè)溫部位[4,44]。對(duì)于家畜來(lái)講,穿戴式傳感器較家禽更易于佩戴。例如,生豬、奶牛等家畜耳道孔徑較大,溫度穩(wěn)定,且不易受外界環(huán)境影響,常作為測(cè)量體溫的理想部位[33,35,37-38,47];在奶牛鼻子處佩戴K型熱電偶測(cè)量探頭[48],監(jiān)測(cè)奶牛鼻孔附近呼吸時(shí)的溫度來(lái)監(jiān)測(cè)牛的體溫,但奶牛頻繁舔舐鼻翼易造成熱電偶脫落。除此之外,奶牛后腿跖骨,由于被毛稀疏,也可選擇肌肉、血管較為豐厚部位作為固定位置,因此,Kou等[49]設(shè)計(jì)了貝殼形狀的溫度傳感器(如圖9所示),以適應(yīng)牛的解剖結(jié)構(gòu)將其與牛后腿緊密貼合。

      圖9 貝殼狀溫度傳感器安裝示意圖[49]

      通過(guò)合理的選取傳感器安裝位置,盡量避免畜禽日常行為所造成的影響,同時(shí)選取低功耗,體積小以及高精準(zhǔn)率的傳感器,建立良好的無(wú)線數(shù)據(jù)傳輸網(wǎng)絡(luò),才能獲得較好的體溫監(jiān)測(cè)數(shù)據(jù)。

      3.2 非接觸式測(cè)溫

      無(wú)論是接觸式測(cè)溫還是植入式測(cè)溫,都是對(duì)單一或少數(shù)的研究對(duì)象進(jìn)行測(cè)溫試驗(yàn),在面臨大規(guī)模畜禽養(yǎng)殖時(shí),耗費(fèi)的時(shí)間、人工、設(shè)備等成本尤為高昂。非接觸式測(cè)溫方法以其速度快,測(cè)溫范圍廣等優(yōu)點(diǎn),逐漸應(yīng)用于大規(guī)模畜禽養(yǎng)殖中。非接觸式測(cè)溫方式包括熱紅外測(cè)溫、超聲波測(cè)溫、激光測(cè)溫等。由于紅外測(cè)溫的便攜性以及低成本等因素,國(guó)內(nèi)外更偏重于熱紅外測(cè)溫方式。在早期,通常是采用紅外溫度傳感器對(duì)動(dòng)物進(jìn)行測(cè)溫。而隨著技術(shù)發(fā)展,又開(kāi)發(fā)出了利用紅外輻射熱效應(yīng),將物體發(fā)出的紅外輻射轉(zhuǎn)化成肉眼可見(jiàn)圖像的紅外熱成像技術(shù)。

      目前,紅外溫度傳感器通常與無(wú)線傳輸網(wǎng)絡(luò)技術(shù)相結(jié)合構(gòu)建成完整的體溫監(jiān)測(cè)系統(tǒng),通過(guò)無(wú)線傳輸將數(shù)據(jù)采集回終端,以完成實(shí)時(shí)監(jiān)控[50]。以Zigbee通信技術(shù)構(gòu)建的無(wú)線傳感器網(wǎng)絡(luò),其丟包率低,無(wú)線通信距離較大,采集的體溫溫差較小[51],實(shí)現(xiàn)了較好的體溫監(jiān)測(cè)效果。基于無(wú)線射頻識(shí)別技術(shù)與紅外測(cè)溫技術(shù)的方法也應(yīng)用于生豬的體溫測(cè)量中,實(shí)現(xiàn)了智能測(cè)溫[52]。運(yùn)用紅外溫度傳感技術(shù)與無(wú)線傳感網(wǎng)絡(luò)技術(shù)、RFID技術(shù)等計(jì)算機(jī)技術(shù)對(duì)畜禽體溫特征方面能夠進(jìn)行更加全面的監(jiān)測(cè)。然而,由于畜禽舍環(huán)境的原因,數(shù)據(jù)傳輸?shù)姆€(wěn)定與正確性易受影響,應(yīng)當(dāng)加強(qiáng)數(shù)據(jù)的傳輸穩(wěn)定以減少丟包率。

      3.2.2 紅外熱成像技術(shù)

      紅外熱像儀是一種成像測(cè)溫設(shè)備,物體以電磁波的形式向外輻射能量,不同物體的紅外輻射強(qiáng)度不同。紅外熱成像的原理是利用目標(biāo)與周?chē)h(huán)境的溫度和發(fā)射率的差異,產(chǎn)生不同的熱梯度,呈現(xiàn)出紅外輻射能量密度分布圖,即“熱圖像”。

      紅外熱成像(Infrared Thermography,IRT)技術(shù)提供了一種非接觸式體表測(cè)溫方式[1,53]。近年來(lái),在生豬的體溫測(cè)量方法中,基于紅外技術(shù)的體溫監(jiān)測(cè)系統(tǒng)研究取得一定進(jìn)展[54-56],可實(shí)現(xiàn)生豬紅外圖像的自動(dòng)化巡檢采集、有效存儲(chǔ)和遠(yuǎn)程傳輸[57]。通過(guò)對(duì)生豬關(guān)鍵部位感興趣區(qū)域(Region of Interest,ROI)進(jìn)行特征提取[58],獲得區(qū)域溫度分析[54,59],并預(yù)測(cè)生豬核心體溫,從而使得體溫?cái)?shù)據(jù)獲取的更加全面和準(zhǔn)確。而在肉雞體溫的監(jiān)測(cè)方面,由于肉雞體表羽毛區(qū)與非羽毛區(qū)也存在較大差異[60],通常采用頭部高溫區(qū)域溫度反演肉雞翅下溫度[61-62],利用紅外攝像機(jī)的個(gè)體無(wú)創(chuàng)性體溫測(cè)量方法,可自動(dòng)獲取個(gè)體肉雞熱圖像,定義代表核心體溫的身體區(qū)域,并應(yīng)用基于熱成像的統(tǒng)計(jì)模型預(yù)測(cè)體溫[63]。然而,紅外熱像儀測(cè)溫效果會(huì)受風(fēng)速、溫濕度等環(huán)境因素的影響。Wang等[64]提出了一種適用于非接觸式牛體溫測(cè)量的紅外熱成像傳感器融合結(jié)構(gòu)(如圖10所示),利用風(fēng)速計(jì)和溫濕度計(jì),校正了風(fēng)速等環(huán)境因素的影響,直腸記錄的參考溫度和IRT溫度之間的平均和標(biāo)準(zhǔn)差分別為0.04和0.1 ℃。

      圖10 多傳感器結(jié)構(gòu)試驗(yàn)設(shè)置[64]

      除了環(huán)境溫濕度等因素帶來(lái)的影響,對(duì)IRT設(shè)備操作認(rèn)識(shí)不足以及特定地點(diǎn)等因素,也易造成IRT測(cè)溫不同結(jié)果。在使用紅外熱像儀拍攝的同時(shí),還應(yīng)當(dāng)對(duì)其他參數(shù)設(shè)置調(diào)整(如發(fā)射率、距離以及反射溫度等),并通過(guò)對(duì)ROI關(guān)鍵部位進(jìn)行溫度提取以建立起與核心體溫之間的普適性溫度補(bǔ)償預(yù)測(cè)模型(如圖11所示)。同時(shí)將體溫指標(biāo)與動(dòng)物等其他參數(shù)(質(zhì)量、耳標(biāo)身份、采食量、日齡等)相結(jié)合[65],可對(duì)動(dòng)物健康進(jìn)行更加準(zhǔn)確的監(jiān)測(cè),為實(shí)現(xiàn)畜禽舍精準(zhǔn)化管理提供堅(jiān)實(shí)基礎(chǔ)。

      圖11 紅外熱成像畜禽體溫檢測(cè)方法

      表2 動(dòng)物體表監(jiān)測(cè)方法總結(jié)

      此外,處理紅外圖像獲取畜禽體溫信息是一個(gè)非常復(fù)雜的過(guò)程[66]。由于紅外圖像易受噪聲干擾,其對(duì)比度、分辨率往往較低,同時(shí)在測(cè)溫過(guò)程中畜禽的姿態(tài)等因素也影響著成像質(zhì)量[67],因此,對(duì)畜禽ROI體溫信息自動(dòng)提取時(shí)存在著識(shí)別率、準(zhǔn)確率較低等問(wèn)題。將紅外與可見(jiàn)光圖像進(jìn)行配準(zhǔn)并融合,融合之后的圖像包含了更多的信息彌補(bǔ)了紅外圖像的局限性,這種方法也還在探索之中。在未來(lái),準(zhǔn)確高效處理紅外圖像或視頻將進(jìn)一步推動(dòng)紅外熱成像測(cè)溫技術(shù)在畜禽體溫自動(dòng)監(jiān)測(cè)中的應(yīng)用。

      脊髓成像方法常見(jiàn)的技術(shù)挑戰(zhàn)已經(jīng)很明顯確定為:(1)磁化率差異;(2)生理運(yùn)動(dòng);(3)脊髓橫截面尺寸較小。成像的這些性質(zhì)中,人類(lèi)脊髓條件不會(huì)改變,因此未來(lái)的發(fā)展需要開(kāi)發(fā)更好的方法來(lái)克服這些挑戰(zhàn),改善成像[18-19]。

      非接觸式紅外測(cè)溫技術(shù)與接觸式、植入式這兩種測(cè)溫方法相比,能夠減少動(dòng)物的應(yīng)激反應(yīng)且具有較好的監(jiān)測(cè)效果,但是在監(jiān)測(cè)過(guò)程中易受畜禽動(dòng)物日常行為影響(如躺臥,飲水等),較難捕捉到關(guān)鍵測(cè)溫部位而導(dǎo)致體溫測(cè)量出現(xiàn)誤差[50]。因此,應(yīng)當(dāng)進(jìn)一步解決動(dòng)物日常行為的動(dòng)態(tài)體溫監(jiān)測(cè)以提高精準(zhǔn)率。同時(shí),由于畜禽舍環(huán)境溫濕度、風(fēng)速等因素影響,紅外測(cè)溫還需考慮處于不同環(huán)境下,紅外體表溫度與核心體溫之間的差異性并做出相應(yīng)的溫度補(bǔ)償。盡管紅外熱成像技術(shù)在智能動(dòng)物體溫監(jiān)測(cè)方面大有前景,但在復(fù)雜的畜禽舍環(huán)境條件下,還需要進(jìn)一步研究以提高體表溫度測(cè)量的準(zhǔn)確性、穩(wěn)定性和適應(yīng)性。動(dòng)物體表監(jiān)測(cè)方法總結(jié)如表2所示。

      4 體溫?cái)?shù)據(jù)傳輸與網(wǎng)絡(luò)技術(shù)

      畜禽體溫?cái)?shù)據(jù)通過(guò)傳感器、芯片等設(shè)備監(jiān)測(cè),組成無(wú)線傳感網(wǎng)絡(luò),傳輸方式多采用短距離無(wú)線數(shù)據(jù)通信的Zigbee[16,39,51]技術(shù)進(jìn)行體溫監(jiān)測(cè)系統(tǒng)信息數(shù)據(jù)的采集和通信,并實(shí)現(xiàn)監(jiān)測(cè)數(shù)據(jù)的實(shí)時(shí)上傳[48,50-51],同時(shí)還可以將ZigBee技術(shù)、RS485傳輸技術(shù)與傳感技術(shù)相結(jié)合組成新興無(wú)線傳感器網(wǎng)絡(luò)以進(jìn)行數(shù)據(jù)傳輸[40]建立奶牛體溫實(shí)時(shí)監(jiān)測(cè)系統(tǒng);無(wú)線射頻識(shí)別RFID技術(shù)通過(guò)豬、牛等動(dòng)物的耳標(biāo)實(shí)現(xiàn)個(gè)體身份識(shí)別并傳輸溫度數(shù)據(jù)[12],取得較好的效果[22];除此外,在生豬與奶牛的體溫?cái)?shù)據(jù)傳輸中,Wi-Fi技術(shù)[35-36,69]與藍(lán)牙技術(shù)[25]也得到廣泛的應(yīng)用。

      5 測(cè)溫部位分布及補(bǔ)償

      5.1 測(cè)溫部位分布

      在豬、牛和雞等畜禽中,直腸溫度能夠反映其真實(shí)體溫,然而在自動(dòng)體溫監(jiān)測(cè)中,通常無(wú)法采取直腸測(cè)溫方法,往往通過(guò)身體其他部位來(lái)采集溫度數(shù)據(jù),以建立其與直腸溫度之間的關(guān)系來(lái)反映動(dòng)物真實(shí)體溫。

      不同種動(dòng)物,不僅存在不同的測(cè)溫方法,而且測(cè)溫部位選擇也大不相同。對(duì)于雞來(lái)說(shuō),翼下溫度較為接近真實(shí)溫度[32],且在安裝溫度傳感器時(shí)也易于貼合,常作為主要測(cè)溫部位之一。除此之外,還有研究者將雞的頭部、眼睛[70]以及臀部作為測(cè)溫部位,并建立與核心體溫的相關(guān)聯(lián)系以反映雞的體溫變化。在豬的體溫監(jiān)測(cè)中,耳根溫度是生豬體表溫度的典型代表,耳根皮膚溫度可作為豬的熱舒適性指標(biāo)[47],此外,眼睛和額頭等區(qū)域也常作為測(cè)溫部位。然而隨著生豬年齡、生物狀態(tài)等變化(例如分娩),其測(cè)溫部位高相關(guān)性可能發(fā)生改變。在奶牛的體溫測(cè)量中,采用紅外體表測(cè)溫技術(shù)監(jiān)測(cè)到奶牛的眼部、鼻鏡、表皮的溫度與直腸溫度相關(guān)性顯著,其中,眼部溫度最接近奶牛體溫(直腸溫度)[71];同時(shí)Salles等[72]研究表明,在熱舒適性條件下,奶牛的前額溫度與直腸溫度相關(guān)性最高,前額和左右側(cè)腹溫度與溫濕度密切相關(guān)。而大多數(shù)接觸式測(cè)溫試驗(yàn)研究中,常采用奶牛后腿部位測(cè)溫;在植入式測(cè)溫中,多采用皮下或者生殖道進(jìn)行測(cè)溫。3種測(cè)溫方法測(cè)溫部位,如表3所示。

      表3 3種測(cè)溫方法測(cè)溫部位總結(jié)

      5.2 溫度補(bǔ)償技術(shù)

      動(dòng)物的體溫受環(huán)境溫濕度影響,隨之有一定程度的變化。通常在高溫濕度環(huán)境中,奶牛的體溫波動(dòng)較大,在低溫濕度環(huán)境中,體溫波動(dòng)較小[73],因此保持較低的溫濕度有利于奶牛的體溫監(jiān)測(cè);而肉雞和蛋雞直腸溫度與翼下體溫存在一定變化規(guī)律[40],其溫濕度環(huán)境指數(shù)與體表溫度存在良好的線性關(guān)系,隨著肉雞日齡增加,溫濕度的權(quán)重逐漸增大[74]。建立動(dòng)物在不同環(huán)境條件下的體溫變化及測(cè)溫部分與直腸溫度的動(dòng)態(tài)補(bǔ)償關(guān)系非常重要,可作為反映飼養(yǎng)環(huán)境舒適性的重要參考指標(biāo)[72]。因此,在紅外熱成像技術(shù)的體表測(cè)溫中,由于體表部位溫度變化受環(huán)境溫濕度的變化影響[12,71],通過(guò)設(shè)置不同發(fā)射率、測(cè)溫距離[75]等參數(shù),建立所測(cè)體表溫度與直腸溫度之間的線性回歸動(dòng)態(tài)關(guān)系。其中紅外體表測(cè)溫中發(fā)射率的設(shè)置及選擇尤為重要,Soerensen等[76]通過(guò)試驗(yàn)證明母豬裸皮的發(fā)射率在0.96~0.98之間,測(cè)溫效果最好。被毛對(duì)熱成像檢測(cè)畜禽體表溫度精度也存在一定影響,賈桂鋒等[77]根據(jù)熱成像數(shù)據(jù)分析出生豬體表毛發(fā)對(duì)溫度檢測(cè)精度的影響規(guī)律,提出了一種被毛噪聲濾除算法。此外,動(dòng)物隨機(jī)運(yùn)動(dòng)引起的視角變化對(duì)溫度測(cè)量也存在一定偏差,Jiao等[78]提出了一種基于 Kinect傳感器和紅外熱像儀可以補(bǔ)償由于視點(diǎn)角度引起的紅外圖像溫度測(cè)量誤差的方法,經(jīng)過(guò)補(bǔ)償處理后,74°~76°視角測(cè)得溫度圖像與0°視角下溫度圖像的溫差范圍僅為0.03~1.2 ℃。

      同種動(dòng)物的體溫在不同年齡段、不同品種之間以及不同的測(cè)溫部位也存在不小差異。此外,動(dòng)物的體態(tài)(如臥躺、爬跨、站立等)也會(huì)間接造成體溫的波動(dòng)。因此,除了考慮在測(cè)量動(dòng)物體溫時(shí)外部因素(環(huán)境,體溫采集方法等)作用造成的差異,還應(yīng)當(dāng)綜合考慮上述動(dòng)物內(nèi)部影響因素,以期在未來(lái)健康監(jiān)測(cè)等方面做出重要指示。

      5.3 測(cè)溫部位與核心體溫關(guān)系模型

      在紅外測(cè)溫試驗(yàn)中,動(dòng)物體表溫度受多種因素影響作用,例如:環(huán)境溫濕度、風(fēng)速、地表溫度以及動(dòng)物不同生產(chǎn)階段等因素。為建立起測(cè)溫部位與核心體溫之間的普適性溫度預(yù)測(cè)模型,通常對(duì)畜禽等動(dòng)物不同身體區(qū)域多個(gè)部位溫度進(jìn)行多天連續(xù)監(jiān)測(cè),并將體溫?cái)?shù)據(jù)以及各項(xiàng)監(jiān)測(cè)參數(shù)進(jìn)行數(shù)理統(tǒng)計(jì)分析得到與其核心體溫之間的相關(guān)性系數(shù)以及回歸模型等。目前,多采用一元或多元線性回歸分析方法建立體溫預(yù)測(cè)模型[71,76,79-82]。近年來(lái),通過(guò)一些非線性方法建立體表溫度與核心溫度關(guān)系模型的研究,逐漸成為熱點(diǎn)。諸如,最小二乘支持向量機(jī)(Least Squares Support Vector Machine,LS-SVM)、高斯過(guò)程(Gaussian Process,GP)和偏最小二乘(Partial Least Squares,PLS)機(jī)器學(xué)習(xí)等方法[83];結(jié)合天氣數(shù)據(jù)和體表溫度人工神經(jīng)網(wǎng)絡(luò)模型[84],以舍內(nèi)CO2、環(huán)境溫濕度等為參數(shù)的人工神經(jīng)網(wǎng)絡(luò)與多元線性回歸相結(jié)合[85]的核心體溫預(yù)測(cè);基于蛋雞頭部和腿部最高溫度的多元線性回歸和BP(Back Propagation)神經(jīng)網(wǎng)絡(luò)肉雞翅下體溫反演模型[86];結(jié)合環(huán)境條件(干球溫度和相對(duì)濕度)建立模糊神經(jīng)網(wǎng)絡(luò)模型以預(yù)測(cè)蛋雞眼球和雞冠溫度[87]。然而,隨著智能感知技術(shù)的發(fā)展,對(duì)體表溫度的監(jiān)測(cè)已不局限于某個(gè)部位,人們開(kāi)始探索最能代表體表溫度變化的測(cè)溫敏感區(qū)域,將敏感區(qū)域的大量溫度數(shù)據(jù)、圖像數(shù)據(jù)相結(jié)合,融入動(dòng)物所處的環(huán)境數(shù)據(jù),來(lái)研究體表溫度與核心溫度之間的關(guān)系,以期構(gòu)建精確的核心體溫模型,為非接觸式測(cè)溫方法奠定重要的理論依據(jù)。因此,傳統(tǒng)的一元或多元線性回歸模型已逐漸不能勝任大數(shù)據(jù)智能驅(qū)動(dòng)的體表溫度與核心溫度關(guān)系模型構(gòu)建要求,在未來(lái)的研究中應(yīng)當(dāng)盡可能的建立基于多參數(shù)數(shù)據(jù)的非線性或深度網(wǎng)絡(luò)模型。

      6 應(yīng)用領(lǐng)域

      6.1 生產(chǎn)性能

      畜禽動(dòng)物生產(chǎn)性能是衡量整個(gè)農(nóng)場(chǎng)經(jīng)濟(jì)效應(yīng)的關(guān)鍵因素,通常包括了產(chǎn)值表現(xiàn)(蛋奶數(shù)量等)、增重率以及繁殖率如動(dòng)物發(fā)情、分娩、妊娠等方面。除了反芻和進(jìn)食時(shí)間可作為發(fā)情的預(yù)測(cè)指標(biāo)外[88],有研究表明,奶牛發(fā)情期陰道溫度平均最大升高(0.9±0.3)℃,發(fā)情前3 d陰道溫度明顯降低,發(fā)情中期明顯升高[8]。因此,監(jiān)測(cè)動(dòng)物外陰等部位溫度的變化能夠有效進(jìn)行發(fā)情預(yù)測(cè)。在試驗(yàn)研究中,多通過(guò)溫敏傳感器[8-10]、熱敏電阻[89]、微芯片[13]等設(shè)備植入外陰或皮下等部位進(jìn)行體溫監(jiān)測(cè)以預(yù)測(cè)發(fā)情。然而,相比只監(jiān)測(cè)外陰溫度并設(shè)置溫度閾值來(lái)監(jiān)測(cè)發(fā)情,結(jié)合畜禽活動(dòng)量、進(jìn)食量以及飲水量等因素的變化情況[48,88],預(yù)測(cè)率得到了更高的提升。

      6.2 健康檢測(cè)

      6.2.1 熱應(yīng)激監(jiān)測(cè)

      畜禽熱應(yīng)激反應(yīng)常出現(xiàn)在夏季高溫時(shí)節(jié),通常伴隨著直腸溫度、體表溫度以及呼吸頻率的升高[90-91]。Chung等[12]設(shè)計(jì)了兩種低成本、低功耗的測(cè)溫設(shè)備,通過(guò)將微芯片植入耳朵和接觸式傳感器貼合頸部,以探究熱應(yīng)激奶牛頸部、耳朵與核心體溫之間的關(guān)系。然而,植入式方法總是無(wú)法避免侵入性手術(shù)及相關(guān)副作用,紅外測(cè)溫方法以其無(wú)創(chuàng)、測(cè)溫范圍廣等優(yōu)點(diǎn)已逐漸應(yīng)用于監(jiān)測(cè)畜禽熱應(yīng)激。例如:通過(guò)紅外溫度計(jì)測(cè)量雞翼下、泄殖腔等部位體溫以監(jiān)測(cè)肉雞熱應(yīng)激認(rèn)知行為[15];利用非接觸式紅外熱成像技術(shù)測(cè)定奶牛眼球最大值溫度,為早期診斷奶牛熱應(yīng)激提供了一種可行性方法[92]。

      6.2.2 疾病監(jiān)測(cè)

      呼吸道疾病常見(jiàn)于豬、牛等動(dòng)物中,通過(guò)吞服網(wǎng)狀瘤胃溫度丸[30]和紅外技術(shù)測(cè)量豬牛眼睛溫度[93-94]可用作早期檢測(cè)豬牛呼吸系統(tǒng)疾病。但是,核心體溫的升高并不是呼吸道疾病的特異性,心率和呼吸速率也是關(guān)鍵生理指標(biāo)[94-95]。除了通過(guò)紅外技術(shù)獲取豬的體溫外,Jorquera等[94]還使用基于計(jì)算機(jī)技術(shù)的RGB(Red, Green, and Blue)和紅外圖像來(lái)測(cè)量評(píng)估豬的心率和呼吸率,并結(jié)合體溫監(jiān)測(cè)作為豬場(chǎng)呼吸系統(tǒng)疾病的早期預(yù)警。這表明計(jì)算機(jī)視覺(jué)和紅外測(cè)溫技術(shù)結(jié)合可更好進(jìn)行疾病診斷。

      奶牛乳腺炎通常發(fā)生在泌乳期,常伴有較高的體溫升高。通過(guò)實(shí)時(shí)測(cè)量奶牛網(wǎng)狀體溫[96]、瘤胃溫度[29]、眼睛溫度[97]以及乳房表面溫度[98-99],監(jiān)測(cè)乳腺炎的發(fā)病機(jī)制,達(dá)到早期發(fā)現(xiàn)乳腺炎的目的。隨著紅外圖像技術(shù)的發(fā)展,紅外熱成像測(cè)溫方法以其智能、準(zhǔn)確、無(wú)接觸等特點(diǎn),逐漸應(yīng)用于奶牛乳房炎的檢測(cè)[100]。除此之外,在其他種類(lèi)的疾病檢測(cè)方面體溫監(jiān)測(cè)均有應(yīng)用。例如:利用紅外圖像提取生豬耳部顏色判斷是否患有藍(lán)耳病,準(zhǔn)確率可達(dá)到77%[101];非接觸式紅外熱成像進(jìn)行非洲豬瘟的早期監(jiān)測(cè)[102];紅外熱成像進(jìn)行牛蹄表面溫度[103]、肉雞腿部非炎癥類(lèi)病變監(jiān)測(cè)[104],再結(jié)合姿態(tài)特征來(lái)綜合判斷是否發(fā)生腿部異常,以此來(lái)評(píng)估健康狀況。大量試驗(yàn)研究表明,非接觸式體溫監(jiān)測(cè)可為動(dòng)物健康檢測(cè)及診斷提供更加方便、快速的技術(shù)手段,將會(huì)在今后動(dòng)物健康預(yù)警方面有巨大的應(yīng)用空間。

      6.3 行為監(jiān)測(cè)

      畜禽體溫不僅易受舍內(nèi)空間環(huán)境溫濕度以及晝夜變化等因素影響[105-106],日常行為狀態(tài)也會(huì)引起體溫的變化。有研究表明,通過(guò)穿戴式無(wú)線感溫設(shè)備監(jiān)測(cè)蛋雞翼下溫度,其長(zhǎng)時(shí)間的攝食過(guò)程會(huì)產(chǎn)生類(lèi)似于生蛋特征峰的體溫上升小峰,但是上升的時(shí)間與峰值高度相較生蛋特征峰較短且較低[32]。生豬耳朵皮膚溫度與其日常行為也存在一定關(guān)聯(lián),通過(guò)接觸式耳標(biāo)溫度傳感器監(jiān)測(cè)生豬體溫,并結(jié)合躺臥、站立等姿勢(shì)行為,結(jié)果表明,與活動(dòng)時(shí)相比,豬在躺臥休息時(shí)耳部皮膚溫度更高[47]。

      同時(shí),通過(guò)奶牛群飲水吞服溫度丸劑,對(duì)網(wǎng)狀管腔溫度進(jìn)行有效的判斷[107-108]。此外,利用紅外技術(shù)進(jìn)行體溫檢測(cè)可作為早期母豬跛行[109]、奶牛跛行運(yùn)動(dòng)特征的提取與檢測(cè)[110]以及斷奶豬仔接種疫苗后的發(fā)熱和行為反應(yīng)指標(biāo)[111]。然而,除了體溫?cái)?shù)據(jù)外,還應(yīng)當(dāng)融合多種無(wú)損檢測(cè)技術(shù)獲取呼吸頻率、心率、運(yùn)動(dòng)量等數(shù)據(jù)[112],并結(jié)合視頻或圖像等,才能更好的綜合判斷畜禽異常行為及生理狀態(tài),為早期疾病預(yù)警提供可行性參考。

      7 問(wèn)題與展望

      近年來(lái),畜禽體溫自動(dòng)監(jiān)測(cè)技術(shù)發(fā)展迅猛,解決了傳統(tǒng)人工監(jiān)測(cè)耗時(shí)耗力等缺點(diǎn),在畜禽生產(chǎn)性能、健康監(jiān)測(cè)以及動(dòng)物行為監(jiān)測(cè)等方面表現(xiàn)效果較好。盡管?chē)?guó)內(nèi)外學(xué)者對(duì)畜禽體溫自動(dòng)監(jiān)測(cè)技術(shù)做了大量研究與改進(jìn),但其自動(dòng)監(jiān)測(cè)技術(shù)在精準(zhǔn)性,數(shù)據(jù)傳輸抗干擾能力等方面還有待改進(jìn)。

      在接觸式測(cè)溫中,傳感器的佩帶部位及固定是一大困擾因素,合理選擇穿戴式的設(shè)備能夠較好固定于動(dòng)物身上,且可放置多傳感器以監(jiān)測(cè)多項(xiàng)畜禽生理指標(biāo)。由于多數(shù)畜禽舍環(huán)境復(fù)雜惡劣,傳感器的選擇應(yīng)當(dāng)能適應(yīng)一些極端惡劣環(huán)境(如雨淋、陽(yáng)光直射、水霧以及動(dòng)物摩擦等)。

      在植入式測(cè)溫中,由于需將設(shè)備植入動(dòng)物體內(nèi),一般需要給動(dòng)物做外科手術(shù)將設(shè)備植入,易造成動(dòng)物不適影響動(dòng)物健康及生產(chǎn)。通過(guò)口服丸以及注射等方式,可極大的減少動(dòng)物的不適,是植入式測(cè)溫中較為溫和的植入方式。同時(shí),選擇合適的植入位置也是植入式測(cè)溫應(yīng)用的難點(diǎn),需確定所植入位置與核心體溫之間的關(guān)系,并保證體內(nèi)測(cè)量精度。如何避免上述因素,是該方法進(jìn)一步改進(jìn)的重點(diǎn)。

      非接觸式測(cè)溫主要以紅外熱成像技術(shù)為主,以其高效、方便、無(wú)應(yīng)激、可進(jìn)行群體體溫自動(dòng)巡檢等的優(yōu)勢(shì)倍受青睞。然而,紅外熱像測(cè)溫方法,易受環(huán)境溫濕度、光照、測(cè)溫距離等影響,造成測(cè)量數(shù)據(jù)與實(shí)際體溫存在一定的差異。因此,應(yīng)建立多種環(huán)境條件下,針對(duì)不同種類(lèi)動(dòng)物體表溫度與直腸溫度的普適性的溫度補(bǔ)償模型。基于紅外熱像技術(shù)構(gòu)建的溫度巡檢系統(tǒng)中,由于熱像數(shù)據(jù)較大為實(shí)時(shí)數(shù)據(jù)傳輸帶來(lái)一定的困難,需要研發(fā)適合于熱像數(shù)據(jù)遠(yuǎn)程傳輸?shù)奈锫?lián)網(wǎng)系統(tǒng),實(shí)現(xiàn)數(shù)據(jù)高效、快速、實(shí)時(shí)傳輸。

      總之,無(wú)論上述哪種自動(dòng)化測(cè)溫技術(shù),都需要做到盡量減少動(dòng)物應(yīng)激反應(yīng),開(kāi)展無(wú)創(chuàng)式體溫監(jiān)測(cè);建立關(guān)鍵測(cè)溫部位的溫度與動(dòng)物核心溫度之間的關(guān)系,準(zhǔn)確反映真實(shí)體溫變化情況;結(jié)合動(dòng)物體溫變化反映出來(lái)的環(huán)境適應(yīng)性,進(jìn)行畜舍環(huán)境舒適性的智能反饋調(diào)控;將自動(dòng)體溫監(jiān)測(cè)技術(shù)作為動(dòng)物群體健康及疾病檢測(cè)重要依據(jù),綜合其他指標(biāo)綜合判定健康狀況,為健康檢測(cè)及疾病診斷提供重要技術(shù)支撐。在未來(lái)畜禽自動(dòng)測(cè)溫技術(shù)的發(fā)展應(yīng)用中,隨著物聯(lián)網(wǎng)、人工智能等新興信息技術(shù)的不斷發(fā)展成熟,研發(fā)低成本、高精準(zhǔn)、實(shí)時(shí)的非接觸式自動(dòng)測(cè)溫技術(shù)及設(shè)備,具有廣闊的發(fā)展前景和應(yīng)用價(jià)值。

      8 結(jié) 論

      本文通過(guò)對(duì)畜禽體溫自動(dòng)監(jiān)測(cè)技術(shù)的應(yīng)用現(xiàn)狀以及未來(lái)發(fā)展趨勢(shì)進(jìn)行深入分析,闡述了體溫自動(dòng)監(jiān)測(cè)技術(shù)在畜禽養(yǎng)殖中的意義,并提出了未來(lái)畜禽體溫自動(dòng)監(jiān)測(cè)發(fā)展方向與前景。傳統(tǒng)的手工測(cè)溫方法已逐漸被新興的自動(dòng)測(cè)溫方法取代。自動(dòng)測(cè)溫技術(shù)以實(shí)時(shí)、高效、方便、準(zhǔn)確的優(yōu)勢(shì),在畜禽健康養(yǎng)殖生產(chǎn)及管理中已表現(xiàn)出強(qiáng)大的優(yōu)勢(shì)和發(fā)展空間,目前廣泛應(yīng)用于動(dòng)物生產(chǎn)性能、疾病檢測(cè)、行為監(jiān)測(cè)等方面。其中,非接觸式紅外測(cè)溫技術(shù)優(yōu)勢(shì)特點(diǎn)更為明顯,結(jié)合紅外圖像處理技術(shù)的紅外熱像儀測(cè)溫方式逐漸成為當(dāng)下畜禽體溫監(jiān)測(cè)研究熱點(diǎn)。然而,紅外圖像普遍存在成像噪聲大、圖像對(duì)比度低等問(wèn)題。因此,紅外圖像處理關(guān)鍵技術(shù)的提升將進(jìn)一步推動(dòng)紅外熱成像測(cè)溫技術(shù)在畜禽體溫自動(dòng)監(jiān)測(cè)中的應(yīng)用。

      在自動(dòng)化的體溫監(jiān)測(cè)技術(shù)中,降低成本、提高數(shù)據(jù)傳輸穩(wěn)定性和測(cè)溫精度,開(kāi)發(fā)便攜式、易操作的測(cè)溫設(shè)備,是實(shí)現(xiàn)規(guī)?;笄轀y(cè)溫的關(guān)鍵。在未來(lái),結(jié)合物聯(lián)網(wǎng)、人工智能等新興技術(shù)實(shí)現(xiàn)體溫自動(dòng)巡檢,構(gòu)建更高效的健康檢測(cè)模式、流程及智能化設(shè)備,將具有廣闊的發(fā)展前景。

      [1] Giro A, De Campos Bernardi A C, Junior W B, et al. Application of microchip and infrared thermography for monitoring body temperature of beef cattle kept on pasture[J]. Journal of Thermal Biology, 2019, 84: 121-128.

      [2] Bao J, Xie Q. Artificial intelligence in animal farming: A systematic literature review [J]. Journal of Cleaner Production, 2022, 331: 129956.

      [3] Bligh J, Heal J. The use of radio-telemetry in the study of animal physiology [J]. Proceedings of the Nutrition Society, 1974, 33(2): 173-181.

      [4] Hetzel D, Bennett I, Holmes C, et al. Description and evaluation of a telemetry system for measuring body temperature in cattle [J]. The Journal of Agricultural Science, 1988, 110(2): 233-238.

      [5] 劉暢. 奶牛體溫植入式傳感器及實(shí)時(shí)檢測(cè)系統(tǒng)研究[D].楊凌:西北農(nóng)林科技大學(xué),2019.

      Liu Chang. Research on Implantable Body Temperature Sensor and Real-Time Detection System of Dairy Cows[D]. Yangling:Northwest A&F University, 2019. (in Chinese with English abstract)

      [6] 何東健,劉暢,熊虹婷. 奶牛體溫植入式傳感器與實(shí)時(shí)監(jiān)測(cè)系統(tǒng)設(shè)計(jì)與試驗(yàn)[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2018,49(12):195-202.

      He Dongjian, Liu Chang, Xiong Hongting. Design and experiment of implantable sensor and real-time detection system for temperature monitoring of cow[J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(12): 195-202. (in Chinese with English abstract)

      [7] Suthar V, Burfeind O, Patel J, et al. Body temperature around induced estrus in dairy cows[J]. Journal of Dairy Science, 2011, 94(5): 2368-2373.

      [8] Kyle B, Kennedy A, Small J. Measurement of vaginal temperature by radiotelemetry for the prediction of estrus in beef cows[J]. Theriogenology, 1998, 49(8): 1437-1449.

      [9] Morais R, Valente A, Almeida J C, et al. Concept study of an implantable microsystem for electrical resistance and temperature measurements in dairy cows, suitable for estrus detection[J]. Sensors and Actuators A: Physical, 2006, 132(1): 354-361.

      [10] Miranda N, Morais R, Dias M, et al. Bioimplantable impedance and temperature monitor low power micro-system suitable for estrus detection[J]. Procedia Chemistry, 2009, 1(1): 505-508.

      [11] Lee Y, Bok J, Lee H, et al. Body temperature monitoring using subcutaneously implanted thermo-loggers from holstein steers[J]. Asian-Australasian Journal of Animal Sciences, 2016, 29(2): 299-306.

      [12] Chung H, Li J, Kim Y, et al. Continuous and wireless skin contact and ear implant temperature measurements and relations to the core body temperature of heat stressed dairy cows[C]//10th International Livestock Environment Symposium (ILES X). American Society of Agricultural and Biological Engineers, Nebraska, 2018: 1.

      [13] 張子云. 新型電子芯片檢測(cè)不同品種后備母豬發(fā)情期體溫變化及行為表現(xiàn)規(guī)律研究[D]. 成都:四川農(nóng)業(yè)大學(xué),2015.

      Zhang Ziyun. A New Type of Electronic Chip to Detect Changes in Body Temperature and Behavioral Behavior of Different Breeds of Gilts During Estrus[D]. Chengdu: Sichuan Agricultural University, 2015. (in Chinese with English abstract)

      [14] Lohse L, Uttenthal ?, En?e C, et al. A study on the applicability of implantable microchip transponders for body temperature measurements in pigs[J]. Acta Veterinaria Scandinavica, 2010, 52(1): 1-9.

      [15] Iyasere O S, Edwards S A, Bateson M, et al. Validation of an intramuscularly-implanted microchip and a surface infrared thermometer to estimate core body temperature in broiler chickens exposed to heat stress[J]. Computers and Electronics in Agriculture, 2017, 133: 1-8.

      [16] Rey B, Fuller A, Hetem R S, et al. Microchip transponder thermometry for monitoring core body temperature of antelope during capture[J]. Journal of Thermal Biology, 2016, 55: 47-53.

      [17] Kearton T R, Doughty A K, Morton C L, et al. Core and peripheral site measurement of body temperature in short wool sheep[J]. Journal of Thermal Biology, 2020, 90:102606.

      [18] Grewar J D. Use of Temperature Sensitive Microchip Transponders to Monitor Body Temperature and Pyrexia in Thoroughbred Foals[D]. Pretoria: University of Pretoria, 2010.

      [19] Auclair-Ronzaud J,Benoist S,Dubois C,et al. No-contact microchip monitoring of body temperature in yearling horses[J]. Journal of Equine Veterinary Science, 2020, 86:102892.

      [20] Chung H, Li J, Kim Y, et al. Using implantable biosensors and wearable scanners to monitor dairy cattle's core body temperature in real-time[J]. Computers and Electronics in Agriculture, 2020, 174: 105453.

      [21] 張國(guó)鋒,陶莎,于麗娜,等. 基于植入式RFID感溫芯片的豬體溫與飲水監(jiān)測(cè)系統(tǒng)[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2019,50(S1):297-304.

      Zhang Guofeng, Tao Sha, Yu Lina, et al. Pig body temperature and drinking water monitoring system based on implantable rfid temperature chip[J]. Transactions of the Chinese Society for Agricultural Machinery, 2019, 50(S1): 297-304. (in Chinese with English abstract)

      [22] Reid E. The Use of Implantable Microchips for Body Temperature Collection in Cattle[D]. Urbana-Champaign: University of Illinois at Urbana-Champaign, 2015.

      [23] Small J, Kennedy A, Kahane S. Core body temperature monitoring with passive transponder boluses in beef heifers[J]. Canadian Journal of Animal Science, 2008, 88(2): 225-235.

      [24] Maxwell B M, Brunell M K, Olsen C H, et al. Comparison of digital rectal and microchip transponder thermometry in ferrets ()[J]. Journal of the American Association for Laboratory Animal Science, 2016, 55(3): 331-335.

      [25] Iwasaki W, Ishida S, Kondo D, et al. Monitoring of the core body temperature of cows using implantable wireless thermometers[J]. Computers and Electronics in Agriculture, 2019, 163: 104849.

      [26] 郭子平. 基于無(wú)線能量傳輸技術(shù)的植入式動(dòng)物生理參數(shù)遙測(cè)系統(tǒng)研究[D]. 上海:上海交通大學(xué),2012.

      Guo Ziping. Research on Implantable Animal Physiological Parameter Telemetry System Based on Wireless Energy Transmission Technology[D]. Shanghai: Shanghai Jiaotong University, 2012. (in Chinese with English abstract)

      [27] Alzahal O, Steele M, Valdes E, et al. The use of a telemetric system to continuously monitor ruminal temperature and to predict ruminal pH in cattle[J]. Journal of Dairy Science, 2009, 92(11): 5697-5701.

      [28] Alzahal O, Alzahal H, Steele M, et al. The use of a radiotelemetric ruminal bolus to detect body temperature changes in lactating dairy cattle[J]. Journal of Dairy Science, 2011, 94(7): 3568-3574.

      [29] Kim H, Min Y, Choi B. Real-time temperature monitoring for the early detection of mastitis in dairy cattle: Methods and case researches[J]. Computers and Electronics in Agriculture, 2019, 162: 119-125.

      [30] Timsit E, Assié S, Quiniou R, et al. Early detection of bovine respiratory disease in young bulls using reticulo-rumen temperature boluses[J]. The Veterinary Journal, 2011, 190(1): 136-142.

      [31] Wiersma F, Stott G H. A technique for securing a temperature probe adjacent to the tympanic membrane in bovine[J]. Transactions of the ASAE, 1983, 26(1): 185-0187.

      [32] 楊威. 蛋雞穿戴式無(wú)線體溫感知設(shè)備的開(kāi)發(fā)及體溫監(jiān)測(cè)實(shí)驗(yàn)研究[D]. 杭州:浙江大學(xué),2017.

      Yang Wei. Development of a Wearable Wireless Body Temperature Sensing Device for Laying Hens and Experimental Research on Body Temperature Monitoring[D]. Hangzhou: Zhejiang University, 2017. (in Chinese with English abstract)

      [33] 武彥,劉子帆,何東健,等. 奶牛體溫實(shí)時(shí)遠(yuǎn)程監(jiān)測(cè)系統(tǒng)設(shè)計(jì)與實(shí)現(xiàn)[J]. 農(nóng)機(jī)化研究, 2012,34(6):148-152.

      Wu Yan, Liu Zifan, He Dongjian, et al. Design and implementation of real-time remote monitoring system for cow body temperature[J]. Journal of Agricultural Mechanization Research, 2012, 34(6): 148-152. (in Chinese with English abstract)

      [34] Okada H, Itoh T, Suzuki K, et al. Wireless sensor system for detection of avian influenza outbreak farms at an early stage[C]//Sensors, 2009 IEEE. IEEE, 2009: 1374-1377.

      [35] 盛顯超. 基于WiFi和云平臺(tái)的生豬體溫監(jiān)測(cè)系統(tǒng)設(shè)計(jì) [D]. 哈爾濱:哈爾濱理工大學(xué),2019.

      Sheng Xianchao. Design of Pig Body Temperature Monitoring System Based on Wifi and Cloud Platform[D]. Harbin: Harbin University of Science and Technology, 2019. (in Chinese with English abstract)

      [36] 劉忠超,范偉強(qiáng),張會(huì)娟,等. 基于Android的奶牛體溫實(shí)時(shí)遠(yuǎn)程監(jiān)測(cè)系統(tǒng)的設(shè)計(jì)[J]. 黑龍江畜牧獸醫(yī),2017(23):6-9,282-283.

      Liu Zhongchao, Fan Weiqiang, Zhang Huijuan, et al. Design of a real-time remote monitoring system for dairy cow body temperature based on Android[J]. Heilongjiang Animal Science and Veterinary Medicine, 2017(23): 6-9, 282-283. (in Chinese with English abstract)

      [37] 王俠. 奶牛體溫預(yù)測(cè)檢測(cè)平臺(tái)設(shè)計(jì)與實(shí)現(xiàn)[D].合肥:安徽農(nóng)業(yè)大學(xué), 2020.

      Wang Xia. Design and Implementation of Dairy Cow Body Temperature Prediction and Detection Platform[D]. Hefei: Anhui Agricultural University, 2020. (in Chinese with English abstract)

      [38] 屈東東. 群養(yǎng)奶牛體溫實(shí)時(shí)監(jiān)測(cè)系統(tǒng)設(shè)計(jì)與實(shí)現(xiàn)[D]. 合肥:安徽農(nóng)業(yè)大學(xué),2017.

      Qu Dongdong. Design and Implementation of Real-Time Monitoring System for Body Temperature of Group Dairy Cows[D]. Hefei: Anhui Agricultural University, 2017. (in Chinese with English abstract)

      [39] 楊宇闐奕,何東健,劉暢,等. 基于ZigBee的奶牛體征監(jiān)測(cè)系統(tǒng)設(shè)計(jì)與實(shí)現(xiàn)[J]. 農(nóng)機(jī)化研究,2018,40(9):74-80.

      Yang Yutianyi, He Dongjian, Liu Chang, et al. Design and implementation of ZigBee-based cow sign monitoring system[J]. Journal of Agricultural Mechanization Research, 2018, 40(9): 74-80. (in Chinese with English abstract)

      [40] 李麗華. 蛋雞體溫與生產(chǎn)性能參數(shù)動(dòng)態(tài)監(jiān)測(cè)關(guān)鍵技術(shù)研究及應(yīng)用[D]. 保定:河北農(nóng)業(yè)大學(xué),2014.

      Li Lihua. Research and Application of Key Technologies for Dynamic Monitoring of Body Temperature and Production Performance Parameters of Laying Hens[D]. Baoding: Hebei Agricultural University, 2014. (in Chinese with English abstract)

      [41] 寇紅祥. 奶牛體溫與活動(dòng)量自動(dòng)檢測(cè)系統(tǒng)設(shè)計(jì)研發(fā)及發(fā)情周期規(guī)律研究 [D]. 長(zhǎng)春:吉林農(nóng)業(yè)大學(xué),2017.

      Kou Hongxiang. Design and Development of Automatic Detection System for Body Temperature and Activity of Dairy Cows and Research on The Regularity of Estrus Cycle[D]. Changchun: Jilin Agricultural University, 2017. (in Chinese with English abstract)

      [42] 蔡勇,趙福平,陳新,等. 牛體表溫度測(cè)定及其與體內(nèi)溫度校正公式研究[J]. 畜牧獸醫(yī)學(xué)報(bào),2015,46(12):2199-2205.

      Cai Yong, Zhao Fuping, Chen Xin, et al. Study on the measurement of bovine body surface temperature and its correction formula with internal temperature[J]. Journal of Animal Husbandry and Veterinary Medicine, 2015, 46(12): 2199-2205. (in Chinese with English abstract)

      [43] Wang S, Zhang H, Tian H, et al. Alterations in vaginal temperature during the estrous cycle in dairy cows detected by a new intravaginal device: A pilot study[J]. Tropical Animal Health and Production, 2020, 52(5): 2265-2271.

      [44] 尹祥宇,王艷君,白杰,等. 基于Tsic506和Zigbee的蛋雞體溫?zé)o線監(jiān)測(cè)系統(tǒng)設(shè)計(jì)[J]. 中國(guó)農(nóng)機(jī)化學(xué)報(bào),2014,35(2):281-285.

      Yin Xiangyu, Wang Yanjun, Bai Jie, et al. Design of wireless temperature monitoring system for laying hens based on Tsic506 and Zigbee[J]. Journal of Chinese Agricultural Mechanization, 2014, 35(2): 281-285. (in Chinese with English abstract)

      [45] Okada H, Nogami H, Itoh T, et al. Development of low power technologies for health monitoring system using wireless sensor nodes[C]//2012 Second Workshop on Design, Control and Software Implementation for Distributed MEMS. IEEE, 2012: 90-95.

      [46] Koyama K,Koyama T,Sugimoto M,et al. Prediction of calving time in Holstein dairy cows by monitoring the ventral tail base surface temperature[J]. The Veterinary Journal, 2018, 240: 1-5.

      [47] Andersen H ML, J?rgensen E, Dybkj?r L, et al. The ear skin temperature as an indicator of the thermal comfort of pigs[J]. Applied Animal Behaviour Science, 2008, 113(1/2/3): 43-56.

      [48] 尹令,劉財(cái)興,洪添勝,等. 基于無(wú)線傳感器網(wǎng)絡(luò)的奶牛行為特征監(jiān)測(cè)系統(tǒng)設(shè)計(jì)[J]. 農(nóng)業(yè)工程學(xué)報(bào),2010,26(3):203-208,388.

      Yin Ling, Liu Caixing, Hong Tiansheng, et al. Design of system for monitoring dairy cattle’s behavioral features based on wireless sensor networks[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(3): 203-208, 388. (in Chinese with English abstract)

      [49] Kou H, Zhao Y, Ren K, et al. Automated measurement of cattle surface temperature and its correlation with rectal temperature[J]. PloS One, 2017, 12(4): e0175377.

      [50] 柏廣宇,劉龍申,沈明霞,等. 基于無(wú)線傳感器網(wǎng)絡(luò)的母豬體溫實(shí)時(shí)監(jiān)測(cè)節(jié)點(diǎn)研制[J]. 南京農(nóng)業(yè)大學(xué)學(xué)報(bào),2014,37(5):128-134.

      Bai Guangyu, Liu Longshen, Shen Mingxia, et al. Design of sow body temperature monitoring node based on wireless sensor network[J]. Journal of Nanjing Agricultural University, 2014, 37(5): 128-134. (in Chinese with English abstract)

      [51] 范永存,張喜海,李建澤. 奶牛體溫監(jiān)測(cè)系統(tǒng)數(shù)據(jù)采集終端設(shè)計(jì)[J]. 東北農(nóng)業(yè)大學(xué)學(xué)報(bào),2012,43(8):48-52.

      Fan Yongcun, Zhang Xihai, Li Jianze. Design of data acquisition terminal for dairy cow body temperature monitoring system[J]. Journal of Northeast Agricultural University, 2012, 43(8): 48-52. (in Chinese with English abstract)

      [52] 秦永孝,喬宇飛,張勤,等. 基于紅外測(cè)溫設(shè)備的豬體溫采集系統(tǒng)研究[C]//中國(guó)畜牧獸醫(yī)學(xué)會(huì)信息技術(shù)分會(huì)第十屆學(xué)術(shù)研討會(huì)論文集,北京:中國(guó)農(nóng)業(yè)大學(xué)出版社,2015:87-89.

      Qin Yongxiao, Qiao Yufei, Zhang Qin, et al. Research on pig body temperature acquisition system based on infrared temperature measurement equipment[C]//Proceedings of the 10th Academic Symposium of Information Technology Branch of China Animal Husbandry and Veterinary Society, Beijing: China Agricultural University Press, 2015: 87-89. (in Chinese with English abstract)

      [53] Fiebig K, Jourdan T, Kock M H, et al. Evaluation of infrared thermography for temperature measurement in adult male NMRI nude mice[J]. Journal of the American Association for Laboratory Animal Science, 2018, 57(6): 715-724.

      [54] 肖德琴,林思聰,劉勤,等. 基于紅外熱成像的生豬耳溫自動(dòng)提取算法[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2021,52(8):255-262.

      Xiao Deqin, Lin Sicong, Liu Qin, et al. Automatic ear temperature extraction algorithm for live pigs based on infrared thermography[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(8): 255-262. (in Chinese with English abstract)

      [55] 孟珍琪. 基于紅外技術(shù)的生豬體溫自動(dòng)檢測(cè)的研究[D]. 天津:天津農(nóng)學(xué)院,2018.

      Meng Zhenqi. Research on Automatic Detection of Pig Body Temperature Based on Infrared Technology[D]. Tianjin: Tianjin Agricultural College, 2018. (in Chinese with English abstract)

      [56] 張澤峰. 母豬體溫紅外監(jiān)測(cè)系統(tǒng)設(shè)計(jì)與實(shí)現(xiàn)[D]. 太原:山西農(nóng)業(yè)大學(xué),2019.

      Zhang Zefeng. Design and Implementation of Infrared Monitoring System for Sow Body Temperature[D]. Taiyuan: Shanxi Agricultural University, 2019. (in Chinese with English abstract)

      [57] 劉勤. 基于熱紅外圖像的生豬體溫巡檢技術(shù)研究[D]. 廣州:華南農(nóng)業(yè)大學(xué),2019.

      Liu Qin. Research on Pig Body Temperature Inspection Technology Based on Thermal Infrared Images[D]. Guangzhou: South China Agricultural University, 2019. (in Chinese with English abstract)

      [58] Xie Q, Wu M, Yang M, et al. A deep learning-based fusion method of infrared thermography and visible image for pig body temperature detection[C]//Animal Enivironment And Welfare-Procedings of International Symposium, 2021: 326-333.

      [59] 張?jiān)谇? 基于紅外圖像的種豬體溫檢測(cè)方法研究[D]. 天津:天津農(nóng)學(xué)院,2019.

      Zhang Zaiqin. Research on Body Temperature Detection Method of Breeding Pigs Based on Infrared Images[D]. Tianjin: Tianjin Agricultural College, 2019. (in Chinese with English abstract)

      [60] Moghbeli Damane M, Barazandeh A, Sattaei Mokhtari M, et al. Evaluation of body surface temperature in broiler chickens during the rearing period based on age, air temperature and feather condition[J]. Iranian Journal of Applied Animal Science, 2018, 8(3): 499-504.

      [61] 范睿. 基于安卓平臺(tái)的肉雞體溫非接觸式監(jiān)測(cè)系統(tǒng)設(shè)計(jì)[D]. 南京:南京農(nóng)業(yè)大學(xué),2018.

      Fan Rui. Design of Non-Contact Monitoring System for Broiler Body Temperature Based on Android Platform[D]. Nanjing: Nanjing Agricultural University, 2018. (in Chinese with English abstract)

      [62] Xiong X, Lu M, Yang W, et al. An automatic head surface temperature extraction method for top-view thermal image with individual broiler[J]. Sensors, 2019, 19(23): 5286.

      [63] Barchilon N, Bloch V, Meir D, et al. Automatic broiler temperature measuring by IR camera for commercial broiler-houses[C]//The 9th European conference on precision livestock farming (ECPLF), Cork, 2019: 885-889.

      [64] Wang F K, Shih J Y, Juan P H, et al. Non-Invasive cattle body temperature measurement using infrared thermography and auxiliary sensors[J]. Sensors, 2021, 21(7): 2425.

      [65] 劉國(guó)強(qiáng). 基于紅外圖像奶牛發(fā)情信息監(jiān)測(cè)裝置的研究[D]. 呼和浩特:內(nèi)蒙古農(nóng)業(yè)大學(xué),2021.

      Liu Guoqiang. Research on Monitoring Device for Cow Estrus Information Based on Infrared Images[D]. Huhhot: Inner Mongolia Agricultural University, 2021. (in Chinese with English abstract)

      [66] Zhang Z, Zhang H, Liu T. Study on body temperature detection of pig based on infrared technology: A review[J]. Artificial Intelligence in Agriculture, 2019, 1: 14-26.

      [67] 何東健,宋子琪. 基于熱紅外成像與骨架樹(shù)模型的奶牛眼溫自動(dòng)檢測(cè)[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2021,52(3):243-250.

      He Dongjian, Song Ziqi. Automatic detection of dairy cow’s eye temperature based on thermal infrared imaging technology and skeleton tree model[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(3): 243-250. (in Chinese with English abstract)

      [68] 蔡勇. 牛體表溫度自動(dòng)采集系統(tǒng)研發(fā)及其與體內(nèi)溫度擬合曲線的研究[D]. 北京:中國(guó)農(nóng)業(yè)科學(xué)院,2015.

      Cai Yong. Development of an Automatic Acquisition System for Bovine Body Surface Temperature and Its Fitting Curve With in Vivo Temperature[D]. Beijing: Chinese Academy of Agricultural Sciences, 2015. (in Chinese with English abstract)

      [69] 陳莉,錢(qián)同惠,張仕臻,等. 基于無(wú)線傳感器網(wǎng)絡(luò)的生豬體征和養(yǎng)殖環(huán)境監(jiān)測(cè)系統(tǒng)設(shè)計(jì)[J]. 自動(dòng)化技術(shù)與應(yīng)用,2017,36(5):61-64.

      Chen Li, Qian Tonghui, Zhang Shizhen, et al. Design of pig signs and breeding environment monitoring system based on wireless sensor network[J]. Techniques of Automation and Applications, 2017, 36(5): 61-64. (in Chinese with English abstract)

      [70] 曹春梅,賈海,閆貴龍. 紅外線體溫計(jì)測(cè)量成年雞體溫部位優(yōu)選[J]. 黑龍江畜牧獸醫(yī),2021(14):50-53.

      Cao Chunmei, Jia Hai, Yan Guilong. Optimization of the location of infrared thermometer for measuring body temperature of adult chickens[J]. Heilongjiang Animal Science and Veterinary Medicine, 2021(14): 50-53. (in Chinese with English abstract)

      [71] 何金成,張鮮,李素青,等. 環(huán)境溫濕度及測(cè)量部位對(duì)奶牛紅外熱成像溫度的影響[J]. 浙江大學(xué)學(xué)報(bào)(農(nóng)業(yè)與生命科學(xué)版),2020,46(4):500-508.

      He Jincheng, Zhang Xian, Li Suqing, et al. Effects of ambient temperature and relative humidity and measurement site on the cow's body temperature measured by infrared thermography[J]. Journal of Zhejiang University (Agriculture and Life Sciences), 2020, 46(4): 500-508. (in Chinese with English abstract)

      [72] Salles M S V, Da Silva S C, Salles F A, et al. Mapping the body surface temperature of cattle by infrared thermography[J]. Journal of Thermal Biology, 2016, 62: 63-69.

      [73] 陳健,顧憲紅,李淦,等. 不同溫濕指數(shù)環(huán)境下奶牛陰道溫度的變化規(guī)律[J]. 中國(guó)畜牧雜志,2019,55(5):112-117.

      Chen Jian, Gu Xianhong, Li Gan, et al. Variation of vaginal temperature under different temperature-humidity index in dairy cows[J]. Chinese Journal of Animal Science, 2019, 55(5): 112-117. (in Chinese with English abstract)

      [74] 楊語(yǔ)嫣,李耀文,邢爽,等. 基于體表溫度的肉雞溫濕指數(shù)模型研究[J]. 中國(guó)農(nóng)業(yè)科學(xué),2021,54(6):1270-1279.

      Yang Yuyan, Li Yaowen, Xing Shuang, et al. Research on temperature and humidity index model of broilers based on body surface temperature[J]. Scientia Agricultura Sinica, 2021, 54(6): 1270-1279. (in Chinese with English abstract)

      [75] 賈桂鋒,武墩,蒙俊宇,等. 測(cè)量距離對(duì)生豬紅外熱成像測(cè)溫的影響及校正[J]. 傳感器與微系統(tǒng),2019,38(11):62-64,68.

      Jia Guifeng, Wu Dun, Meng Junyu, et al. Influence and correction of measuring distance on pig's IRT temperature measurement[J]. Transducer and Microsystem Technologies, 2019, 38(11): 62-64, 68. (in Chinese with English abstract)

      [76] Soerensen D D, Clausen S, Mercer J B, et al. Determining the emissivity of pig skin for accurate infrared thermography[J]. Computers and Electronics in Agriculture, 2014, 109: 52-58.

      [77] 賈桂鋒,蒙俊宇,武墩,等. 被毛對(duì)熱成像檢測(cè)生豬體表溫度精度的影響及噪聲濾除方法[J]. 農(nóng)業(yè)工程學(xué)報(bào),2019,35(4):162-167.

      Jia Guifeng, Meng Junyu, Wu Dun, et al. Effect of hair on thermometry of skin by infrared thermography and noise reduction method for live pigs[J]. Chinese Journal of Agricultural Engineering (Transactions of the CSAE), 2019, 35(4): 162-167. (in Chinese with English abstract)

      [78] Jiao L, Dong D, Zhao X, et al. Compensation method for the influence of angle of view on animal temperature measurement using thermal imaging camera combined with depth image[J]. Journal of Thermal Biology, 2016, 62: 15-19.

      [79] Kammersgaard T, Malmkvist J, Pedersen L. Infrared thermography: A non-invasive tool to evaluate thermal status of neonatal pigs based on surface temperature[J]. Animal, 2013, 7(12): 2026-2034.

      [80] Talukder S, Kerrisk K, Ingenhoff L, et al. Infrared technology for estrus detection and as a predictor of time of ovulation in dairy cows in a pasture-based system[J]. Theriogenology, 2014, 81(7): 925-935.

      [81] Byrne D T, Berry D P, Esmonde H, et al. Investigation of the relationship between udder quarter somatic cell count and udder skin surface temperature of dairy cows measured by infrared thermography[J]. Journal of Animal Science, 2018, 96(10): 4458-4470.

      [82] Akter S, Cheng B, West D, et al. Impacts of air velocity treatments under summer condition: Part I—heavy broiler’s surface temperature response[J]. Animals, 2022, 12(3): 328.

      [83] Yuan H, Liu C, Wang H, et al. Optimization and comparison of models for core temperature prediction of mother rabbits using infrared thermography[J]. Infrared Physics & Technology, 2022, 120: 103987.

      [84] De Sousa R V, Da Silva Rodrigues A V, De Abreu M G, et al. Predictive model based on artificial neural network for assessing beef cattle thermal stress using weather and physiological variables [J]. Computers and Electronics in Agriculture, 2018, 144: 37-43.

      [85] Basak J K, Arulmozhi E, Khan F, et al. Assessment of the influence of environmental variables on pig's body temperature using ann and mlr models [J]. Indian Journal of Animal Research, 2020, 54(9): 1165-1170.

      [86] 沈明霞,陸鵬宇,劉龍申,等. 基于紅外熱成像的白羽肉雞體溫檢測(cè)方法[J]. 農(nóng)業(yè)機(jī)械學(xué)報(bào),2019,50(10):222-229.

      Shen Mingxia, Lu Pengyu, Liu Longshen, et al. Body temperature detection method of ross broiler based on infrared thermography[J]. Transactions of the Chinese Society for Agricultural Machinery, 2019, 50(10): 222-229. (in Chinese with English abstract)

      [87] Lins A C, Louren?oni D, Yanagi Júnior T, et al. Neuro-fuzzy modeling of eyeball and crest temperatures in egg-laying hens[J]. Engenharia Agrícola, 2021, 41: 34-38.

      [88] Mayo L, Silvia W, Ray D, et al. Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows[J]. Journal of Dairy Science, 2019, 102(3): 2645-2656.

      [89] Redden K, Kennedy A, Ingalls J, et al. Detection of estrus by radiotelemetric monitoring of vaginal and ear skin temperature and pedometer measurements of activity[J]. Journal of Dairy Science, 1993, 76(3): 713-721.

      [90] Bohmanova J, Misztal I, Cole J. Temperature-humidity indices as indicators of milk production losses due to heat stress[J]. Journal of Dairy Science, 2007, 90(4): 1947-1956.

      [91] 嚴(yán)格齊,李浩,施正香,等. 奶牛熱應(yīng)激指數(shù)的研究現(xiàn)狀及問(wèn)題分析[J]. 農(nóng)業(yè)工程學(xué)報(bào),2019,35(23):226-233.

      Yan Geqi, Li Hao, Shi Zhengxiang, et al. Research status and existing problems in establishing cow heat stress indices[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(23): 226-233. (in Chinese with English abstract)

      [92] 張鮮. 基于紅外熱成像技術(shù)的奶牛熱應(yīng)激診斷方法的研究[D]. 福州:福建農(nóng)林大學(xué),2016.

      Zhang Xian. Research on The Diagnosis Method of Heat Stress in Dairy Cows Based on Infrared Thermal Imaging Technology[D]. Fuzhou: Fujian Agriculture and Forestry University, 2016. (in Chinese with English abstract)

      [93] Jorquera-Chavez M, Fuentes S, Dunshea F R, et al. Remotely sensed imagery for early detection of respiratory disease in pigs: A pilot study[J]. Animals, 2020, 10(3): 451.

      [94] Jorquera C M, Fuentes S, Dunshea F R, et al. Using imagery and computer vision as remote monitoring methods for early detection of respiratory disease in pigs[J]. Computers and Electronics in Agriculture, 2021, 187: 106283.

      [95] Schaefer A, Cook N, Bench C, et al. The non-invasive and automated detection of bovine respiratory disease onset in receiver calves using infrared thermography[J]. Research in Veterinary Science, 2012, 93(2): 928-935.

      [96] Adams A, Olea-Popelka F, Roman-Muniz I. Using temperature-sensing reticular boluses to aid in the detection of production diseases in dairy cows[J]. Journal of Dairy Science, 2013, 96(3): 1549-1555.

      [97] Xudong Z, Xi K, Ningning F, et al. Automatic recognition of dairy cow mastitis from thermal images by a deep learning detector[J]. Computers and Electronics in Agriculture, 2020, 178: 105754.

      [98] Berry R, Kennedy A, Scott S, et al. Daily variation in the udder surface temperature of dairy cows measured by infrared thermography: Potential for mastitis detection[J]. Canadian Journal of Animal Science, 2003, 83(4): 687-693.

      [99] 郭艷嬌,楊圣慧,遲宇,等. 基于熱紅外圖像的奶牛乳區(qū)溫度分布與乳房炎識(shí)別方法[J]. 農(nóng)業(yè)工程學(xué)報(bào),2022,38(2):250-259.

      Guo Yanjiao, Yang Shenghui, Chi Yu, et al. Recognizing mastitis using temperature distribution from thermal infrared images in cow udder regions[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(2): 250-259. (in Chinese with English abstract)

      [100] 宋子琪. 基于熱紅外圖像的奶牛乳房炎檢測(cè)方法研究[D]. 楊凌:西北農(nóng)林科技大學(xué),2021.

      Song Ziqi. Research On Detection Method of Dairy Cow Mastitis Based on Thermal Infrared Images[D]. Yangling: Northwest A&F University, 2021. (in Chinese with English abstract)

      [101] 周麗萍. 生豬發(fā)熱及藍(lán)耳疫情檢測(cè)方法與巡檢消毒裝備研究[D]. 北京:中國(guó)農(nóng)業(yè)機(jī)械化科學(xué)研究院,2016.

      Zhou Liping. Research on Detection Methods and Inspection and Disinfection Equipment for Fever and PRRS in Pigs[D]. Beijing: China Academy of Agricultural Mechanization, 2016. (in Chinese with English abstract)

      [102] Oh S I, Lee H S, Bui V N, et al. Dynamic variations in infrared skin temperature of weaned pigs experimentally inoculated with the african swine fever virus: A pilot study[J]. Veterinary Sciences, 2021, 8(10): 223-231.

      [103] Lokeshbabu D, Jeyakumar S, Vasant P J, et al. Monitoring foot surface temperature using infrared thermal imaging for assessment of hoof health status in cattle: A review[J]. Journal of Thermal Biology, 2018, 78: 10-21.

      [104] 許志強(qiáng),沈明霞,劉龍申,等. 基于紅外熱圖像的肉雞腿部異常檢測(cè)方法[J]. 南京農(nóng)業(yè)大學(xué)學(xué)報(bào),2021,44(2):384-393.

      Xu Zhiqiang, Shen Mingxia, Liu Longshen, et al. Abnormal recognition method of broiler leg based on infrared thermal image[J]. Journal of Nanjing Agricultural University, 2021, 44(2): 384-393. (in Chinese with English abstract)

      [105] Swiergiel A H. Modifications of operant thermoregulatory behavior of the young pig by environmental temperature and food availability[J]. Physiology & Behavior, 1997, 63(1): 119-125.

      [106] Kim Y J, Song M H, Lee S I, et al. Evaluation of pig behavior changes related to temperature, relative humidity, volatile organic compounds, and illuminance[J]. Journal of Animal Science and Technology, 2021, 63(4): 790-798

      [107] Cantor M C,Costa J H,Bewley J M. Impact of observed and controlled water intake on reticulorumen temperature in lactating dairy cattle[J]. Animals, 2018, 8(11): 194-203.

      [108] Vázquez-Diosdado J, Miguel-Pacheco G, Plant B, et al. Developing and evaluating threshold-based algorithms to detect drinking behavior in dairy cows using reticulorumen temperature[J]. Journal of Dairy Science, 2019, 102(11): 10471-10482.

      [109] Amezcua R, Walsh S, Luimes P H, et al. Infrared thermography to evaluate lameness in pregnant sows[J]. The Canadian Veterinary Journal, 2014, 55(3): 268-272.

      [110] 康熙,李樹(shù)東,張旭東,等. 基于熱紅外視頻的奶牛跛行運(yùn)動(dòng)特征提取與檢測(cè)[J]. 農(nóng)業(yè)工程學(xué)報(bào),2021,37(23):169-178.

      Kang Xi, Li Shudong, Zhang Xudong, et al. Features extraction and detection of cow lameness movement based on thermal infrared videos[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(23): 169-178. (in Chinese with English abstract)

      [111] Cook N, Chabot B, Lui T, et al. Infrared thermography detects febrile and behavioural responses to vaccination of weaned piglets[J]. Animal, 2015, 9(2): 339-346.

      [112] 汪開(kāi)英,趙曉洋,何勇. 畜禽行為及生理信息的無(wú)損監(jiān)測(cè)技術(shù)研究進(jìn)展[J]. 農(nóng)業(yè)工程學(xué)報(bào),2017,33(20):197-209.

      Wang Kaiying, Zhao Xiaoyang, He Yong. Review on noninvasive monitoring technology of poultry behavior and physiological information[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(20): 197-209. (in Chinese with English abstract)

      Technology and application in automatic monitoring of the body temperature for livestock and poultry

      Xie Qiuju1, Liu Xuefei1, Zheng Ping1, Bao Jun2,3,4, Liu Honggui2, Wu Mengru1, Liu Wenyang1

      (1.,,150030,; 2.,,150030,; 3.,150030,; 4.,150030,)

      Body temperature is an important physiological indicator to measure the health status of livestock and poultry. It is critical to a fast and accurate method of temperature measurement for disease monitoring and diagnosis. Some automatic temperature measurements can be expected to replace the traditional rectal temperature measurement commonly used in livestock and poultry production, due to the current time-consuming, laborious, and posture dependency. Usually, the rectal temperature cannot be directly taken by the automatic temperature measurement. It needs to collect the temperature of other body parts, and then establish the relationship with the rectal temperature for the core temperature. In this study, the automatic temperature measurement was divided into two types: the vivo and the vitro. A systematic review was also made of the technology and development history, in order to compare two types of temperature monitoring currently used in the livestock and poultry breeding industry (e.g., pig, cows, and chickens). An intelligent device (such as a capsule or chip) was normally implanted into an animal for long-term temperature monitoring in vivo temperature measurement, indicating the popular trend for high accuracy and stability. However, the invasive devices inevitably caused animal discomfort during the implantation process, which was harmful to animal welfare. In vitro detection was also divided into contact and non-contact temperature measurement. Specifically, the contact one was simple and easy to operate, but difficult to wear on the animal body, and highly sensitive to the complex environment of animal houses. The infrared-based temperature detection provided a non-invasive body surface temperature measurement, which was characterized by rapidity, high efficiency, and no stress. But, it was normally required for the temperature compensation between the body surface and thermal environment, due to the interference by environmental factors (e.g., temperature, humidity, CO2, light intensity, and ventilation). Therefore, the prediction model was mostly focused on the relationship between the core body temperature and measured temperature derived from the parameters. As such, these important points were necessary, whatever the automatic temperature measurement was used. It was a high demand to minimize the stress response of animals for the non-invasive monitoring of body temperature. A reliable prediction was then required to establish the monitoring temperature and the core temperature of animals. Correspondingly, the environment of livestock and poultry house was tunable controlled, as the changes in the monitoring temperature of animals. These methods have been widely used in animal farming for production performance, health, and behavior monitoring. Finally, the existing technology of automatic temperature measurement was summarized for the key points of improvement research. An emphasis was posed on the commonly-used infrared temperature measurement, due to its high efficiency, convenience, no stress, and easy detection of the automatic body temperature for animal groups or flocks. The infrared temperature measurement can be expected to dominate the promising research and application of body temperature monitoring on animal farms.

      temperature; sensors; livestock and poultry temperature monitoring; infrared thermography; temperature measurement compensation; body surface temperature measurement; non-invasive temperature detection

      10.11975/j.issn.1002-6819.2022.15.023

      S126

      A

      1002-6819(2022)-15-0212-14

      謝秋菊,劉學(xué)飛,鄭萍,等. 畜禽體溫自動(dòng)監(jiān)測(cè)技術(shù)及應(yīng)用研究進(jìn)展[J]. 農(nóng)業(yè)工程學(xué)報(bào),2022,38(15):212-225.doi:10.11975/j.issn.1002-6819.2022.15.023 http://www.tcsae.org

      Xie Qiuju, Liu Xuefei, Zheng Ping, et al. Technology and application in automatic monitoring of the body temperature for livestock and poultry[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(15): 212-225. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2022.15.023 http://www.tcsae.org

      2022-04-11

      2022-07-20

      國(guó)家自然科學(xué)基金面上項(xiàng)目(32072787);農(nóng)業(yè)農(nóng)村部生豬養(yǎng)殖設(shè)施工程重點(diǎn)實(shí)驗(yàn)室課題;黑龍江省博士后資助項(xiàng)目(LBH-Q21070);東北農(nóng)業(yè)大學(xué)東農(nóng)學(xué)者計(jì)劃項(xiàng)目(19YJXG02)

      謝秋菊,博士,教授,博士生導(dǎo)師,研究方向?yàn)樾笊岘h(huán)境控制及智慧養(yǎng)殖技術(shù)。Email:xqj197610@163.com

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