溫永菁,李 春,董朝陽(yáng),程 陳,劉淑梅,宮志宏,黎貞發(fā),馮利平
鐘模型在日光溫室番茄發(fā)育進(jìn)程模擬中的適應(yīng)性探討*
溫永菁1,李 春2**,董朝陽(yáng)2,程 陳3,劉淑梅2,宮志宏2,黎貞發(fā)2,馮利平3
(1.天津市靜海區(qū)氣象局,天津 301600;2.天津市氣候中心,天津 300074;3.中國(guó)農(nóng)業(yè)大學(xué)資源與環(huán)境學(xué)院,北京 100193)
依據(jù)日光溫室番茄生長(zhǎng)發(fā)育的光溫反應(yīng)特性,基于2個(gè)番茄品種不同播期12個(gè)生長(zhǎng)季的發(fā)育階段日數(shù)、溫度和日照時(shí)數(shù)觀測(cè)資料,利用鐘模型中相關(guān)數(shù)學(xué)指數(shù)表達(dá)式表征番茄的不同發(fā)育時(shí)期和發(fā)育進(jìn)度,將番茄的發(fā)育時(shí)期指標(biāo)化。隨后對(duì)各個(gè)發(fā)育階段的模型參數(shù)進(jìn)行求解,得到基本發(fā)育系數(shù)、溫度反應(yīng)特性遺傳參數(shù)和光照反應(yīng)特性遺傳參數(shù)等模型參數(shù)初值,對(duì)模型進(jìn)行統(tǒng)計(jì)檢驗(yàn)和調(diào)試,使模型的模擬值與實(shí)測(cè)值之間誤差最小,由此得到模型參數(shù)終值,建立基于鐘模型方法的溫室番茄發(fā)育期模擬模型。經(jīng)驗(yàn)證,該模型在播種?三葉期、播種?初花期、播種?坐果期、播種?成熟期和播種?拉秧期5個(gè)番茄發(fā)育階段模擬值與實(shí)際觀測(cè)值之間的回歸估計(jì)均方根誤差(RMSE)分別為8.3、14.4、16.3、23.7和28.1d;回歸估計(jì)標(biāo)準(zhǔn)均方根誤差(NRMSE)分別為20.78%、20.18%、20.21%、17.35%和14.86%,表明本模型模擬效果較好。將鐘模型模擬結(jié)果與有效積溫法模擬結(jié)果進(jìn)行對(duì)比,鐘模型對(duì)各個(gè)關(guān)鍵發(fā)育期的模擬精度更高,模擬效果更好。
溫室;番茄;鐘模型;發(fā)育期模擬
番茄是重要設(shè)施栽培蔬菜之一。在番茄的設(shè)施生產(chǎn)中,影響其獲得高產(chǎn)和優(yōu)質(zhì)生長(zhǎng)發(fā)育的重要因子除了品種的遺傳特性及水肥管理外,溫度和光照等氣象環(huán)境條件也是重要的影響因子,實(shí)際生產(chǎn)中常通過(guò)調(diào)控溫度和光照以獲得有利氣象環(huán)境條件,從而達(dá)到高效生產(chǎn)的目的。因此,模擬溫室番茄發(fā)育進(jìn)程與環(huán)境條件的關(guān)系,實(shí)現(xiàn)溫室番茄栽培和環(huán)境調(diào)控優(yōu)化管理,提高溫室番茄生產(chǎn)經(jīng)濟(jì)效益具有重要的科研和現(xiàn)實(shí)意義[1-3]。
國(guó)外對(duì)于溫室蔬菜生長(zhǎng)發(fā)育模擬模型研究較早,取得了一定成果。其中,關(guān)于番茄發(fā)育進(jìn)程有代表性的模擬模型有HORTISIM(Horticulture Simulator)模型、TOMSIM(Tomato Simulator)番茄生長(zhǎng)發(fā)育動(dòng)態(tài)模型和TOMGRO(Tomato Growth)番茄生長(zhǎng)發(fā)育模型[4-11]。國(guó)內(nèi)設(shè)施園藝模型起步較晚,其中齊維強(qiáng)等進(jìn)行的溫室番茄生長(zhǎng)發(fā)育模型研究主要采用積溫法,利用經(jīng)驗(yàn)方法和回歸分析研究溫度對(duì)溫室番茄不同發(fā)育期的影響[12-14];曹衛(wèi)星等基于生理發(fā)育時(shí)間法(Physiological Development Time,PDT)分別建立了溫室番茄和黃瓜發(fā)育期模擬模型[15-17];鄒薇等主要考慮溫度對(duì)溫室番茄發(fā)育速度的影響,分別提出了基于線性分段函數(shù)、正弦指數(shù)分段函數(shù)和指數(shù)函數(shù)來(lái)計(jì)算生理發(fā)育時(shí)間的溫室番茄生長(zhǎng)發(fā)育模型,獲得的結(jié)果較準(zhǔn)確[18-20]。雖然目前國(guó)內(nèi)外在番茄生長(zhǎng)發(fā)育模擬模型的品種和建模方法方面已取得一系列進(jìn)展,但多為典型的統(tǒng)計(jì)經(jīng)驗(yàn)?zāi)P?,其機(jī)理性和普適性仍需加強(qiáng)。
鐘模型最早是由高亮之等開(kāi)發(fā)應(yīng)用于水稻生長(zhǎng)發(fā)育進(jìn)程的模擬模型,作為比較有代表性的大田作物模型之一,以同時(shí)考慮作物發(fā)育期長(zhǎng)短以及營(yíng)養(yǎng)生長(zhǎng)性、感溫性、感光性等遺傳特性和環(huán)境因子兩方面為優(yōu)點(diǎn),被廣泛應(yīng)用到模擬小麥、棉花、玉米等大田作物研究中[21-25]。近幾年,鐘模型被借鑒應(yīng)用到一些經(jīng)濟(jì)作物中,周靜等借鑒水稻鐘模型,構(gòu)建了描述溫室水果黃瓜不同植株葉齡、不同位置葉片獲得干物質(zhì)量模擬模型[26];程陳等構(gòu)建了基于鐘模型溫室黃瓜發(fā)育模擬模型[27],陳瀟等基于鐘模型建立了甘蔗發(fā)育期模擬模型[28]。
本研究以鐘模型為基礎(chǔ),將各個(gè)發(fā)育階段的影響因素歸因于溫室內(nèi)的空氣溫度和日照時(shí)數(shù),歸納番茄各個(gè)發(fā)育階段的三基點(diǎn)溫度,構(gòu)建“瑞粉882”和“普羅斯旺”兩個(gè)北方常見(jiàn)溫室番茄品種的發(fā)育進(jìn)程模擬模型,并通過(guò)不同播期番茄的試驗(yàn)數(shù)據(jù)對(duì)模型進(jìn)行檢驗(yàn),確保模型具有準(zhǔn)確性和普適性,以期為溫室番茄種植用戶(hù)確定種植時(shí)間、上市時(shí)間以及管理和調(diào)控提供指導(dǎo),進(jìn)而達(dá)到提高番茄種植經(jīng)濟(jì)效益的目的。
試驗(yàn)于2013-2015年在天津市農(nóng)業(yè)科技創(chuàng)新基地日光溫室(116.97°E,39.43°N,海拔8m)內(nèi)進(jìn)行。該溫室為典型二代溫室,墻高3.7m,墻體厚度50.0cm,脊高5.3m,后屋面仰角44.0°,前屋面角32.0°,跨度10.0°,長(zhǎng)度65m,占地總面積650.0m2。試驗(yàn)供試品種為“瑞粉882”和“普羅斯旺”。試驗(yàn)期間共種植4茬番茄,包括2013年和2014年各一次春茬栽培,即冬季播種育苗,春季移栽,品種為“瑞粉882”;2013/2014年度和2014/2015年度各一次秋冬茬栽培,即秋季播種育苗并栽培,品種為“普羅斯旺”。當(dāng)?shù)爻R?guī)播種日期,春茬在2-3月播種,秋冬茬在8-9月播種。每茬設(shè)3個(gè)播期,早播:早于當(dāng)?shù)爻R?guī)播種日期15~30d;中播:當(dāng)?shù)爻R?guī)播種日期,春茬在2?3月播種,秋冬茬在8?9月播種;晚播:晚于當(dāng)?shù)爻R?guī)播種日期15~30d。其中,中播用于建立模型,早播和晚播用于模型檢驗(yàn)。每個(gè)播期處理設(shè)3個(gè)重復(fù),采用隨機(jī)區(qū)組排列。各小區(qū)栽培行距均為0.67m,株距為0.55m,種植密度為2.71 株×m?2。栽培管理措施按當(dāng)?shù)爻R?guī)。
1.2.1 發(fā)育期觀測(cè)
根據(jù)番茄生物學(xué)特性,結(jié)合當(dāng)?shù)卦耘嘟?jīng)驗(yàn),并參考文獻(xiàn)[11?14],將番茄的整個(gè)生長(zhǎng)過(guò)程劃分為6個(gè)關(guān)鍵發(fā)育期,定義各發(fā)育期相應(yīng)的形態(tài)特征如表1。自播種之日起每隔5d觀測(cè)1次,臨近關(guān)鍵發(fā)育期時(shí)每日觀察,當(dāng)供試植株中有不少于50%植株表現(xiàn)出某發(fā)育期的形態(tài)特征時(shí),即視為群體到達(dá)該發(fā)育期。
表1 番茄發(fā)育期的劃分及其形態(tài)指標(biāo)
1.2.2 氣象數(shù)據(jù)采集
溫室內(nèi)小氣候觀測(cè)選用DZN1型小氣候觀測(cè)儀(天津市產(chǎn)),溫度傳感器的精度為±0.2℃,測(cè)量范圍-40.0~50.0℃。溫室內(nèi)空氣溫度和輻射自動(dòng)記錄頻率為1次·10min?1。
1.3.1 鐘模型的建立
由于溫度和光照因子對(duì)番茄的生長(zhǎng)發(fā)育有重要影響,因此,每個(gè)發(fā)育階段都考慮到了這兩個(gè)環(huán)境因子。表達(dá)式為[28?32]
式中,DS為發(fā)育期或發(fā)育階段的日數(shù)(d);k為基本發(fā)育系數(shù)(Basic development coefficient),由品種自身的遺傳特性決定,k值越大,說(shuō)明該品種發(fā)育速度越快,為早熟品種;p為溫度反應(yīng)特性遺傳系數(shù)(Genetic thermal coefficient),反應(yīng)該品種在這一發(fā)育階段內(nèi)對(duì)溫度的反應(yīng)敏感性;TE為溫度效應(yīng)因子,反應(yīng)溫度對(duì)番茄發(fā)育的非線性影響[27?28,33];q為光周期反應(yīng)特性遺傳系數(shù)(Genetic thermal coefficient),反應(yīng)該品種在這一發(fā)育階段對(duì)日照時(shí)數(shù)的反應(yīng)敏感性;PE為光周期效應(yīng)因子,反應(yīng)日照時(shí)數(shù)對(duì)番茄發(fā)育的非線性影響。
利用模型中基于一系列參數(shù)的數(shù)學(xué)指數(shù)表達(dá)式表征番茄的不同發(fā)育時(shí)期,并在各發(fā)育期指數(shù)之間通過(guò)找到相應(yīng)的小數(shù)值表示各發(fā)育時(shí)期的發(fā)育進(jìn)度,最終實(shí)現(xiàn)將番茄的發(fā)育時(shí)期指標(biāo)化。各發(fā)育時(shí)期內(nèi)影響番茄發(fā)育的主要環(huán)境因子及該階段的基本發(fā)育模型都隨基因型品種而異。
隨后對(duì)各個(gè)發(fā)育階段的模型參數(shù)進(jìn)行求解,得到模型參數(shù)的初值,主要包括基本發(fā)育系數(shù)、溫度反應(yīng)特性遺傳參數(shù)和光照反應(yīng)特性遺傳參數(shù),對(duì)模型進(jìn)行統(tǒng)計(jì)檢驗(yàn)并通過(guò)非線性規(guī)劃中的步長(zhǎng)加速法對(duì)各個(gè)參數(shù)進(jìn)行逐一調(diào)試,使模型的模擬值與實(shí)測(cè)值之間誤差最小,由此得到模型參數(shù)終值。
發(fā)育生理日數(shù)(D0)表示品種完成某個(gè)發(fā)育階段的基本發(fā)育期最短的發(fā)育日數(shù)[34]。
1.3.2 有效積溫模型的建立
預(yù)測(cè)作物發(fā)育期傳統(tǒng)的方法是使用有效積溫法(Growing degree days,GDD),其最大的優(yōu)點(diǎn)是模型輸入變量只有溫度,計(jì)算簡(jiǎn)單,易于實(shí)踐推廣。有效積溫法的計(jì)算式為[15,29]
表2 番茄不同發(fā)育階段的三基點(diǎn)溫度和日照時(shí)數(shù)
注:Tb為作物生長(zhǎng)的下限溫度,Tol為作物生長(zhǎng)的最適下限溫度,Tou為作物生長(zhǎng)的最適上限溫度,Tm為作物生長(zhǎng)的上限溫度,Db為臨界日照時(shí)數(shù),Da為最適日照時(shí)數(shù)。
Note: Tb is lower limit temperature at which crops grow, Tol is lower optimal temperature at which crops grow, Tou is upper optimum temperature at which crops grow, Tm is upper limit temperature at which crops grow, Db is critical sunshine hours, Da is optimum hours of sunshine.
1.3.3 模型的檢驗(yàn)
式中,Xobs和Xsim分別為觀測(cè)值和模擬值,模擬誤差的大小可用RMSE和NRMSE表示,總體模擬效果由模擬值均值與實(shí)測(cè)值均值的差異反映。當(dāng)線性回歸系數(shù)(α)越接近1,截距(β)越接近0,并且決定系數(shù)(R2)越大時(shí),模擬值與觀測(cè)值的吻合度越高。
2.1.1 番茄發(fā)育期觀測(cè)結(jié)果
根據(jù)表3中發(fā)育期記錄結(jié)果可算出,兩個(gè)品種共12組試驗(yàn)的播種?三葉期、播種?初花期、播種?坐果期、播種?成熟期和播種?拉秧期,平均所需日數(shù)分別約為36.9、68.6、78.3、133.3和186.8d。同時(shí),根據(jù)實(shí)際觀測(cè)的氣象數(shù)據(jù)計(jì)算出各階段有效積溫的平均累積值分別為371.3、517.3、556.7、763.8和1108.5℃·d,因此,以此作為有效積溫發(fā)育期模擬模型的參數(shù)。
2.1.2 鐘模型各發(fā)育階段參數(shù)確定
對(duì)鐘模型表達(dá)式(式1)兩邊同時(shí)取對(duì)數(shù)進(jìn)行線性化,得到
將兩個(gè)品種中播期處理觀測(cè)的各發(fā)育階段日數(shù)、溫度和日照時(shí)數(shù)觀測(cè)資料,代入線性方程中,利用最小二乘法求解出模型參數(shù)初值,結(jié)果見(jiàn)表4。由表可見(jiàn),兩個(gè)品種各發(fā)育階段的發(fā)育進(jìn)程均可用鐘模型來(lái)表達(dá),復(fù)合相關(guān)系數(shù)均通過(guò)0.05水平的顯著性檢驗(yàn)。但是,同時(shí)表中也顯示,不同品種或同一品種不同發(fā)育階段內(nèi),方程的基本發(fā)育系數(shù)(k)、溫度反應(yīng)特性遺傳系數(shù)(p)、光照反應(yīng)特性遺傳系數(shù)(q)略有差異,說(shuō)明不同品種在不同發(fā)育期對(duì)環(huán)境溫度、光照的反應(yīng)特性有差異。從兩個(gè)品種整個(gè)生長(zhǎng)季模擬方程的系數(shù)看,品種間存在較大差異。
表3 2013?2014年兩品種番茄不同播期的主要發(fā)育期日期記錄(年?月?日)
注:E為早播處理,M為中播處理,L為晚播處理。
Note: E is early sowing treatment, M is medium sowing treatment, L is late sowing treatment.
表4 兩品種番茄各階段發(fā)育進(jìn)程的鐘模型模擬方程
續(xù)表
注:DS為各發(fā)育階段的發(fā)育日數(shù),TE為溫度效應(yīng)因子,PE為光周期效應(yīng)因子。
Note: DS is days of development at each development stage, TE is temperature effect factor, PE is photoperiod effect factor.
2.2.1 與實(shí)測(cè)值比較
利用得出的參數(shù)終值,根據(jù)表4各方程對(duì)各個(gè)發(fā)育階段的發(fā)育進(jìn)程進(jìn)行計(jì)算,與兩個(gè)品種各發(fā)育期實(shí)測(cè)天數(shù)進(jìn)行比較,對(duì)模型進(jìn)行驗(yàn)證,模擬驗(yàn)證結(jié)果見(jiàn)圖1。由圖可見(jiàn),播種?三葉期的模擬結(jié)果最好,播種?初花期次之,而播種?成熟期的模擬結(jié)果最差。這也是由于在初花期之前發(fā)育期界限特征較明顯,并且為營(yíng)養(yǎng)生長(zhǎng)階段,主要受光溫影響;初花期之后為生殖生長(zhǎng),多重環(huán)境因子共同作用,并且植株受授粉、打叉、掐尖兒、采摘等人為農(nóng)事活動(dòng)影響,導(dǎo)致模型模擬準(zhǔn)確率較低。
由表5可知,播種?三葉期、播種?初花期、播種?坐果期、播種?成熟期、播種?拉秧期的模擬值與實(shí)測(cè)值的均值分別相差1.5、1.8、2.3、1.5、0.4d,標(biāo)準(zhǔn)差在12.0d以?xún)?nèi);各個(gè)發(fā)育階段的P值都在0.38~0.49,說(shuō)明發(fā)育期模擬值與實(shí)測(cè)值之間差異極??;播種?成熟期、播種?拉秧期的NRMSE都在10%~15%,播種?三葉期、播種?初花期、播種?坐果期的NRMSE都在15%~20%,具有較高的模擬精度;播種?三葉期的RMSE在10d以?xún)?nèi),播種?初花期、播種?坐果期的RMSE在15d以?xún)?nèi),播種?成熟期的RMSE在20d以?xún)?nèi),播種?拉秧期的RMSE在30d以?xún)?nèi);從α值和β值也可以得出模擬值與實(shí)測(cè)值的線性關(guān)系較顯著。綜合分析可以得出,鐘模型能夠較好地預(yù)測(cè)番茄各個(gè)關(guān)鍵發(fā)育時(shí)期。
圖1 各階段模擬發(fā)育日數(shù)與實(shí)測(cè)發(fā)育日數(shù)的對(duì)比
注:虛線方程為y=(1±CV)·x,CV為變異系數(shù),設(shè)定值為10%。α為線性方程的斜率,β為截距。下同。
Note: The equation of dotted line is y=(1±CV)·x,CV is coefficient of variation and set the value at 10%. α and β aretheslope and intercept of linear equation, respectively. The same as below.
表5 番茄各發(fā)育階段驗(yàn)證結(jié)果的統(tǒng)計(jì)指標(biāo)
2.2.2 與有效積溫模型模擬結(jié)果比較
根據(jù)有效積溫模型參數(shù)與鐘模型參數(shù),對(duì)兩個(gè)品種番茄的各發(fā)育階段進(jìn)行模擬,統(tǒng)計(jì)結(jié)果見(jiàn)表6。由表可以看出,鐘模型預(yù)測(cè)誤差都維持在3.5d以?xún)?nèi),而有效積溫法的預(yù)測(cè)誤差在15.5d以?xún)?nèi)。除播種?三葉期外,鐘模型的RMSE和NRMSE均比有效積溫法小,鐘模型的RMSE在6.8~23.0d,而有效積溫法的RMSE在5.9~33.1d。鐘模型的NRMSE在12.13%~6.50%,而有效積溫法的NRMSE在15.09%~34.38%。總體而言,鐘模型的模擬精度優(yōu)于有效積溫法。對(duì)于播種?三葉期的模擬,有效積溫法比鐘模型的模擬精度要稍好,而其余關(guān)鍵發(fā)育階段,鐘模型的模擬精度明顯優(yōu)于有效積溫法模擬精度。其原因可能是番茄發(fā)育初期以營(yíng)養(yǎng)生長(zhǎng)為主,溫度為其主要驅(qū)動(dòng)因子,所以前期兩種方法的模擬效果均較好,而進(jìn)入生長(zhǎng)中后期,主要驅(qū)動(dòng)因子增多,僅以溫度為輸入量難以獲得較好的模擬結(jié)果。
表6 鐘模型(用C表示)和有效積溫模型(用EA表示)對(duì)番茄各階段發(fā)育日數(shù)的模擬結(jié)果
注:誤差=觀測(cè)值?模擬值。
Note: Error=observation value-simulation value.
綜合分析可知,鐘模型能夠很好地預(yù)測(cè)番茄各個(gè)關(guān)鍵發(fā)育期。由于有效積溫法忽略了光照等其它重要因素的影響,僅考慮番茄發(fā)育速度與溫度的線性關(guān)系,并且只在發(fā)育的生物學(xué)下限溫度與上限溫度范圍內(nèi)給出不同的發(fā)育速率,假定番茄發(fā)育各個(gè)時(shí)期對(duì)溫度的敏感性是恒定的,違背了番茄的實(shí)際發(fā)育規(guī)律,因此有效積溫的預(yù)測(cè)誤差偏大。鑒于番茄的發(fā)育受溫度與日長(zhǎng)的影響,本研究建立了番茄發(fā)育的非線性模型,經(jīng)可靠性檢驗(yàn)后認(rèn)為,用這一方法解釋番茄的生長(zhǎng)發(fā)育狀況可以得到較高的模擬精度。
鐘模型能較準(zhǔn)確地預(yù)測(cè)溫室番茄的發(fā)育期,對(duì)番茄各生長(zhǎng)階段的模擬值與實(shí)測(cè)值的RMSE在8.3~28.1d,NRMSE在14.86%~20.78%,而有效積溫法模擬值與實(shí)測(cè)值的RMSE在5.9~33.1d,NRMSE在15.09%~34.38%。綜合比較兩個(gè)發(fā)育期模擬模型對(duì)各個(gè)發(fā)育階段的實(shí)測(cè)值與模擬值的α值和β值可以看出,鐘模型模擬值與實(shí)測(cè)值之間具有很好的線性關(guān)系,RMSE分別為8.3、14.4、16.3、23.7、28.1d,NRMSE分別為20.78%、20.18%、20.21%、17.35%、14.86%,可見(jiàn)鐘模型的模擬精度要優(yōu)于有效積溫模型。
(1)在試驗(yàn)數(shù)據(jù)獲取方面,根據(jù)2013-2015年試驗(yàn)數(shù)據(jù)建模并檢驗(yàn),后續(xù)可堅(jiān)持多年試驗(yàn),補(bǔ)充數(shù)據(jù)量,調(diào)整模擬模型參數(shù),進(jìn)一步提升溫室番茄發(fā)育進(jìn)程模擬模型準(zhǔn)確率。此外,本研究?jī)H獲取了天津地區(qū)的兩個(gè)代表性品種發(fā)育期數(shù)據(jù),實(shí)際溫室番茄在全國(guó)的種植面積與種植品種都較多,還需進(jìn)一步在控制環(huán)境下在更多地區(qū)進(jìn)行不同基因型品種比較試驗(yàn)來(lái)完善模型對(duì)更多地域基因型的品種普適性。
(2)在研究方法方面,關(guān)于影響番茄發(fā)育期的環(huán)境因素方面考慮仍不夠全面,例如播種深度、施肥等農(nóng)業(yè)措施的影響未考慮到模型中,還需進(jìn)行控制環(huán)境下的試驗(yàn)研究來(lái)證實(shí)和修訂。
(3)在模型精度方面,溫室番茄發(fā)育期模擬與經(jīng)典的積溫模型模擬法進(jìn)行比較,后續(xù)研究可與其它溫室番茄發(fā)育進(jìn)程模擬模型方法進(jìn)行對(duì)比分析,并對(duì)不同方法的結(jié)果進(jìn)行集成分析,以?xún)?yōu)化溫室番茄發(fā)育期模擬模型。
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Research on the Simulation Model of Tomato Development Period in Solar Greenhouse Based on Clock Model Method
WEN Yong-jing1,LI Chun2,DONG Chao-yang2,CHENG Chen3,LIU Shu-mei2,GONG Zhi-hong2,LI Zheng-fa2,FENG Li-ping3
(1. Jinghai District Meteorological Office,Tianjin 301600,China; 2.Tianjin Climate Center, Tianjin 300074; 3. College of Resources and Environment, China Agricultural University, Beijing 100193)
Tomato is one of the most important vegetables grown in China and around the world. In the facility production of tomato, not only the genetic characteristics of varieties and the management of water and fertilizer, but also the meteorological conditions such as temperature and light are important factors affecting the high yield and quality growth and development of tomato. In the actual production, the favorable meteorological conditions are often obtained by adjusting the temperature and light, so as to achieve the purpose of efficient production. Based on the clock model, this study attributed the influencing factors of each development stage to the air temperature and sunshine hours in the greenhouse, summarized the temperature of three basis points in each development stage of tomato, and constructed the development process simulation model of "Rijk Zwaan882" and "Provence" two common greenhouse tomato varieties in the north of China. The experiment was conducted in solar greenhouse (116.97°E, 39.43°N, altitude 8m) of Tianjin Agricultural Science and Technology Innovation Base from 2013 to 2015. According to the characteristics of light and temperature response of tomato growth and development in solar greenhouse, the different development stages and development phases of tomato were characterized by the mathematical index expression in clock model, and the development stage of tomato was indexed. Then, the model parameters of each development stage were solved, and the initial values of the model parameters, such as the basic development coefficient, the genetic parameters of temperature response characteristics and the genetic parameters of light response characteristics, were obtained, and the model was statistically tested and adjusted. The error between the simulated value and the measured value was minimized, and the final value of the model parameters was obtained. A simulation model of tomato development periods in greenhouse were established based on the clock model. The results showed that, firstly, the regression estimated root mean square error (RMSE) between the simulated values and the actual observed values in the five tomato development stages of the model were 8.3, 14.4, 16.3, 23.7 and 28.1 days, respectively. The standard root mean square error (NRMSE) of regression estimation were 20.78%, 20.18%, 20.21%, 17.35% and 14.86%, respectively, indicating that the simulation effect of this model was good. Secondly, the clock model simulation results was compared with the method of growing degree days (GDD) model simulation results. the RMSE of the tomato in each development stage of the clock model of the simulated values and the measured values was in 8.3?28.1 days, NRMSE was in 14.86%?20.78%, and the RMSE of the tomato in each development stage of GDD model of the simulated values and measured values was in 5.9?33.1 days, NRMSE was in 15.09%?34.38%. It was showed that the clock model could accurately predict development of greenhouse tomato development periods. In general, it was helpful to provide guidance for greenhouse tomato planting users to determine planting time, marketing time, management and control, so as to improve the economic benefits of tomato planting.
Greenhouse;Tomato;The clock model;Development periods simulation
10.3969/j.issn.1000-6362.2020.10.002
溫永菁,李春,董朝陽(yáng),等.鐘模型在日光溫室番茄發(fā)育進(jìn)程模擬中的適應(yīng)性探討[J].中國(guó)農(nóng)業(yè)氣象,2020,41(10):622-631
2020-03-19
李春,E-mail:spring_lee@hotmail.com
天津市農(nóng)業(yè)科技成果轉(zhuǎn)化與推廣項(xiàng)目“溫室小氣候資源高效利用及蔬菜茬口搭配技術(shù)集成與應(yīng)用”(201502150)
溫永菁,E-mail:betterbaymax@163.com