宮彬彬,王 寧,章鐵軍,吳曉蕾,呂桂云,褚新培,高洪波※
?
綜合形態(tài)與葉片葉綠素含量的番茄壯苗指數(shù)篩選
宮彬彬1,王 寧1,章鐵軍2,吳曉蕾1,呂桂云1,褚新培1,高洪波1※
(1. 河北農(nóng)業(yè)大學園藝學院,保定 071001;2. 河北農(nóng)業(yè)大學現(xiàn)代教育技術中心,保定 071001)
為建立最佳的番茄秧苗壯苗指數(shù),提高秧苗評判的準確度,該文以四葉一心番茄秧苗為研究對象,在測定11項秧苗指標的基礎上,利用模糊綜合評判法建立番茄秧苗綜合評價指數(shù),使用主成分分析進行指標篩選并組合構成多個番茄壯苗指數(shù),通過綜合評價指數(shù)與壯苗指數(shù)的相關分析篩選出適宜的壯苗指數(shù)并驗證。結果表明:對300株樣本進行統(tǒng)計分析,番茄秧苗綜合評價指數(shù)為0.26~0.79,可全面概括秧苗的整體素質(zhì),能客觀、準確地評價秧苗健壯程度;通過秧苗單一指標的主成分分析將各指標劃分為形態(tài)指標、色素指標和株高3個主成分,表明秧苗的質(zhì)量必須從形態(tài)、葉綠素含量和株高這3方面進行評價。從主成分中各選一種指標進行完全隨機排列組合成25種壯苗指數(shù),并篩選出與綜合評價指數(shù)相關性較高且具有代表性的4種壯苗指數(shù);并用3種不同品種番茄秧苗對其進行穩(wěn)定性驗證,其中壯苗指數(shù)“(總葉綠素/株高)?全株干質(zhì)量”與綜合評價指數(shù)相關性最大為0.797且極顯著(<0.01),穩(wěn)定性好、代表性強,可作為衡量番茄秧苗素質(zhì)的推薦壯苗指數(shù)。以番茄秧苗的綜合評價指數(shù)為分級依據(jù),根據(jù)推薦壯苗指數(shù)將秧苗質(zhì)量分為3個等級(等級Ⅰ(壯苗指數(shù)≥0.065)為優(yōu)質(zhì)苗,等級Ⅱ(壯苗指數(shù):0.030~0.065)為合格苗,等級Ⅲ(壯苗指數(shù)≤0.030)為弱苗(幼苗或老苗)),各等級間差異顯著,可以作為較好的判別指標。該研究表明可為番茄育苗生產(chǎn)提供參考,也可為其他蔬菜秧苗評判提供參考。
葉綠素;形態(tài);番茄;壯苗指數(shù);模糊綜合評判;主成分分析;相關性分析
蔬菜育苗已成為現(xiàn)代蔬菜產(chǎn)業(yè)的首要和關鍵技術環(huán)節(jié),秧苗健壯程度的評價是工廠化育苗成功與否的關鍵,也是后期蔬菜生長、產(chǎn)量和品質(zhì)的保障[1]。在傳統(tǒng)育苗過程中,通常通過觀察或測定秧苗的株高、莖粗、葉片顏色等單一指標進行秧苗健壯程度的評判,但這種方法包含的指標較少,有時與秧苗的實際質(zhì)量存在較大偏差。在對蔬菜秧苗壯苗指數(shù)的大量研究過程中,提出了(莖粗/莖高)×全株干質(zhì)量、(莖粗/株高+根干質(zhì)量/地上部干質(zhì)量)×全株干質(zhì)量、(根干質(zhì)量/地上部干質(zhì)量)×全株干質(zhì)量等一些較為適用的評價指標[2-4]。其中1984年建立的(莖粗/莖高)×全株干質(zhì)量[5]仍是目前較為通用的蔬菜秧苗好壞的評判依據(jù),在實際生產(chǎn)和科學研究中得到了廣泛應用[6]。然而,由于這些壯苗評判標準主要以番茄形態(tài)指標為基礎,而且在品種和育苗條件發(fā)生變化時,這一壯苗指數(shù)準確率存在下降的風險。近年來,大量研究證明葉片色素指標是秧苗光合作用的關鍵因素,與秧苗質(zhì)量有著密切的關系,因此葉綠素指標已作為蔬菜等秧苗質(zhì)量評價的關鍵參數(shù)[7-10]。但是,如何科學將葉綠素指標與形態(tài)指標聯(lián)系在一起,作為蔬菜等秧苗健壯程度的評價指標尚不明確。
模糊綜合評判法是一種基于模糊數(shù)學的評價方法,可以在大量樣本的情況下提供一個較為可靠的評判依據(jù),在農(nóng)業(yè)生產(chǎn)中主要應用在溫室環(huán)境控制[11]、灌溉系統(tǒng)設計[12]、植物抗逆性評價[13-15]、土地質(zhì)量等級評價[16]等領域,而應用數(shù)學模型評價幼苗壯苗指數(shù)的研究卻比較少見,尤其對于工廠化蔬菜育苗模式。為此,本文以工廠化培育的番茄秧苗為研究對象,在大量、全面測定秧苗單項指標的基礎上,利用模糊綜合評判法,首先建立番茄秧苗指標的綜合評價指數(shù),再依據(jù)秧苗指標的主成分分析結果將關鍵性指標組合構成壯苗指數(shù),最后根據(jù)壯苗指數(shù)和綜合評價指數(shù)的相關性分析,篩選出極顯著相關,且穩(wěn)定性好、代表性強的番茄壯苗指數(shù),并根據(jù)綜合評價指數(shù)和壯苗指數(shù)聚類分析的結果對番茄秧苗質(zhì)量進行分級,旨在為番茄育苗提供理論依據(jù)以及為蔬菜秧苗健壯程度的評價提供參考。
本試驗于2017年9月–2018年9月在河北饒陽萬禾冠蔬菜種植專業(yè)合作社和定興縣華龍蔬菜專業(yè)合作社的工廠化育苗基地進行。育苗采用72孔育苗穴盤,基質(zhì)采用“商道”育苗專用基質(zhì)(容重0.32 g/cm3,總孔隙度80.5%,氣水比0.27,pH值0.64,EC值810S/cm),番茄秧苗生長至四葉一心時進行各項指標測定。
構建壯苗指數(shù)所用番茄品種為‘金棚一號’,指數(shù)穩(wěn)定性評價所用番茄品種為‘金棚一號’、‘東圣’和‘美顏1319’。
隨機抽取300株四葉一心番茄秧苗,洗凈并用濾紙擦干,用直尺測定株高;用游標卡尺(日本三豐/IP67)測定莖粗;用剪刀將地上和地下部分開,采用萬分之一電子天平(奧豪斯/CP114)分別稱量地上部、地下部鮮質(zhì)量和全株鮮質(zhì)量;再將其裝于信封袋內(nèi)置于鼓風干燥箱(SHKTYQ/101-2AB)105 ℃殺青30 min,80 ℃下烘至恒質(zhì)量,并稱量地下部干質(zhì)量、地上部干質(zhì)量和全株干質(zhì)量,并用地下部鮮質(zhì)量/地上部鮮質(zhì)量、地下部干質(zhì)量/地上部干質(zhì)量分別表示烘干前和烘干后秧苗根冠比;葉綠素a、葉綠素b、總葉綠素、類胡蘿卜素含量采用乙醇丙酮[17]浸提法測定;采用葉綠素儀(SPAD-502Plus)測定葉片葉綠素相對含量。
參照吳克寧等[18]模糊綜合評判法,以番茄秧苗單項指標數(shù)值范圍[19]和單項指標所屬的隸屬函數(shù)確定單因素評價矩陣;以番茄秧苗單項指標與其他指標的線性回歸確定權重系數(shù)矩陣;再通過單因素評價矩陣乘權重系數(shù)確定綜合評價矩陣即每棵秧苗的綜合評價指數(shù)。
1.3.1 單項指標隸屬函數(shù)的確定
隸屬函數(shù)主要分為4種類型,戒上型,戒下型、峰型和直線型[20]。戒上型隸屬函數(shù)是指指標在某一范圍與秧苗質(zhì)量正相關,超過此范圍對秧苗質(zhì)量影響不大,多用于有利因子。戒下型隸屬函數(shù)是指指標在某一范圍與秧苗質(zhì)量負相關,超過此范圍對秧苗質(zhì)量影響不大,多用于有害因子。峰型隸屬函數(shù)是指指標在某一范圍對秧苗質(zhì)量最為有益,偏離這一范圍增長或是減少都不利于秧苗質(zhì)量。直線型隸屬函數(shù)是指指標沒有明顯的上下限,隨指標的增長與秧苗質(zhì)量成正相關。在具體表達式方面,戒上型,戒下型和峰型這3種隸屬函數(shù)又分為線性和非線性[21],由于本研究中所涉及到的11項指標與番茄秧苗質(zhì)量之間存在較好的線性關系,因此根據(jù)煙草[22]和黃瓜[23]單項指標的特性,將各單項指標分為3種類型的線性隸屬函數(shù):“拋物線型”(式(1))、“正S型”(式(2))和“直線型”(式(3))。根據(jù)隸屬函數(shù)和設定的指標臨界值,將每株秧苗單項指標的測定值代入相應隸屬函數(shù)公式,計算隸屬度,組合成單因素評價矩陣(式(4))。
3()=+(3)
式中μ()(=1,2,3)為隸屬函數(shù)值,1表示指標數(shù)值下限,2表示指標最優(yōu)數(shù)值下限,3表示指標最優(yōu)數(shù)值上限,4表示指標數(shù)值上限。其中=(1-0.1)/(max–min),=1–max,max表示數(shù)值上限,min表示數(shù)值下限。為行列矩陣,樣本數(shù)量,為每個樣本秧苗指標的個數(shù)。
1.3.2 單項指標權重系數(shù)的確定
采用多元線性回歸法,根據(jù)各指標與其他指標之間的共線性強弱來確定指標權重。
3)通過對每個指標的復相關系數(shù)取倒數(shù)后歸一化得到各項指標的權重系數(shù)r,組成權重系數(shù)矩陣(式(7))。
1.3.3 綜合評價指數(shù)
利用模糊矩陣合成計算綜合評價矩陣,×T=(式(8))[24-25]。
式中為綜合評判矩陣;為單因素指標評價矩陣;為權重系數(shù)矩陣。
將番茄11項單項指標采用IBM SPSS Statistics對數(shù)據(jù)進行歸一化處理,對標準化后的指標進行主成分分析,去除各主成分中貢獻率小于0.4的成分后,得到對各主成分相關性較大的關鍵指標。
將每個主成分中相關性較大的指標進行完全隨機排列組合,初步建立壯苗指數(shù)。以綜合評價指數(shù)為番茄秧苗的評定標準,以傳統(tǒng)壯苗指數(shù)為對照,進行壯苗指數(shù)與綜合評價指數(shù)相關性分析[26],篩選出相關性較高且優(yōu)于傳統(tǒng)壯苗指數(shù)的壯苗指數(shù)。
分別選取60株‘金棚1號’,‘東圣’和‘美顏1319’四葉一心的秧苗,對單項指標進行測定,分別建立3種品種秧苗的綜合評價指數(shù),并與篩選出的壯苗指數(shù)做相關性分析,以驗證其的穩(wěn)定性。
采用-均值聚類的方法[27-28],以300株番茄秧苗樣本的綜合評價指數(shù)作為類別中心值,對篩選出的壯苗指數(shù)進行聚類分析,根據(jù)中心值結果確定依據(jù)壯苗指數(shù)劃分的番茄秧苗質(zhì)量分級標準。
從表1可以看出,番茄秧苗單項指標權重系數(shù)整體偏低,在0.070~0.180之間,表明多項指標之間存在明顯的共線性。其中株高的權重系數(shù)最大為0.180,可能是由于株高和其他指標的相關性較差,而且在番茄秧苗生長過程中差異性較大;莖粗、根冠比(鮮樣)、全株鮮質(zhì)量、根冠比(干樣)、全株干質(zhì)量、葉綠素a、葉綠素b、總葉綠素、類胡蘿卜素、SPAD等指標的權重系數(shù)均小于0.1,證明這些指標之間關系較為密切,共線性較高。
表1 番茄秧苗單項指標權重系數(shù)
番茄秧苗單項指標隸屬函數(shù)參數(shù)[19,22-23]如表2所示,其中株高在一定范圍可以提高秧苗質(zhì)量,偏離這一范圍都容易導致秧苗素質(zhì)變差,這種趨勢適合于“拋物線型”隸屬函數(shù);莖粗、全株鮮質(zhì)量和全株干質(zhì)量在一定范圍與秧苗質(zhì)量呈正相關,超過這一范圍后對秧苗質(zhì)量評價影響較小,這一特性符合“正S型”隸屬函數(shù);葉綠素a、葉綠素b、總葉綠素、類胡蘿卜素、SPAD和根冠比在秧苗質(zhì)量評價中沒有明顯的上下限,且均與秧苗質(zhì)量呈正相關,為“直線型”隸屬函數(shù)的特點。
表2 番茄秧苗單項指標的隸屬函數(shù)和臨界值
由于篇幅有限,在此處僅列出6株樣本的綜合評價指數(shù)計算結果。
1)首先根據(jù)四葉一心番茄秧苗的指標測定建立秧苗指標參數(shù)矩陣,如式(9)所示。
式中從左至右的列依次為指標株高、莖粗、根冠比(鮮樣)、全株鮮質(zhì)量、根冠比(干樣)、全株干質(zhì)量、葉綠素a、葉綠素b、總葉綠素、類胡蘿卜素和SPAD。下同。
2)將番茄秧苗每一列指標帶入所屬的隸屬函數(shù)中進行計算,得到番茄秧苗單因素評價矩陣,如式(10)所示。
3)將番茄秧苗單因素評價矩陣與表(1)中指標權質(zhì)量系數(shù)相乘,得到綜合評價矩陣,結果如式(11)所示。
將300株番茄秧苗樣本的綜合評價指數(shù)進行匯總(圖1),番茄質(zhì)量綜合評價指數(shù)在0.26~0.79,曲線的上下范圍較大,表明本次試驗取樣范圍較廣,包含各種優(yōu)劣番茄秧苗,能夠準確地作為壯苗指數(shù)準確性的評判依據(jù)。
圖1 番茄秧苗質(zhì)量綜合評價指數(shù)
根據(jù)11項番茄秧苗單項指標主成分分析結果,前3個主成分總方差的累計貢獻率大于80%,可作為番茄秧苗的鑒別指標。從(表3)番茄秧苗主成分旋轉后的成分矩陣可以看出,去除掉相關性小于0.4的成分后,番茄秧苗總葉綠素、葉綠素a、類胡蘿卜素、葉綠素b、和SPAD等色素指標是主成分1的主要因子,根冠比(干樣)、根冠比(鮮樣)、全株干質(zhì)量、全株鮮質(zhì)量和莖粗等形態(tài)指標是主成分2主要因子,株高是主成分3的主要因子。
表3 番茄秧苗指標主成分旋轉后的成分矩陣
通過主成分分析,將番茄秧苗的11項單一指標組合為3個主要成分,壯苗指數(shù)必須同時包括這3個主成分中一個或多個指標才能全面的體現(xiàn)番茄秧苗質(zhì)量差異[29-30]。為了使壯苗指數(shù)盡量簡化且包含全面,在本研究中,從每類主成分中分別選取1項指標進行完全隨機排列組合,得到25個壯苗指數(shù)(表4),由于株高為拋物線類型(表2),說明株高大于一定數(shù)值后對壯苗指數(shù)有負向的決定作用,這與張世祥[31]的研究結果一致。為了保障壯苗指數(shù)的單調(diào)性,壯苗指數(shù)的組合中采用“/株高”的方式,其余指標均組合在分子的位置。并以傳統(tǒng)壯苗指數(shù)公式“(莖粗/株高)×全株干質(zhì)量”和“(莖粗/株高+根干質(zhì)量/地上部干質(zhì)量)×全株干質(zhì)量”為對照CK1和CK2。
表4 番茄壯苗指數(shù)構建
將得到的壯苗指數(shù)與綜合評價指數(shù)做相關性分析(表5)。所有構建的番茄壯苗指數(shù)均與綜合評價指數(shù)呈極顯著相關,CK1“(莖粗/株高)×全株干質(zhì)量”和CK2“(莖粗/株高+根干質(zhì)量/地上部干質(zhì)量)×全株干質(zhì)量”的相關系數(shù)分別為0.723和0.738,其中X15“(總葉綠素/株高)×全株干質(zhì)量”與綜合評價指數(shù)相關性最大,達到0.798。篩選得到的4個相關性高于對照的壯苗指數(shù)相關性分別為:X5、X15、X20、X25,用于后續(xù)評價驗證。
表5 番茄幼苗壯苗指數(shù)與綜合評價指數(shù)的相關性分析
注:“**”極顯著(<0.01)。下同。
Note: “**”means different significantly at 0.01 level. Same as follows.
不同番茄品種秧苗之間壯苗指數(shù)相關性存在差異(表6),其中對照CK1、CK2均表現(xiàn)出相關性不穩(wěn)定(‘金鵬1號’分別為0.627和0.607,‘美顏1319’分別為0.802和0.822),表明CK1、CK2在番茄品種改變時不能全面的評定秧苗質(zhì)量。在所篩選的壯苗指數(shù)中,只有X5“(葉綠素a/株高)×全株干質(zhì)量”和X15“(總葉綠素/株高)×全株干質(zhì)量”表現(xiàn)出較高的相關性和較好的穩(wěn)定性,‘金棚1號’ X5和X15的相關性分別為0.81和0.826;‘東圣’ X5和X15的相關性分別為0.865和0.894;‘美顏1319’ X5和X15的相關性分別為0.883和0.886,且均顯著高于對照。綜合3種番茄品種的壯苗指數(shù),X5和X15均可作為番茄秧苗壯苗的準確評判,其中X15“(總葉綠素/株高)×全株干質(zhì)量”最為可靠。
圖2為在構建番茄秧苗綜合評價指數(shù)時所用的300株番茄秧苗樣本的壯苗指數(shù)X15的分布情況??梢钥闯鏊鶚嫿ǔ龅膲衙缰笖?shù)隨著綜合評價指數(shù)的增加線性增長,相關系數(shù)0.797(2=0.635)??梢砸罁?jù)壯苗指數(shù)的大小的比較直接判定秧苗質(zhì)量。
表6 不同品種壯苗指數(shù)與綜合評價指數(shù)的相關性分析
圖2 番茄壯苗指數(shù)在綜合評價指數(shù)范圍內(nèi)的分布圖
以300株番茄秧苗樣本的綜合評價指數(shù)作為聚類劃分依據(jù),將壯苗指數(shù)X15進行等級劃分。由表7可以看出,番茄秧苗共分為3個等級,其中等級Ⅰ(壯苗指數(shù)≥0.065)為優(yōu)質(zhì)苗,等級Ⅱ(壯苗指數(shù):0.030~0.065)為合格苗,等級Ⅲ(壯苗指數(shù)≤0.030)為弱苗(幼苗或老苗)。在300樣本中,Ⅰ、Ⅱ等級苗占65%,Ⅲ等級苗占35%。通過方差分析可以看出,壯苗指數(shù)各等級間差異顯著,可以作為較好的判別指標[32]。
表7 番茄秧苗質(zhì)量等級
注:、為方差分析參數(shù)。
Note:andare parameters for variance analysis.
不同果菜類蔬菜秧苗的壯苗指數(shù)均不相同,張菊平等[33]以“(莖粗/莖高)×全株干質(zhì)量”來評價辣椒秧苗;張碩等[34]以“(莖粗/株高+地下干質(zhì)量/地上干質(zhì)量)×單株干質(zhì)量”作為黃瓜的壯苗指數(shù);高玉紅等[35]采用“(根鮮質(zhì)量/地上部鮮質(zhì)量+莖粗/株高)×全株鮮質(zhì)量”作為甜瓜的壯苗指數(shù),因此,在壯苗指數(shù)使用時需要謹慎選擇。論文以番茄秧苗為試材,創(chuàng)建了一種科學的壯苗指數(shù)建立的方法,采用模糊綜合評判法建立起番茄秧苗的評價體系,求得能全面反映番茄秧苗整體質(zhì)量的綜合評價指數(shù),通過主成分分析對秧苗形態(tài)、色素指標進行了篩選和排列組合,并將組合的壯苗指數(shù)分別與綜合評價指數(shù)做相關性分析,篩選出對番茄秧苗質(zhì)量評價較好的壯苗指數(shù),研究過程中發(fā)現(xiàn),形態(tài)、葉片葉綠素含量對于番茄秧苗的質(zhì)量均存在較大影響,能反映番茄農(nóng)藝性狀指標與生理生化指標的協(xié)調(diào)關系,充分體現(xiàn)番茄各項指標相互依存、相互制約的生長發(fā)育規(guī)律。因此,壯苗指數(shù)的構建應包含色素指標,這與前人的研究結果是不同的。因此,在實際生產(chǎn)中應以提高物質(zhì)積累為基礎,以防止幼苗徒長為前提,通過壯苗措施,提高葉綠素含量,增加總干質(zhì)量,來達到培育壯苗的目的。
本研究通過大量番茄秧苗樣本的指標測定、各類指標權重的分析以及指標隸屬函數(shù)類型的分類,構建了覆蓋面較大的綜合評判指數(shù)(0.26~0.79)。并以此為依據(jù)篩選出了相關性、穩(wěn)定性均較好的“(總葉綠素/株高)×全株干質(zhì)量”作為番茄秧苗的推薦壯苗指數(shù)。這一指數(shù)包含了株高、全株干質(zhì)量、總葉綠素等重要指標,且與綜合評判指數(shù)成線性關系,可以通過壯苗指數(shù)數(shù)值的大小直觀的判定秧苗質(zhì)量。同時,綜合形態(tài)和葉片葉綠素指標的壯苗指數(shù)充分考慮了秧苗內(nèi)在和外在的生長狀態(tài),可以更加全面的評價番茄秧苗健碩程度。最后,本研究同樣依據(jù)覆蓋面較廣的番茄秧苗綜合評價指數(shù)進一步聚類分級的結果,對所篩選出的壯苗指數(shù)進行了分級,將番茄秧苗分為3個等級,其中等級Ⅰ(壯苗指數(shù)≥0.065),等級Ⅱ(壯苗指數(shù):0.030~0.065),等級Ⅲ(壯苗指數(shù)≤0.030)。此結果可以為實際生產(chǎn)提供較方便的質(zhì)量評價依據(jù),同時也可以為其他研究者研究番茄秧苗質(zhì)量提供參考。
[1] 郭孟報,楊明金,劉斌,等. 我國蔬菜育苗產(chǎn)業(yè)現(xiàn)狀及發(fā)展動態(tài)[J]. 農(nóng)機化研究,2015,37(1):250-253.Guo Mengbao, Yang Mingjin, Liu Bin, et al. Present situation and development trend of vegetable seedling industry in China[J]. Research on Agricultural Mechanization, 2015, 37(1): 250-253. (in Chinese with English abstract)
[2] 葛曉光. 果菜壯苗指標研究的概況[J]. 中國蔬菜,1987(1):32-34. Ge Xiaoguang. Overview of research on fruit and vegetable seedling index[J]. Chinese Vegetables, 1987(1): 32-34. (in Chinese with English abstract)
[3] 賈保太,郝素芳,成京輝,等. 平菇菌糠基質(zhì)在番茄、甜椒育苗上的應用研究[J]. 蔬菜,2018(8):8-10. Jia Baotai, Hao Sufang, Cheng Jinghui, et al. Study on the application ofostreatus substrate in tomato and sweet pepper seedlings[J]. Vegetables, 2018(8): 8-10. (in Chinese with English abstract)
[4] 徐麗榮,葛長軍,閆良,等. 不同葉面施肥處理對番茄穴盤育苗的影響[J]. 湖北農(nóng)業(yè)科學,2018,57(14):97-98,104. Xu Lirong, Ge Changjun, Yan Liang, et al. Effects of different foliar application treatments on seedling rearing of tomato seedlings[J]. Hubei Agricultural Sciences, 2018, 57(14): 97-98, 104. (in Chinese with English abstract)
[5] 陸幗一,張和義. 周存田. 番茄壯苗指標的初步研究[J]. 中國蔬菜,1984 (1):13-17. Lu Guoyi, Zhang Heyi, Zhou Cuntian. Preliminary study on the index of tomato seedlings[J]. Chinese Vegetables, 1984(1): 13-17. (in Chinese with English abstract)
[6] 梁志卿,張翼,趙瑞. 澆施不同濃度矮壯素對穴盤苗生長質(zhì)量及產(chǎn)量的影響[J]. 安徽農(nóng)業(yè)科學,2018,46(22): 41-46,57. Liang Zhiqing, Zhang Yi, Zhao Rui. Effect of different concentration of high-strength on growth quality and yield of acupoint-disc seedlings[J]. Anhui Agricultural Science, 2018, 46(22): 41-46, 57. (in Chinese with English abstract)
[7] Tanaka H, Murai K, Nakanishi T, et al. Storage of plug seedlings of tomato under limited fertilisation, and growth, flowering and yield after planting[J]. Journal of Horticultural Science & Biotechnology, 2018: 1-7.
[8] Liu G, Du Q, Li J. Interactive effects of nitrate-ammonium ratios and temperatures on growth, photosynthesis, and nitrogen metabolism of tomato seedlings[J]. Scientia Horticulturae, 2017, 214: 41-50.
[9] 王正,劉明池,劉海河,等. 不同苗齡期黃瓜水肥需求規(guī)律及供液方案的研究[J].中國農(nóng)學通報,2016,32(4):68-76. Wang Zheng, Liu Mingchi, Liu Haihe, et al. Exploration of nutrient solution demand rule and irrigation schemes in different cucumber seedling stages[J].Chinese Agricultural Science Bulletin, 2016, 32(4): 68-76. (in Chinese with English abstract)
[10] 王舉才,席磊,趙曉莉. 基于模糊綜合評判的可視化葉色模型數(shù)據(jù)標準化[J]. 農(nóng)業(yè)工程學報,2011,27(11):155-159. Wang Jucai, Xi Lei, Zhao Xiaoli. Data normalization of leaf color based on fuzzy comprehensive evaluation for visualization model[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(11): 151-159. (in Chinese with English abstract)
[11] 劉全鳳,王譯萱,齊立學,等. 模糊綜合評價法評估鹽漬化潮土區(qū)溫室番茄減量施氮效益[J]. 北方園藝,2018(16):150-154. Liu Quanfeng, Wang Yixuan, Qi Lixue, et al. Evaluation of the effect of reducing nitrogen application in greenhouse tomato in saline-soil area by fuzzy comprehensive evaluation method[J]. Northern Horticulture, 2018(16): 150-154. (in Chinese with English abstract)
[12] 龔雪文,劉浩,劉東鑫,等. 基于模糊算法的溫室番茄調(diào)虧滴灌制度綜合評判[J]. 農(nóng)業(yè)工程學報,2017,33(14):144-151. Gong Xuewen, Liu Hao, Liu Dongxin, et al. Comprehensive evaluation of tomato-deficient drip irrigation system in greenhouse based on Fuzzy algorithm [J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(14): 144-151. (in Chinese with English abstract)
[13] 許翩翩,王建柱. 三種常見邊坡植物對模擬干旱環(huán)境抗旱性能的研究[J]. 草業(yè)學報,2018,27(2):36-47. Xu Pianpian, Wang Jianzhu. Drought resistance of three common slope plants determined in asimulated drought experiment[J]. Acta Prataculturae Sinica, 2018, 27(2): 36-47. (in Chinese with English abstract)
[14] Yang W, Xu K, Lian J, et al. Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model[J]. Journal of Environmental Management, 2018, 213: 440-450.
[15] 張敏娟,李昭良,焦鋒,等. 8個桑品種的植株莖葉解剖結構及與耐旱性的關聯(lián)分析[J]. 蠶業(yè)科學,2018,44(4): 516-522. Zhang Minjuan, Li Zhaoliang, Jiao Feng, et al. Anatomical structure of the stems and leaves of 8 mulberry cultivars and their relationship with drought tolerance [J]. Sericulture Science, 2018, 44(4): 516-522. (in Chinese with English abstract)
[16] 羅文敏,楊萬云,林昌虎. 三穗縣何首烏種植基地的土壤質(zhì)量綜合評價[J]. 貴州農(nóng)業(yè)科學,2014(3):182-186. Luo Wenmin, Yang Wanyun, Lin Changhu. Comprehensive assessment of polygonum planting soil quality in sansui county[J]. Guizhou Agricultural Sciences, 2014(3): 182-186. (in Chinese with English abstract)
[17] 李合生. 植物生理生化實驗原理和技術[M]. 北京:高等教育出版社,2000:123?124.
[18] 吳克寧,楊揚,呂巧靈. 模糊綜合評判在煙草生態(tài)適宜性評價中的應用[J]. 土壤通報,2007(4):631-634. Wu Kening, Yang Yang, Lü Qiaoling. The application of fuzzy comprehensive evaluation in the evaluation of the ecological suitability of tobacco[J]. Soil Bulletin, 2007(4): 631-634. (in Chinese with English abstract)
[19] 葛曉光. 現(xiàn)編蔬菜育苗大全[M]. 北京:中國農(nóng)業(yè)出版社,2004:317-321.
[20] Medasani S, Kim J, Krishnapuram R. An overview of membership function generation techniques for pattern recognition[J]. International Journal of Approximate Reasoning, 1998, 19(3/4): 391-417.
[21] 李家軍,楊莉. 對隸屬函數(shù)確定方法的進一步探討[J].貴州工業(yè)大學學報:自然科學版,2004,33(6):1-4. Li Jiajun,Yang Li. Further study on the determination of menbership function[J]. Journal of Guizhou University of Technology: Natural Science Edition, 2004, 33(6): 1-4. (in Chinese with English abstract)
[22] 白巖,史萬華,邢小軍,等. 煙草壯苗指數(shù)模型研究[J].中國農(nóng)業(yè)科學,2014,47(6):1086-1098. Bai Yan, Shi Wanhua, Xing Xiaojun, et al. Study on the model of tobacco seedling index [J]. China Agricultural Science, 2014, 47(6): 1086-1098. (in Chinese with English abstract)
[23] 申寶營,李毅念,趙三琴,等. 暗期補光對黃瓜幼苗形態(tài)調(diào)節(jié)效果及綜合評價[J]. 農(nóng)業(yè)工程學報,2014,30(22):201-208. Shen Baoying, Li Yinian, Zhao Sanqin, et al. Effect of dark period lighting regulation on cucumber seedling morphology and comprehensive evaluation analysis and comprehensive evaluation[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(22): 201-208. (in Chinese with English abstract)
[24] 王洪云,陳愛國,趙國明,等. 云南大理州烤煙生態(tài)適宜性評價[J]. 中國農(nóng)學通報,2012,28(28):280-285.Wang Hongyun, Chen Aiguo, Zhao Guoming, et al. Evaluation of ecological suitability of flue-cured tobacco in Yunnan Dali Prefecture [J]. Chinese Agricultural Science Bulletin, 2012, 28(28): 280-285. (in Chinese with English abstract)
[25] 張久權,張教俠,劉傳峰,等. 山東烤煙生態(tài)適應性綜合評價[J]. 中國煙草科學,2008(5):11-17,71. Zhang Jiuquan, Zhang Jiaoxia, Liu Chuanfeng, et al. Comprehensive evaluation of ecological adaptability of flue-cured tobacco in Shandong[J]. China Tobacco Science, 2008(5): 11-17, 71. (in Chinese with English abstract)
[26] 黃淑華,徐福利,王渭玲,等. 丹參壯苗指數(shù)及其模擬模型[J]. 應用生態(tài)學報,2012,23(10):2779-2785. Huang Shuhua, Xu Fuli, Wang Weiling, et al. The seedling index of Salvia miltiorrhiza and its simulation model [J]. Journal of Applied Ecology, 2012, 23(10): 2779-2785. (in Chinese with English abstract)
[27] Tsapanos N, Tefas A, Nikolaidis N, et al. Efficient mapreduce kernel k-means for big data clustering[J]. Automatica, 2016, 43(2): 1-5.
[28] Guo L, Abbosh A. Stroke localization and classification using microwave tomography with k-means clustering and support vector machine[J]. Bioelectromagnetics, 2018, 39(4): 312-324.
[29] Moore B C. Principal component analysis in linear systems: Controllability, observability, and model reduction[J]. IEEE Transactions on Automatic Control, 2003, 26(1): 17-32.
[30] Dem?ar U, Harris P, Brunsdon C, et al. Principal component analysis on spatial data: An overview[J]. Annals of the Association of American Geographers, 2013, 103(1): 106-128.
[31] 張世祥,王海明. 番茄壯苗指數(shù)與影響因素通徑分析[J].北方園藝,1992(1):17-20. Zhang Shixiang, Wang Haiming. Path analysis of tomato seedling index and influencing factors[J]. Northern Horticulture, 1992(1): 17-20. (in Chinese with English abstract)
[32] 向麗,韓建萍,陳士林. 人工栽培川貝母種苗質(zhì)量標準研究[J]. 環(huán)球中醫(yī)藥,2011,4(2):91-94. Xiang Li, Han Jianping, Chen Shilin. Study on the quality of purposive cultivation ofcirrhosa seedling[J]. Global Traditiongal Chinese Medicine, 2011, 4(2): 91-94. (in Chinese with English abstract)
[33] 張菊平,張興志. 辣椒壯苗指數(shù)與苗期性狀的關系分析[J].河南農(nóng)業(yè)大學學報,1999(S1):120-122. Zhang Juping, Zhang Xingzhi. The relationship between the seedling index and seedling traits of capsicum [J]. Journal of Henan Agricultural University, 1999(S1): 120-122. (in Chinese with English abstract)
[34] 張碩,余宏軍,蔣衛(wèi)杰. 發(fā)酵玉米芯或甘蔗渣基質(zhì)的黃瓜育苗效果[J]. 農(nóng)業(yè)工程學報,2015,31(11):236-242. Zhang Shuo, Yu Hongjun, Jiang Weijie. Effect of fermented maize cob or bagasse substrate on cucumber seedling breeding[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(11): 236-242. (in Chinese with English abstract)
[35] 高玉紅,閆生輝,鄧黎黎. 逆境脅迫對甜瓜幼苗生長的影響及綜合抗逆鑒定指標的篩選[J]. 江蘇農(nóng)業(yè)科學,2018,46(15):116-118. Gao Yuhong, Yan Shenghui, Deng Lili. Effect of stress on the growth of muskmelon seedlings and selection of comprehensive anti-inverse identification index[J]. Jiangsu Agricultural Science, 2018, 46(15): 116-118. (in Chinese with English abstract)
Selection of tomato seedling index based on comprehensive morphology and leaf chlorophyll content
Gong Binbin1, Wang Ning1, Zhang Tiejun2, Wu Xiaolei1, Lü Guiyun1, Chu Xinpei1, Gao Hongbo1※
(1.071001,2.071001,)
In this study, we aimed to establish an optimal index model of tomato seedlings to improve the accuracy of seedlings evaluation. Based on the determination of eleven individual indicators such as plant height, stem circumference, root-shoot ratio (Fresh), plant fresh weight, root-shoot ratio (Dry), plant dry weight, chlorophyll a, chlorophyll b, total chlorophyll, carotenoid and SPAD of about 300 tomato seedlings with three leaves, according to the seedling standard, the membership function formula of each index was established and the single factor evaluation matrix was calculated. The weight coefficient matrix was calculated according to multiple linear regression. Finally, the fuzzy comprehensive evaluation method was used to multiply the single factor evaluation matrix and the weight coefficient matrix to calculate the comprehensive evaluation matrix and establish a comprehensive evaluation index of tomato seedlings. This index can stably and accurately evaluate tomato seedlings, but the calculation was relatively complicated. Therefore, a simple and effective seedling model was needed instead of the comprehensive evaluation index. Then the principal component analysis was used to screen the indicators and combine them into index model of tomato seedlings. After that, the suitable model was selected through the correlation analysis between the comprehensive evaluation index and seedling index model. Finally, the optimal model was selected based on the verification of suitable model using industrialized nursery seedlings of three different tomato varieties. The results showed that the weight coefficients of each indicator such as plant height, stem circumference, root-shoot ratio (Fresh), plant fresh weight, root-shoot ratio (Dry), plant dry weight, chlorophyll a, chlorophyll b, total chlorophyll, carotenoid and SPAD of tomato seedlings were 0.180, 0.085, 0.098, 0.076, 0.103, 0.078, 0.070, 0.070, 0.070, 0.072, and 0.097, respectively. And the index was divided into three subordinate functions: parabola, positive S and straight line. The parabola included plant height, the positive S included stem circumference, plant fresh weight and plant dry weight, and the straight line included root-shoot ratio (Fresh), root-shoot ratio (Dry), chlorophyll a, chlorophyll b, total chlorophyll, carotenoid and SPAD. The comprehensive evaluation index of tomato seedlings was calculated to be 0.26-0.79, which could comprehensively summarize the overall quality of seedlings as well as objectively and accurately evaluate the robustness degree of seedlings. The eleven individual indicators of seedlings could be divided into three principal components, including morphological indicators, pigment indicators and plant height. The morphological indicators included stem circumference, root-shoot ratio (Fresh), plant fresh weight, root-shoot ratio (Dry) and plant dry weight. The pigment indicators included chlorophyll a, chlorophyll b, total chlorophyll, carotenoid and SPAD. Plant height was divided into one component. Twenty-five seedlings index models were combined using one indicator from each principal component and taking (stem circumference/plant height) × whole plant dry weight and (stem circumference/plant height + root dry weight/dry weight of the ground) × whole plant dry weight as the control group, furthermore, four suitable models such as (chlorophyll a/plant height) × whole plant dry weight, (total chlorophyll / plant height) × whole plant dry weight, (carotenoid/plant height) × whole plant dry weight and (SPAD/plant height) × whole plant dry weight were selected due to the high correlation and representativeness. According to the model verification results of three different tomato varieties, (chlorophyll a / plant height) × whole plant dry weight and (total chlorophyll/plant height) × whole plant dry weight were identified as the optimal models to evaluate the quality of tomato seedlings because of high correlation with the comprehensive evaluation index, good stability and representativeness. This result showed that the fuzzy comprehensive evaluation was good for assessment of tomato seedlings. According to the comprehensive evaluation index and cluster analysis of the selected seedling index model of tomato seedlings, the quality of tomato seedlings was divided into three grades, and the range of seedling index of different grades was given. The research can provide theoretical basis for tomato seedling production and also provide an optimized reference for evaluating quality of other vegetable seedlings.
chlorophyll; morphology; tomato; seedling index; fuzzy comprehensive evaluation; principal component analysis; correlation analysis
2018-10-15
2019-02-12
河北省重點研發(fā)計劃(農(nóng)業(yè)關鍵共性技術攻關專項)(18226907D)
宮彬彬,講師,從事設施工程與無土栽培配套栽培技術研究。Email:yygbb@hebau.edu.cn
高洪波,教授,博士生導師,主要從事設施蔬菜與無土栽培研究。Email:hongbogao@hebau.edu.cn
10.11975/j.issn.1002-6819.2019.08.028
S641.2
A
1002-6819(2019)-08-0237-08
宮彬彬,王 寧,章鐵軍,吳曉蕾,呂桂云,褚新培,高洪波.綜合形態(tài)與葉片葉綠素含量的番茄壯苗指數(shù)篩選[J]. 農(nóng)業(yè)工程學報,2019,35(8):237-244. doi:10.11975/j.issn.1002-6819.2019.08.028 http://www.tcsae.org
Gong Binbin, Wang Ning, Zhang Tiejun, Wu Xiaolei, Lü Guiyun, Chu Xinpei, Gao Hongbo. Selection of tomato seedling index based on comprehensive morphology and leaf chlorophyll content[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(8): 237-244. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2019.08.028 http://www.tcsae.org