熊淑萍,高明,張志勇,秦步壇,徐賽俊,付新露,王小純,馬新明
基于GIS的河南省小麥產(chǎn)量及產(chǎn)量構(gòu)成要素時空差異分析
1河南農(nóng)業(yè)大學(xué)農(nóng)學(xué)院/教育部作物生長發(fā)育調(diào)控重點實驗室,鄭州 450046;2河南農(nóng)業(yè)大學(xué)生命科學(xué)學(xué)院,鄭州 450002
【】分析河南省不同產(chǎn)區(qū)小麥籽粒產(chǎn)量和產(chǎn)量構(gòu)成要素的時空差異,明確不同產(chǎn)區(qū)進(jìn)一步提高小麥籽粒產(chǎn)量的主攻方向。選用河南省小麥固定監(jiān)測站點實地監(jiān)測數(shù)據(jù),利用地理信息系統(tǒng)(GIS)選擇最優(yōu)模型,繪制2017—2020年河南省4個小麥生產(chǎn)區(qū)產(chǎn)量與產(chǎn)量構(gòu)成要素空間分布圖,分析產(chǎn)量和產(chǎn)量構(gòu)成要素在不同小麥產(chǎn)區(qū)的差異及其相互關(guān)系。小麥產(chǎn)量及產(chǎn)量構(gòu)成要素在不同產(chǎn)區(qū)間存在差異,其中,產(chǎn)量和穗數(shù)均表現(xiàn)為豫北和豫中產(chǎn)區(qū)顯著高于豫南和豫西產(chǎn)區(qū),以豫北產(chǎn)區(qū)最高,豫西產(chǎn)區(qū)最低。而穗粒數(shù)表現(xiàn)為豫中、豫南和豫北產(chǎn)區(qū)顯著高于豫西產(chǎn)區(qū),豫中產(chǎn)區(qū)最高,豫西產(chǎn)區(qū)最低。千粒重表現(xiàn)為豫北產(chǎn)區(qū)最高,豫南產(chǎn)區(qū)最低。小麥產(chǎn)量、穗數(shù)、穗粒數(shù)、千粒重多在豫中和豫南交匯處(漯河、周口、駐馬店等地)表現(xiàn)較高且在年際間穩(wěn)定。相關(guān)分析表明,不同小麥產(chǎn)區(qū)產(chǎn)量構(gòu)成三要素與產(chǎn)量的關(guān)系不一致。其中,豫北和豫中產(chǎn)區(qū)以穗數(shù)和穗粒數(shù)與產(chǎn)量的相關(guān)性最大,而豫西和豫南產(chǎn)區(qū)產(chǎn)量構(gòu)成三要素與產(chǎn)量的相關(guān)性則表現(xiàn)為穗數(shù)最高,千粒重次之,穗粒數(shù)最低。通徑分析進(jìn)一步表明,4個小麥產(chǎn)區(qū)間產(chǎn)量構(gòu)成要素對產(chǎn)量的貢獻(xiàn)不同,其中,豫北產(chǎn)區(qū)以穗數(shù)、穗粒數(shù)對產(chǎn)量貢獻(xiàn)最大,直接通徑系數(shù)均為0.67;豫中和豫南產(chǎn)區(qū)產(chǎn)量構(gòu)成三要素對產(chǎn)量的貢獻(xiàn)依次為穗數(shù)>穗粒數(shù)>千粒重;而豫西產(chǎn)區(qū)則為穗數(shù)最大,千粒重次之,穗粒數(shù)最低,直接通徑系數(shù)分別為0.69、0.45、0.39。同時,間接通徑系數(shù)顯示,豫北、豫中、豫南產(chǎn)區(qū)提高千粒重的增產(chǎn)效果優(yōu)于提高穗粒數(shù),而豫西產(chǎn)區(qū)則為提高穗粒數(shù)更優(yōu)。河南省小麥產(chǎn)量及產(chǎn)量構(gòu)成要素在不同小麥產(chǎn)間區(qū)及年際間存在較大差距,同時,不同小麥產(chǎn)區(qū)小麥產(chǎn)量構(gòu)成三要素對產(chǎn)量的貢獻(xiàn)不同,因此,河南省在進(jìn)一步挖掘小麥生產(chǎn)潛力方面,應(yīng)分區(qū)域、分年型精準(zhǔn)分類進(jìn)行。就本試驗條件而言,河南省各小麥產(chǎn)區(qū)在穩(wěn)定穗數(shù)的基礎(chǔ)上,豫北、豫中、豫南產(chǎn)區(qū)應(yīng)著力進(jìn)一步挖掘千粒重的潛力,而豫西產(chǎn)區(qū)提高穗粒數(shù)的增產(chǎn)效果優(yōu)于千粒重。
小麥產(chǎn)量;產(chǎn)量構(gòu)成要素;小麥產(chǎn)區(qū);時空分布
【研究意義】小麥?zhǔn)俏覈蠹Z食作物之一[1],在國家糧食安全中居重要地位,河南省位于黃淮海麥區(qū)腹地,是全國小麥生產(chǎn)大省[2],其產(chǎn)量高低與國家糧食安全關(guān)系密切[3]。河南省地域廣闊,各地栽培措施和氣候條件等有所不同,導(dǎo)致產(chǎn)量差異較大[4-5],豐產(chǎn)穩(wěn)產(chǎn)存在不確定性因素,因此,準(zhǔn)確掌握產(chǎn)量與產(chǎn)量構(gòu)成要素時空分布特征,以及產(chǎn)量與產(chǎn)量構(gòu)成要素間的關(guān)系,對河南省小麥的區(qū)域化布局、標(biāo)準(zhǔn)化生產(chǎn)和進(jìn)一步挖掘區(qū)域生產(chǎn)潛力有著重要意義?!厩叭搜芯窟M(jìn)展】信息技術(shù)與農(nóng)業(yè)科學(xué)的快速發(fā)展與交叉融合,形成了農(nóng)業(yè)信息技術(shù)[6],地理信息系統(tǒng)(GIS)是其中重要的信息處理技術(shù)之一,不斷被應(yīng)用到農(nóng)業(yè)生產(chǎn)的空間分布和變異研究中,為農(nóng)業(yè)生產(chǎn)發(fā)展評價與決策提供了重要平臺[7-10]。近年來GIS已廣泛應(yīng)用到作物產(chǎn)量空間分布變化[8, 11]、作物區(qū)域生產(chǎn)潛力的計算[10-14]、作物品質(zhì)空間分布特征[15-19]等研究中。小麥經(jīng)濟(jì)產(chǎn)量的形成受到外界環(huán)境、人為因素和基因型等多方面的影響,成因較為復(fù)雜,前人經(jīng)過多年研究表明有效穗數(shù)、穗粒數(shù)、千粒重在籽粒產(chǎn)量形成過程中相互作用,相互影響最終形成小麥經(jīng)濟(jì)產(chǎn)量[20-22],田紀(jì)春等[23]研究表明,產(chǎn)量構(gòu)成要素對籽粒產(chǎn)量的貢獻(xiàn)從大到小依次為穗數(shù)、穗粒數(shù)、千粒重。金艷等[24]的研究結(jié)果則顯示產(chǎn)量構(gòu)成要素對籽粒產(chǎn)量的貢獻(xiàn)從大到小依次為穗粒數(shù)、千粒重、穗數(shù)。馮素偉等[25]的研究表明,產(chǎn)量構(gòu)成要素對籽粒產(chǎn)量的貢獻(xiàn)從大到小依次為穗數(shù)、千粒重、穗粒數(shù)。而楊程等[26]的研究結(jié)果顯示,產(chǎn)量構(gòu)成要素對籽粒產(chǎn)量的貢獻(xiàn)從大到小依次為穗數(shù)、穗粒數(shù)、千粒重?!颈狙芯壳腥朦c】關(guān)于河南省小麥產(chǎn)量構(gòu)成要素與籽粒產(chǎn)量關(guān)系的研究較多,但結(jié)果不盡相同,而且,這些研究多基于某一產(chǎn)區(qū),很少在全省層面上針對不同小麥產(chǎn)區(qū)具體情況進(jìn)行分析?!緮M解決的關(guān)鍵問題】本研究采用2017—2020年河南省不同產(chǎn)區(qū)小麥測產(chǎn)數(shù)據(jù),利用空間插值等方法,具體分析不同年度間,豫北、豫中、豫西、豫南四大小麥產(chǎn)區(qū)之間小麥籽粒產(chǎn)量及產(chǎn)量構(gòu)成要素差異。旨在揭示不同小麥產(chǎn)區(qū)小麥產(chǎn)量構(gòu)成三要素對產(chǎn)量貢獻(xiàn)的差異,為不同產(chǎn)區(qū)進(jìn)一步提高小麥產(chǎn)量的主攻方向提供理論參考。
以河南省小麥產(chǎn)區(qū)為研究對象,依據(jù)胡廷積等[27]的劃分方法,將河南省小麥產(chǎn)區(qū)劃分為豫北灌區(qū)、豫中補灌區(qū)、豫西旱作區(qū)、豫南雨養(yǎng)區(qū)4個種植區(qū)。根據(jù)麥播面積、縣區(qū)分布等情況分別在4個種植區(qū)選擇有代表性的監(jiān)測站點計84個,各種植區(qū)概況及監(jiān)測站點分布情況見表1和圖1。監(jiān)測時間為2017—2020年,小麥產(chǎn)區(qū)小麥生長季雨熱狀況見表2。主要監(jiān)測指標(biāo)為各產(chǎn)區(qū)小麥的籽粒產(chǎn)量和產(chǎn)量構(gòu)成三要素(單位面積穗數(shù)、穗粒數(shù)和千粒重),其中,籽粒產(chǎn)量采取5點取樣法,每監(jiān)測點分別收獲5個1 m2,折算單位面積籽粒產(chǎn)量,產(chǎn)量構(gòu)成三要素采取一米雙行法進(jìn)行考種,每監(jiān)測點重復(fù)3次。
采用Microsoft Excel軟件進(jìn)行數(shù)據(jù)處理及繪制產(chǎn)量及產(chǎn)量構(gòu)成要素柱形圖。
采用Spss24.0軟件進(jìn)行方差分析(analysis of variance)、偏相關(guān)分析(analysis of partial correlation)和通徑分析(path analysis)[28-29]。其中,利用方差分析明確不同產(chǎn)區(qū)間產(chǎn)量及產(chǎn)量構(gòu)成要素的差異顯著性,利用偏相關(guān)分析明確產(chǎn)量構(gòu)成要素與產(chǎn)量的關(guān)系,利用通徑分析明確產(chǎn)量構(gòu)成要素對產(chǎn)量的貢獻(xiàn)。
采用Arc GIS 10.2地理統(tǒng)計分析模塊的趨勢分析法,繪制河南省籽粒產(chǎn)量及產(chǎn)量構(gòu)成要素全局趨勢圖,分析河南省小麥產(chǎn)量及產(chǎn)量構(gòu)成要素經(jīng)緯向的總體趨勢。
圖1 84個監(jiān)測點分布情況
表1 研究區(qū)域概況及監(jiān)測點分布情況
表2 河南省不同小麥產(chǎn)區(qū)小麥生育期降水量與積溫情況
采用Arc Gis10.2地理統(tǒng)計分析模塊的克里金插值法(kriging)進(jìn)行插值分析[15],插值分析前對數(shù)據(jù)進(jìn)行檢驗,在滿足插值分析基本條件的情況下[30-31],選用簡單克里金插值(simple kriging)、普通克里金(ordinary kriging)、泛克里金插值法(universal kriging)建立預(yù)測模型,利用交叉檢驗的方法,以標(biāo)準(zhǔn)平均值(mean standardized)接近0、均方根(root mean square)最小、平均標(biāo)準(zhǔn)誤差(standard error of mean)接近1為標(biāo)準(zhǔn),確定最優(yōu)模型,分別繪制2017—2020年籽粒產(chǎn)量及產(chǎn)量構(gòu)成要素空間分布圖,分析小麥籽粒產(chǎn)量與產(chǎn)量構(gòu)成要素空間分布規(guī)律。
2.1.1 籽粒產(chǎn)量 圖2顯示,2017、2019和2020年籽粒產(chǎn)量為豫北較高豫西較低,2018年為豫南較高,豫西較低。產(chǎn)區(qū)平均籽粒產(chǎn)量表現(xiàn)為豫北>豫中>豫南>豫西,豫北產(chǎn)區(qū)平均籽粒產(chǎn)量分別比豫中、豫西、豫南產(chǎn)區(qū)高出4.72%、28.68%、10.29%。2017—2020年平均籽粒產(chǎn)量由高到低依次為2019>2020>2017>2018,2019年平均籽粒產(chǎn)量與2017、2018、2020年比分別高出5.89%、19.21%、5.13%。
2.1.2 穗數(shù) 圖3顯示,2017、2019和2020年穗數(shù)多為豫北和豫中產(chǎn)區(qū)較高,豫西較低。2018年穗數(shù)與其他年份相比明顯下降,該年豫南產(chǎn)區(qū)穗數(shù)最高,豫西產(chǎn)區(qū)穗數(shù)最低。平均穗數(shù)表現(xiàn)為豫北>豫中>豫南>豫西,豫北產(chǎn)區(qū)平均穗數(shù)分別比豫中、豫西、豫南產(chǎn)區(qū)高出1.60%、18.87%、6.53%。
不同字母表示(P=0.05)差異顯著。下同
圖3 河南省不同小麥產(chǎn)區(qū)2017—2020年穗數(shù)差異情況
2.1.3 穗粒數(shù) 由圖4可知,2017、2019和2020年穗粒數(shù)多為豫中和豫南產(chǎn)區(qū)較高,豫西產(chǎn)區(qū)較低,2018年穗粒數(shù)為豫南產(chǎn)區(qū)最高,豫北產(chǎn)區(qū)穗數(shù)最低。產(chǎn)區(qū)平均穗粒數(shù)表現(xiàn)為豫中>豫南>豫北>豫西,豫中產(chǎn)區(qū)平均穗粒數(shù)分別比豫北、豫西、豫南產(chǎn)區(qū)高出2.49%、8.68%、0.55%。
2.1.4 千粒重 圖5顯示,2017—2020年千粒重多為豫北和豫中產(chǎn)區(qū)較高,豫南和豫西產(chǎn)區(qū)較低,產(chǎn)區(qū)平均千粒重表現(xiàn)為豫北>豫中>豫西>豫南,豫北產(chǎn)區(qū)平均千粒重分別比豫中、豫西、豫南產(chǎn)區(qū)高出1.87%、5.10%、5.22%。
圖4 河南省不同小麥產(chǎn)區(qū)2017—2020年穗粒數(shù)差異情況
2.2.1 籽粒產(chǎn)量及產(chǎn)量構(gòu)成要素空間分布總體趨勢 由圖6可知,小麥籽粒產(chǎn)量在河南省北部、中部高,西部低,由西向東先增加后減少,由北向南逐漸降低;穗數(shù)呈中部北部高,西部南部低,自西向東先增加后減少,由北向南逐漸降低;穗粒數(shù)由西向東先增加后減少,由北向南先降低后增加;千粒重中北部高西部低,由西向東先增加后減少,由北向南逐漸降低。
圖5 河南省不同小麥產(chǎn)區(qū)2017—2020年千粒重差異情況
圖中黑色柱體表示監(jiān)測點量的高低,綠色曲線為徑向的變化趨勢,藍(lán)色為緯向
2.2.2 籽粒產(chǎn)量 圖7可知,2017、2018與2019年河南省小麥籽粒產(chǎn)量整體表現(xiàn)為豫北、豫中籽粒產(chǎn)量高于豫南與豫西,豫中和豫南交匯處(漯河、周口、駐馬店三市交界處)4年籽粒產(chǎn)量均較高。2018年全省籽粒產(chǎn)量普遍降低,該年籽粒產(chǎn)量呈多態(tài)分布,與其他年份相比豫北籽粒產(chǎn)量明顯下降,但豫西的南部、豫南的北部則較其他年份有明顯的增加,該年最高產(chǎn)量在漯河、周口、駐馬店三地交界處。
圖7 2017—2020產(chǎn)量空間分布情況
2.2.3 穗數(shù) 由圖8可知,2018—2020年穗數(shù)分布情況表現(xiàn)為豫北、豫中和豫南的北部地區(qū)穗數(shù)較高,豫西和豫南的淮河以南地區(qū)則較低。豫中和豫南交匯地,漯河、周口、駐馬店三地交界處4年穗數(shù)均較高。2017年穗數(shù)分布情況為東北、西南高,豫南的南陽盆地穗數(shù)明顯高于其他年份,穗數(shù)最高點在鶴壁、新鄉(xiāng)兩地交界處,而豫西和豫南淮河南部地區(qū)穗數(shù)則低于其他區(qū)域。
2.2.4 穗粒數(shù) 由圖9可知,2017—2020年穗粒數(shù)年際間變化差異較大,豫中和豫南及其交界處多數(shù)年份較高。2017年穗粒數(shù)為中部,北部高,最高點在新鄉(xiāng)、焦作、鄭州三市交界處,2018年豫北和豫中產(chǎn)區(qū)穗粒數(shù)較2017年下降明顯,豫南產(chǎn)區(qū)穗粒數(shù)較高。2019年豫西產(chǎn)區(qū)穗粒數(shù)較低,其他產(chǎn)區(qū)穗粒數(shù)差異較小,高值區(qū)主要集中在豫中產(chǎn)區(qū)以及豫中和豫南產(chǎn)區(qū)交界處。2020年穗粒數(shù)呈南北兩頭高的趨勢,黃河南岸形成低值帶,貫穿東西,穗粒數(shù)最高點集中在淮河流域南北兩側(cè)。
圖8 2017—2020穗數(shù)空間分布情況
圖9 2017—2020年穗粒數(shù)空間分布情況
2.2.5 千粒重 由圖10可知,2017—2020年千粒重多為豫北和豫中產(chǎn)區(qū)高于其他產(chǎn)區(qū)。2017年除豫南的淮河南部外,其他區(qū)域高值與低值錯落分布,無明顯規(guī)律。2018年千粒重呈從北向南逐漸降低的趨勢,高點在豫北的焦作、滑縣,豫中的商丘東部等地。2019、2020年千粒重分布情況相似,都表現(xiàn)為豫北、豫中過渡帶以及豫中、豫南過渡帶高,西南低的趨勢。豫北的東部(內(nèi)黃、滑縣、原陽等)穗粒數(shù)兩年均為高點。
圖10 2017—2020千粒重空間分布
2.3.1 產(chǎn)量構(gòu)成要素與籽粒產(chǎn)量的相關(guān)性 偏相關(guān)分析表明(圖11),豫北產(chǎn)區(qū)產(chǎn)量構(gòu)成要素與籽粒產(chǎn)量的相關(guān)性從高到低依次穗數(shù)=穗粒數(shù)>千粒重,豫中產(chǎn)區(qū)為穗數(shù)>穗粒數(shù)>千粒重,豫西和豫南產(chǎn)區(qū)為穗數(shù)>千粒重>穗粒數(shù),相關(guān)系數(shù)均為正值,不同產(chǎn)區(qū)間穗數(shù)與籽粒產(chǎn)量的相關(guān)性最高。
另外,產(chǎn)量構(gòu)成要素之間,豫中產(chǎn)區(qū)穗數(shù)與千粒重呈顯著正相關(guān),豫南產(chǎn)區(qū)穗數(shù)與穗粒數(shù)呈極顯著負(fù)相關(guān),豫西產(chǎn)區(qū)穗粒數(shù)與千粒重呈顯著負(fù)相關(guān)。
2.3.2 產(chǎn)量構(gòu)成要素對籽粒產(chǎn)量的貢獻(xiàn) 表3顯示,直接通徑系數(shù)從大到小依次為:豫北產(chǎn)區(qū)為穗數(shù)=穗粒數(shù)>千粒重,豫中和豫南產(chǎn)區(qū)為穗數(shù)>穗粒數(shù)>千粒重,豫西產(chǎn)區(qū)則為穗數(shù)>千粒重>穗粒數(shù)。不同產(chǎn)區(qū)產(chǎn)量構(gòu)成要素對籽粒產(chǎn)量貢獻(xiàn)均為穗數(shù)最大。間接通徑系數(shù)可以反應(yīng)產(chǎn)量構(gòu)成要素間的關(guān)系,其中豫北產(chǎn)區(qū)穗數(shù)通過穗粒數(shù)與千粒重對籽粒產(chǎn)量的間接通徑系數(shù)分別為-0.13和0.07。穗粒數(shù)通過穗數(shù)與千粒重對籽粒產(chǎn)量的間接通徑系數(shù)分別為-0.13和-0.06。千粒重通過穗數(shù)與穗粒數(shù)對籽粒產(chǎn)量的間接通徑系數(shù)分別為0.13和-0.1。穗粒數(shù)通過其他產(chǎn)量構(gòu)成要素對籽粒產(chǎn)量的間接作用均為負(fù)值,而千粒重則優(yōu)于穗數(shù),即豫北產(chǎn)區(qū)在穩(wěn)定穗數(shù)的前提下,提高千粒重的增產(chǎn)效果好于提高穗粒數(shù)。豫南產(chǎn)區(qū)情況與豫北產(chǎn)區(qū)相似。
?表示相關(guān)性,其上數(shù)字為相關(guān)系數(shù),*和**表示0.05、0.01水平上顯著相關(guān)
表3 不同產(chǎn)區(qū)籽粒產(chǎn)量與產(chǎn)量構(gòu)成要素通徑分析
自變量一列中X1、X2、X3分別為穗數(shù)、穗粒數(shù)、千粒重;直接通徑系數(shù)表示自變量對籽粒產(chǎn)量的直接作用,數(shù)值越大作用越大;間接通徑系數(shù)表示自變量通過其他自變量對籽粒產(chǎn)量的間接影響
X1, is spike number, X2is kernels per ear, and X3is 1000-grains weight. the direct path coefficient represents the direct effect of the independent variable on the grain yield, the larger the value, the greater the effect; the indirect path coefficient represents the independent variable through the indirect effect of independent variables on grain yield
豫中產(chǎn)區(qū)的間接通徑系數(shù)均為正值,其中千粒重通過穗數(shù)對籽粒產(chǎn)量的間接作用最大(0.09),穗數(shù)與穗粒數(shù)間的間接通經(jīng)系數(shù)最?。?),說明豫中產(chǎn)區(qū)產(chǎn)量構(gòu)成要素間較為協(xié)調(diào),在穩(wěn)定穗數(shù)的前提下,提高千粒重的增產(chǎn)效果最好。
豫西產(chǎn)區(qū)穗數(shù)通過穗粒數(shù)與千粒重對籽粒產(chǎn)量的間接通徑系數(shù)分別為0.15和-0.01,穗粒數(shù)通過穗數(shù)與千粒重對籽粒產(chǎn)量的間接通徑系數(shù)分別為0.28和-0.15,千粒重通過穗數(shù)與穗粒數(shù)對籽粒產(chǎn)量的間接通徑系數(shù)分別為-0.01和-0.12,穗粒數(shù)通過穗數(shù)對籽粒產(chǎn)量的間接影響最大(0.28),同時穗數(shù)通過穗粒數(shù)對籽粒產(chǎn)量的間接影響也較高(0.15),說明豫西產(chǎn)區(qū)產(chǎn)量構(gòu)成要素間競爭激烈,尤其是穗粒數(shù)與千粒重間,但提高穗數(shù)的同時提高穗粒數(shù)不失為一種較好增產(chǎn)途徑。
河南省地域廣闊,地區(qū)間氣候差異明顯,不同產(chǎn)區(qū)間產(chǎn)量差異較大[32],李巧云等[33]2007—2008年在河南省北緯36°到32°的不同生態(tài)類型區(qū)研究表明,河南省小麥產(chǎn)量隨緯度降低呈現(xiàn)先升高后降低的趨勢,馬新明等[34]研究表明,豫北和豫中地區(qū)小麥產(chǎn)量及生產(chǎn)潛力較大,豫東和豫東南地區(qū)居中,豫西和豫西南地區(qū)較低。本研究關(guān)于河南省產(chǎn)量的變化趨勢與前人研究結(jié)果較為一致,并明確了河南省不同小麥產(chǎn)區(qū)間產(chǎn)量和產(chǎn)量構(gòu)成要素的差距,指出豫中南區(qū)域的漯河、周口、駐馬店三市交界處為河南省小麥高產(chǎn)穩(wěn)產(chǎn)的區(qū)域。
本研究進(jìn)一步表明,河南省小麥產(chǎn)量構(gòu)成要素在不同小麥產(chǎn)區(qū)存在較大差異。豫北產(chǎn)區(qū)穗數(shù)和粒重均高于其他產(chǎn)區(qū),但穗粒數(shù)卻低于豫中和豫南產(chǎn)區(qū);豫中產(chǎn)區(qū)的穗粒數(shù)居河南省4個小麥產(chǎn)區(qū)之首,且穗數(shù)和粒重亦高于豫西和豫南兩麥區(qū);豫南麥區(qū)穗粒數(shù)僅次于豫中麥區(qū),但穗數(shù)和粒重較低,尤其是粒重在四大小麥產(chǎn)區(qū)最低。豫西產(chǎn)區(qū)除粒重略高于豫南產(chǎn)區(qū)外,產(chǎn)量及穗數(shù)、穗粒數(shù)在4個小麥產(chǎn)區(qū)中均顯著低于其他產(chǎn)區(qū)。由此可以看出,除豫西產(chǎn)區(qū)外,河南省各小麥產(chǎn)區(qū)在產(chǎn)量構(gòu)成要素上均存在一定的優(yōu)勢和劣勢,關(guān)于造成差異的原因,前人已進(jìn)行了詳盡的研究,其中,小麥遮蔭試驗表明遮蔭導(dǎo)致穗粒數(shù)、千粒重與籽粒產(chǎn)量出現(xiàn)不同程度的下降[35-36];Bruckner等[37]研究表明灌漿期日均高溫每提高1℃,灌漿期總天數(shù)將縮短3.1 d,粒重將降低2.8 mg;王萬里等[38]研究表明灌漿前期經(jīng)受干旱處理后小麥籽粒產(chǎn)量減產(chǎn)較多,即在生育期內(nèi),冬小麥產(chǎn)量受氣候條件波動的影響。同時也有大量研究表明,土壤狀況與栽培技術(shù)措施對產(chǎn)量與產(chǎn)量構(gòu)成要素有顯著影響[39-41]。因此,針對產(chǎn)量及產(chǎn)量構(gòu)成因素在不同小麥產(chǎn)區(qū)的差距,揭示造成這種差距的可能原因,如自然條件、品種、栽培技術(shù)等,協(xié)調(diào)相應(yīng)產(chǎn)區(qū)小麥產(chǎn)量構(gòu)成因素,優(yōu)化河南省小麥區(qū)域布局具有重要意義,需進(jìn)一步深入研究。
小麥的單位面積產(chǎn)量由單位面積穗數(shù)、每穗粒數(shù)和粒重構(gòu)成[42]。前人研究表明,在一定的范圍內(nèi),產(chǎn)量隨著單位面積穗數(shù)的增加而提高,有效穗數(shù)在產(chǎn)量構(gòu)成要素中占主導(dǎo)地位[43-44],充足的穗數(shù)是高產(chǎn)的基礎(chǔ)。王紹中等[45]對國家黃淮南片麥區(qū)及河南省小麥區(qū)域試驗結(jié)果進(jìn)行分析,結(jié)果顯示產(chǎn)量在9 000 kg·hm-2以上且穗數(shù)在較高水平時,千粒重對產(chǎn)量起主導(dǎo)作用。而周延輝等[46]的研究則認(rèn)為產(chǎn)量構(gòu)成三要素對產(chǎn)量的貢獻(xiàn)從大到小依次為穗數(shù)、穗粒數(shù)、千粒重。本研究對河南省小麥產(chǎn)量構(gòu)成要素與產(chǎn)量的關(guān)系分種植區(qū)域進(jìn)行分析發(fā)現(xiàn),河南省不同小麥產(chǎn)區(qū)也均以穗數(shù)對產(chǎn)量的貢獻(xiàn)最大,這與前人研究結(jié)果一致,但千粒重和穗粒數(shù)對產(chǎn)量的貢獻(xiàn)在河南省各小麥產(chǎn)區(qū)中存著差異。其中,豫北、豫中和豫南產(chǎn)區(qū)穗粒數(shù)對產(chǎn)量的貢獻(xiàn)高于千粒重。豫西產(chǎn)區(qū)千粒重對產(chǎn)量的貢獻(xiàn)大于穗粒數(shù)??梢?,在小麥產(chǎn)量構(gòu)成三要素中,穗數(shù)對產(chǎn)量的貢獻(xiàn)最大,但穗粒數(shù)和千粒重對產(chǎn)量的貢獻(xiàn)則因種植區(qū)域及種植條件、品種、年份的不同,存在較大的差異。因此,河南省各小麥產(chǎn)區(qū)在進(jìn)一步挖掘小麥生產(chǎn)潛力的過程中,應(yīng)在保證充足穗數(shù)的基礎(chǔ)上協(xié)調(diào)產(chǎn)量構(gòu)成要素,主攻方向應(yīng)分區(qū)域分年型分類進(jìn)行。但本研究未考慮年際間氣候差異,不同氣候年型小麥產(chǎn)量構(gòu)成要素與產(chǎn)量的關(guān)系可能有所變化,后續(xù)的相關(guān)研究可針對不同氣候年型開展研究,明確不同氣候年型下小麥產(chǎn)量構(gòu)成要素與產(chǎn)量的關(guān)系,為不同小麥產(chǎn)區(qū)產(chǎn)量的進(jìn)一步提高提供更加具體的主攻方向。另外結(jié)合氣象數(shù)據(jù),分析不同小麥產(chǎn)區(qū)產(chǎn)量構(gòu)成要素的主要氣象影響因子,明確各小麥產(chǎn)區(qū)產(chǎn)量進(jìn)一步提高的氣候限制因子。
河南省小麥產(chǎn)量及產(chǎn)量構(gòu)成要素在不同小麥產(chǎn)區(qū)間及年際間存在較大差距,同時,不同小麥產(chǎn)區(qū)小麥產(chǎn)量構(gòu)成三要素對產(chǎn)量的貢獻(xiàn)不同。豫北和豫中產(chǎn)區(qū)產(chǎn)量、穗數(shù)、千粒重均較高,穗粒數(shù)為豫中和豫南產(chǎn)區(qū)較高,其中豫中和豫南交匯處(漯河、周口、駐馬店等地)為高產(chǎn)穩(wěn)產(chǎn)區(qū)域。各產(chǎn)區(qū)均為穗數(shù)對產(chǎn)量的貢獻(xiàn)最大,在穩(wěn)定穗數(shù)的基礎(chǔ)上,豫北、豫中、豫南產(chǎn)區(qū)應(yīng)著力挖掘千粒重的潛力,而豫西產(chǎn)區(qū)提高穗粒數(shù)的增產(chǎn)效果優(yōu)于千粒重。本研究揭示不同小麥產(chǎn)區(qū)產(chǎn)量構(gòu)成三要素對產(chǎn)量貢獻(xiàn)的差異,為不同產(chǎn)區(qū)進(jìn)一步提高小麥產(chǎn)量的主攻方向提供理論依據(jù)。
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Spatial and temporal difference analysis of wheat yield and yield components in Henan Province based on GIS
1College of Agronomy, Henan Agricultural University/Key Laboratory of Regulating and Controlling Crop Growth and Development, Ministry of Education, ZhengZhou 450046;2College of life Science, Henan Agricultural University, ZhengZhou 450002
【】The aim of the study was to clarify the main direction of further improving wheat grain yield in the different wheat regions of Henan province by analyzing the temporal and spatial differences of wheat yield and yield components.【Method】The spatial distribution maps of wheat grain yield and yield components in four wheat regions of Henan province from 2017 to 2020 were drawn based on the field monitoring data of fixed wheat monitoring stations in Henan province, and the optimal model was selected by geographic information system (GIS), and then the differences and relationships among different wheat regions were analyzed.】The wheat yield and yield components were different between different wheat regions. Among them, the yield and the spike number in North Henan and Central Henan were significantly higher than those in South Henan and West Henan, and the North Henan’s were the most, while the West Henan’s were the least. However, the kernels per ear showed that the production regions in Central Henan, South Henan and North Henan were significantly more than West Henan’s, and the most in Central Henan, while the least in West Henan. The 1000-grains weight in North Henan was the most, while South Henan was the lowest. The wheat yield, spike number, kernels per ear, and 1000-grains weight in Central Henan and South Henan (Luohe, Zhoukou, Zhumadian, etc.) were often more than that of other places in Henan, and this performance were stable between years. Correlation analysis showed that the relationship between the three elements of yield and yield in different wheat regions was inconsistent. Specifically speaking, the 1000-grains weight, the kernels per ear and the spike number in the North Henan and Central Henan regions had the largest correlation with the yield. However, the relationship with yield in East Henan and South Henan were appeared as: the spike number was the largest, the 1000-grains weight was the second, and the kernels per ear was the smallest. Path analysis was carried out on the three elements of yield and yield in those four wheat regions, which further showed that there were differences in the contribution of the yield components to yield. More precisely, the spike number and kernels per ear contributed the most to the yield in North Henan, with a direct path coefficient of 0.67. The contribution of yield components to yield in Central Henan and South Henan regions was spike number> kernels per ear> 1000-grain weight; while in West Henan, the greatest was the spike number, followed by 1000-grain weight, and the kernels per ear was the least; the direct path coefficients were 0.69, 0.45 and 0.39, respectively. Meanwhile, the indirect diameter coefficient showed that enhancing the yield increase effect of the 1000-grain weight was better than that of the kernels per ear in North Henan, Central Henan, and South Henan regions, but the West Henan was better by enhancing the kernels per ear.【】There were large differences in wheat yield and yield components in Henan different wheat regions and between years. At the same time, the three components of wheat yield in different wheat regions had different contributions to yield. Therefore, in term of further tapping the potential of wheat production for Henan province, it should be accurately classified by regions and years. As far as the conditions of this experiment concerned, based on stabilizing the spike number in the Henan province wheat regions, the production regions of North Henan, Central Henan, and South Henan should focus on further tapping the potential of 1000-grain weight, while the West Henan improving the yield increase effect of the kernels per ear were better than that of the 1000-grain weight.
wheat yield; yield components; wheat producing area; temporal and spatial distribution
10.3864/j.issn.0578-1752.2022.04.006
2021-04-25;
2021-10-27
河南省高等學(xué)校重點科研項目(21A210015)、河南省小麥產(chǎn)業(yè)技術(shù)體系項目(S2010-01-G04)、國家重點研發(fā)計劃(2016YFD0300205)
熊淑萍,E-mail:shupxiong@163.com。通信作者馬新明,E-mail:xinmingma@126.com
(責(zé)任編輯 楊鑫浩)