李 慧 王旭敏 劉 苗 劉朋召 李巧麗 王小利 王 瑞 李 軍

基于夏玉米產(chǎn)量和氮素利用的水氮減量方案優(yōu)選

李 慧 王旭敏 劉 苗 劉朋召 李巧麗 王小利 王 瑞 李 軍*

1西北農(nóng)林科技大學(xué)農(nóng)學(xué)院, 陜西楊凌 712100;2農(nóng)業(yè)農(nóng)村部西北黃土高原作物生理生態(tài)與耕作重點(diǎn)實(shí)驗(yàn)室, 陜西楊凌 712100

針對(duì)當(dāng)前夏玉米生產(chǎn)中水氮投入不合理, 缺少綜合夏玉米產(chǎn)量、氮素利用及土壤硝態(tài)氮含量對(duì)水氮優(yōu)化管理模式評(píng)價(jià)的問題, 運(yùn)用層次分析法、熵權(quán)法、博弈論組合賦權(quán)計(jì)算各指標(biāo)權(quán)重, 使用TOPSIS法建立模型對(duì)水氮減量方案進(jìn)行綜合評(píng)價(jià), 為關(guān)中平原夏玉米節(jié)水節(jié)肥環(huán)保增效的生產(chǎn)模式提供理論依據(jù)。于2018—2020年在陜西楊凌開展水、氮二因素裂區(qū)田間試驗(yàn)。設(shè)置3個(gè)灌溉處理, 以傳統(tǒng)灌水量(800 m3hm–2, W2)為對(duì)照、在此基礎(chǔ)上減50% (400 m3hm–2, W1)和減100% (0 m3hm–2, W0)。每個(gè)灌溉量下設(shè)5個(gè)施氮梯度, 以傳統(tǒng)施氮量(300 kg hm–2, N300)為對(duì)照、在此基礎(chǔ)上減25% (225kg hm–2, N225)、減50% (150 kg hm–2, N150)、減75% (75 kg hm–2, N75)和減100% (0)。分析不同水氮減量處理夏玉米產(chǎn)量、氮素利用及土壤硝態(tài)氮含量, 使用TOPSIS法建模選優(yōu)。與對(duì)照W2N300相比, W1N225增產(chǎn)效果最明顯, 增產(chǎn)率為5.4%, W2N225、W2N150、W1N150也表現(xiàn)出明顯的增產(chǎn)效應(yīng), 增產(chǎn)率分別為2.4%、0.7%、0.3%。W1N225、W1N150可以顯著提高氮肥農(nóng)學(xué)效率、氮肥回收效率、氮肥偏生產(chǎn)力, 2018年NAE、NRE、NPFP分別比傳統(tǒng)模式提高29.7%、16.2%、24.5%, 36.5%、25.4%、28.8%; 2019年分別提高53.4%、36.7%、32.8%, 46.5%、35.2%、47.4%; 2020年分別提高43.6%、37.3%、48.0%, 66.9%、43.1%、54.5%。W1N225、W1N150土壤硝態(tài)氮?dú)埩袅勘葌鹘y(tǒng)水氮管理模式減少28.6%、53.8%。使用TOPSIS法進(jìn)行綜合評(píng)價(jià), 發(fā)現(xiàn)氮肥減量25%～50%、灌水減少50%時(shí)各指標(biāo)評(píng)價(jià)值最高, 水氮減量(中水中肥)優(yōu)于高水高肥, 高水高肥優(yōu)于低水低肥, 高水低肥優(yōu)于低水高肥。通過TOPSIS法模擬尋優(yōu)得出灌水量為W1 (400 m3hm–2)施氮量為200 kg hm–2時(shí)綜合評(píng)價(jià)值最優(yōu)。因此, 在關(guān)中平原灌溉區(qū), 灌水減量50% (400 m3hm–2)、施氮減少33.3% (200 kg hm–2)可以實(shí)現(xiàn)關(guān)中平原夏玉米生產(chǎn)節(jié)水減肥環(huán)保增效的目標(biāo)。

夏玉米; 水氮減量; 氮素利用; 產(chǎn)量; TOPSIS法

施氮和灌溉是促進(jìn)作物生長發(fā)育和產(chǎn)量提高的重要途徑[1]。我國純氮施用量在逐年上升, 平均每年增加約7.8×105t[2], 關(guān)中地區(qū)農(nóng)田平均施氮量高達(dá)(288±113) kg hm–2 [3], 過量氮肥投入導(dǎo)致氮肥利用效率降低, 使得我國農(nóng)作物氮肥利用率平均只有28%～41%, 遠(yuǎn)低于40%～60%的世界平均水平[4-5]。我國農(nóng)業(yè)水資源供需矛盾日益明顯, 關(guān)中地區(qū)灌溉水資源短缺嚴(yán)重[6], 節(jié)約農(nóng)業(yè)灌溉用水也是亟待解決的重要問題。目前不合理的農(nóng)業(yè)生產(chǎn)方式, 不僅降低了水肥利用效率, 而且引發(fā)了環(huán)境污染等一系列問題[7-8]。解決玉米栽培中水氮過量投入、資源浪費(fèi)突出的問題, 有助于實(shí)現(xiàn)我國農(nóng)業(yè)從以“增產(chǎn)為核心”的單一目標(biāo)向“可持續(xù)發(fā)展的高產(chǎn)高效、環(huán)境友好”多重目標(biāo)轉(zhuǎn)變[9]。

農(nóng)田水氮存在明顯的交互效應(yīng)[10], 水氮互作可顯著提高玉米產(chǎn)量, 其中氮為主效[11], 科學(xué)的水肥管理可以有效促進(jìn)水氮耦合效應(yīng)[12]。前人研究表明, 減氮條件下適量滴灌有利于提高氮肥吸收利用率, 充分發(fā)揮水氮協(xié)同和耦合效應(yīng), 彌補(bǔ)減氮帶來的產(chǎn)量損失, 川中丘陵地區(qū)純氮180 kg hm–2、滴灌750～1125 m3hm–2[13]有利于促進(jìn)玉米生長, 提高產(chǎn)量和氮素利用。在關(guān)中平原, 與常規(guī)施氮300 kg hm–2、灌溉800 m3hm–2相比, 適宜減少施氮和灌水不會(huì)造成產(chǎn)量減少[14]。控釋氮肥減量25%可使玉米小幅度增產(chǎn), 且氮素利用效率顯著提高[15]。黃土高原旱地玉米連作農(nóng)田單施氮肥180 kg hm–2處理下, 23年后0～300 cm土層硝態(tài)氮?dú)埩袅扛哌_(dá)1500 kg hm–2 [16]。渭北旱地春玉米施氮量高于180 kg hm–2, 0～200 cm土層硝態(tài)氮?dú)埩袅扛哌_(dá)504.7～620.8 kg hm–2, 存在氮素淋溶風(fēng)險(xiǎn)[17]。

在傳統(tǒng)水肥管理模式基礎(chǔ)上適宜的水氮減量, 可以有效提高玉米水肥資源利用效率, 減少硝態(tài)氮淋溶風(fēng)險(xiǎn)[7]。前人已經(jīng)在灌水和施氮單一因素對(duì)玉米產(chǎn)量、氮素利用和硝態(tài)氮積累等方面開展了相關(guān)研究[18-22], 但相關(guān)研究多為單因素回歸分析, 適用于指標(biāo)較少的情況, 不利于多指標(biāo)判定, 夏玉米產(chǎn)量、氮素利用、土壤硝態(tài)氮含量各指標(biāo)衡量標(biāo)準(zhǔn)不盡相同, 但卻相互影響。因此本研究通過3年夏玉米田間定位灌溉和施氮試驗(yàn), 分析水氮共同減量處理下水氮互作對(duì)玉米產(chǎn)量、氮素利用和土壤硝態(tài)氮的影響, 運(yùn)用層次分析法[23]、熵權(quán)法[24]、博弈論組合賦權(quán)[25]得到各指標(biāo)綜合權(quán)重, 并通過TOPSIS法[26]建模綜合選優(yōu), 旨在達(dá)到水氮量化管理, 以期為關(guān)中平原夏玉米發(fā)展高產(chǎn)、高效、節(jié)水、節(jié)肥、環(huán)保的生產(chǎn)模式提供科學(xué)依據(jù)。

1 材料與方法

1.1 試驗(yàn)區(qū)概況

于2018—2020年在陜西省楊凌區(qū)西北農(nóng)林科技大學(xué)曹新莊試驗(yàn)農(nóng)場(chǎng)(34°20′N, 108°07′E)實(shí)施。當(dāng)?shù)貙儆诖箨懶约撅L(fēng)暖溫帶半濕潤氣候, 年均日照時(shí)數(shù)2163.8 h, 年均氣溫12.9℃, 年均降水量635.1 mm, 年均蒸發(fā)量993.2 mm, 無霜期211 d, 供試土壤為壤土。試驗(yàn)地種植制度為冬小麥、夏玉米一年二熟制輪作, 試驗(yàn)開始前土壤養(yǎng)分見表1。2018—2020年夏玉米均為6月14日播種, 2018年為10月1日收獲, 2019年和2020年為9月30日收獲, 生育期內(nèi)降水量分別為335.3、499.8和508.9 mm, 2018年和2020年生育前期降水較密集, 2019年生育后期降水較密集(圖1)。

表1 試驗(yàn)地0～60 cm土層基礎(chǔ)理化性狀

圖1 夏玉米生長季月降雨量

1.2 試驗(yàn)設(shè)計(jì)

采用二因素裂區(qū)設(shè)計(jì), 灌溉量為主區(qū), 施氮量為副區(qū)。灌溉量設(shè)3個(gè)灌溉水平: 傳統(tǒng)灌水量(800 m3hm–2, W2)為對(duì)照, 于拔節(jié)期和抽雄期各灌溉400 m3hm–2; 減量50% (400 m3hm–2, W1), 于拔節(jié)期進(jìn)行; 不灌溉(W0)。施氮量設(shè)5個(gè)施氮水平: 傳統(tǒng)施氮量(300 kg hm–2, N300)為對(duì)照、減施25% (225 kg hm–2, N225)、減施50% (150 kg hm–2, N150)、減施75% (75 kg hm–2, N75)和不施氮(N0)。小區(qū)面積91 m2(6.5 m×14.0 m), 3次重復(fù), 共計(jì)45個(gè)小區(qū)。施用氮肥為尿素, 試驗(yàn)地統(tǒng)一施磷肥為P2O5120 kg hm–2,本地區(qū)農(nóng)田土壤富含鉀素, 因此本試驗(yàn)不施鉀肥, 氮、磷肥全部基施。供試玉米品種為鄭單958, 密度6×104株 hm–2。灌溉方式采用噴灌, 水表控制灌水量, 其他管理措施同當(dāng)?shù)厣a(chǎn)習(xí)慣。

1.3 測(cè)定項(xiàng)目與方法

1.3.1 產(chǎn)量及產(chǎn)量構(gòu)成因素 在玉米成熟期, 每個(gè)小區(qū)選取行長5 m長勢(shì)均勻的玉米各3行, 統(tǒng)計(jì)穗數(shù), 在行內(nèi)選取20個(gè)均勻果穗, 取3次重復(fù), 風(fēng)干后于室內(nèi)考種, 測(cè)定穗粒數(shù)和百粒重, 按14%含水量折算籽粒產(chǎn)量。

1.3.2 植株樣品 于夏玉米成熟期, 采集不同處理具有代表性玉米植株3株, 取其地上部分105℃殺青30 min, 85℃烘干至恒重后稱重并粉碎, 采用H2SO4-H2O2消煮, 凱氏定氮法測(cè)定全氮含量[27]。

1.3.3 土壤硝態(tài)氮 在2018和2019年夏玉米成熟期, 用土鉆采集0～200 cm、2020年采集0～300 cm土層土樣, 每20 cm為一個(gè)土層。將待測(cè)土樣過2 mm篩, 稱取5.0 g鮮土樣, 用50 mL 1 mol L–1KCl溶液浸提, 振蕩1 h后過濾, 用連續(xù)流動(dòng)分析儀(AA3型)測(cè)定硝態(tài)氮含量。

1.3.4 權(quán)重確定 由于產(chǎn)量、氮素利用和土壤硝態(tài)氮含量評(píng)價(jià)指標(biāo)各不相同, 相互之間無法直接比較, 為消除量綱不同的影響, 先對(duì)數(shù)據(jù)進(jìn)行歸一化處理, 再利用不同方法確定各指標(biāo)所占權(quán)重, 運(yùn)用層次分析法[20]進(jìn)行主觀層次分析, 利用熵權(quán)法[21]進(jìn)行客觀權(quán)重分析, 由于二者之間存在差異, 運(yùn)用博弈論組合賦權(quán)[22]獲得最終權(quán)重。

1.3.5 測(cè)定項(xiàng)目相關(guān)計(jì)算方法[16]收獲指數(shù) = 籽粒產(chǎn)量/地上部生物量; 氮肥農(nóng)學(xué)效率(NAE, kg kg–1) = (施氮區(qū)玉米產(chǎn)量–不施氮區(qū)玉米產(chǎn)量)/施氮量; 氮肥回收效率 (NRE, %) = (施氮區(qū)植株地上部氮積累量–不施氮區(qū)植株地上部氮積累量)/施氮量 × 100; 氮肥偏生產(chǎn)力(NPFP, kg kg–1) = 施氮區(qū)籽粒產(chǎn)量/施氮量; 每一土層硝態(tài)氮?dú)埩袅?NR, kg hm–2) = 土壤硝態(tài)氮含量(mg kg–1) ×土層厚度(cm) × 土壤容重(g cm–1)/10。一定深度土壤硝態(tài)氮?dú)埩艨偭繛楦鱾€(gè)土層硝態(tài)氮?dú)埩袅恐汀?/p>

1.4 數(shù)據(jù)分析

使用SPSS19.0分析試驗(yàn)數(shù)據(jù), 采用Duncan’s法多重比較, 差異顯著性水平<0.05。使用Origin 2018、2021制圖。

2 結(jié)果與分析

2.1 不同水氮減量處理對(duì)夏玉米產(chǎn)量的影響

由表2可知, 3年試驗(yàn)期間, 除2019年外, 施氮量和灌水量及其互作對(duì)夏玉米產(chǎn)量有顯著影響。試驗(yàn)結(jié)果表明, 在同一灌水水平下, 隨施氮量的減少, 產(chǎn)量總體呈現(xiàn)先增后降的趨勢(shì), N225優(yōu)于其他處理。在同一施氮水平下, W1和W2產(chǎn)量差異不顯著, 但都與W0差異顯著, 與W2相比, 3年平均產(chǎn)量W0減少13.6%。在不同水氮處理下, 與W2N300相比, 2018年W2N225產(chǎn)量最高, 增高2.1%, 2019、2020年W1N225與W1N300產(chǎn)量最高, 分別增高5.0%、5.5%, 10.5%、8.8%。連續(xù)3年田間試驗(yàn)顯示, 與對(duì)照W2N300相比, W2N225、W2N150、W1N300、W1N225、W1N150增產(chǎn)2.4%、0.7%、4.5%、5.4%、0.3%, 其中W1N225增產(chǎn)最高。

2.2 不同水氮減量處理對(duì)夏玉米氮素吸收利用的影響

由表3可知, 施氮量和灌水量及其互作對(duì)夏玉米地上部吸氮量有極顯著影響。總體來說, 在同一灌水水平下, 隨施氮量的減少, 2018年和2019年氮素吸收呈減小趨勢(shì), 2020年則是先增后減, 但N225和N300無顯著差異。由此說明, 植株吸氮量存在閾值, 超過閾值繼續(xù)增施氮肥不會(huì)改善作物生長潛力。在同一施氮水平下, 植株吸氮量隨灌水量的減少而減少, 與W2相比, 2018年和2019年植株吸氮量W1和W0減少6.8%、21.0%和12.1%、17.8%, 2020年W1與W2則無顯著差異, 由此說明, 同一施氮下W2需要更多的氮肥供應(yīng)。施氮和灌水對(duì)氮肥農(nóng)學(xué)效率、氮肥回收率、氮肥偏生產(chǎn)力具有顯著影響。在同一灌水水平下, 隨施氮量的減少, NAE、NRE、NPFP都呈增加趨勢(shì)。在同一施氮量下, NAE隨灌水量的減少呈先增后降的趨勢(shì), 與W2相比, 2018、2019、2020年W1分別增大6.3%、14.1%、17.7%。2018、2020年NRE隨灌水量的減少呈先增后降, 2019年則是隨施氮量的減少呈現(xiàn)先降后增的趨勢(shì)。2018、2019、2020年NPFP在W1、W2無顯著差異, 與W0差異顯著。不同水氮處理下, 與W2N300相比, W2N225、W2N150、W1N225、W1N150在2018年NAE、NRE、NPFP分別提高30.8%、19.9%、26.5%, 26.3%、24.3%、25.5%, 40.7%、26.4%、28.2%, 40.8%、30.5%、49.5%; 2019年分別提高45.4%、49.7%、48.6%, 63.0%、32.4%、52.8%, 29.7%、16.2%、24.5%, 36.5%、25.4%、28.8%, 2020年分別提高53.4%、36.7%、32.8%, 46.5%、35.2%、47.4%, 43.6%、37.3%、48.0%和66.9%、43.1%、54.5%。

表2 不同水氮減量處理下夏玉米產(chǎn)量

N300: 施氮量為 300 kg hm–2; N225: 施氮量為 225 kg hm–2; N150: 施氮量為 150 kg hm–2; N75: 施氮量為 75 kg hm–2; N0: 施氮量為 0 kg hm–2; W2: 拔節(jié)期和抽雄期共灌水 800 m3hm–2; W1: 拔節(jié)期灌水 400 m3hm–2; W0: 不灌水;-: 產(chǎn)量減少; W: 灌水量; N: 施氮量; W×N: 灌水量×施氮量。同列數(shù)據(jù)后不同小寫字母表示同一年份不同處理間差異顯著(< 0.05)。NS表示無顯著差異, *表示在0.05概率水平差異顯著, **表示在0.01概率水平差異顯著, ***表示在0.001概率水平差異顯著。

N300: nitrogen application rate was 300 kg hm–2; N225: nitrogen application rate was 225 kg hm–2; N150: nitrogen application rate was 150 kg hm–2; N75: nitrogen application rate was 75 kg hm–2; N0: no nitrogen application; W2: irrigated 800 m3hm–2in jointing and tasseling stage; W1: irrigated 400 m3hm–2in jointing stage; W0: no irrigation;-: yield reduction. W: irrigation amount; N: nitrogen application; W×N: irrigation × nitrogen.Values followed by different lowercase letters within a column indicate significant difference among treatments in the same year at< 0.05. NS: not significant. *, **, and *** indicate significant difference at the 0.05, 0.01, and 0.001 probability levels, respectively.

表3 不同水氮減量處理下夏玉米地上部吸氮量和氮素利用效率

N300: 施氮量為300 kg hm–2; N225: 施氮量為225 kg hm–2; N150: 施氮量為150 kg hm–2; N75: 施氮量為75 kg hm–2; N0: 施氮量為 0 kg hm–2; W2: 拔節(jié)期和抽雄期共灌水 800 m3hm–2; W1: 拔節(jié)期灌水 400 m3hm–2; W0: 不灌水; W: 灌水量; N: 施氮量; W×N: 灌水量×施氮量; N uptake: 夏玉米地上部吸氮量; NAE: 氮肥農(nóng)學(xué)效率; NRE: 氮肥回收效率; NPFP: 氮肥偏生產(chǎn)力。同列數(shù)據(jù)后不同小寫字母表示同一年份不同處理間差異顯著(< 0.05)。NS表示無顯著差異, *表示在0.05概率水平差異顯著, **表示在0.01概率水平差異顯著, ***表示在0.001概率水平差異顯著。

N300: nitrogen application rate was 300 kg hm–2; N225: nitrogen application rate was 225 kg hm–2; N150: nitrogen application rate was 150 kg hm–2; N75: nitrogen application rate was 75 kg hm–2; 0: no nitrogen application; W2: irrigated 800 m3hm–2at jointing and tasseling stages; W1: irrigated 400 m3hm–2at jointing stage; W0: no irrigation; W: irrigation amount; N: nitrogen application; W×N: irrigation × nitrogen, N uptake: aboveground nitrogen uptake of summer maize; NAE: nitrogen agronomic efficiency; NRE: nitrogen recovery efficiency; NFPF: N partial factor productivity. Values followed by different lowercase letters within a column indicate significant difference among treatments in the same year at< 0.05. NS: not significant. *, **, and *** indicate significant difference at the 0.05, 0.01, and 0.001 probability levels, respectively.

2.3 不同水氮減量處理對(duì)土壤硝態(tài)氮含量及其殘留的影響

由圖2可知, 在同一灌水水平下, 隨施氮量減少, 夏玉米田0～200 cm、0～300 cm土層土壤硝態(tài)氮含量呈遞減趨勢(shì), 與N300相比, N75、N0硝態(tài)氮含量始終處于相對(duì)較低的水平, N300累積峰含量大約為50.2 mg kg–1。從灌水量看, W2、W1土壤硝態(tài)氮含量隨土層的加深逐漸增大, W0則逐漸減小。2018—2019年0～60 cm土層中硝態(tài)氮含量W0和W1大于W2, 2020年0～100 cm土層中硝態(tài)氮含量W0和W1大于W2, 60 cm、100 cm以下則是W2大于W1、W0。2018年W2、W1、W0累積峰分別出現(xiàn)在120～160 cm、80～120 cm、40～60 cm; 2019年W2處理累積峰不明顯, 可能出現(xiàn)在200 cm以下, W1下N300在80、180 cm土層出現(xiàn)累積峰, N225、N150在120～140 cm土層出現(xiàn)累積峰, W0下在60～80 cm出現(xiàn)累積峰; 2020年W2下硝態(tài)氮含量在0～100 cm、200～300 cm土層時(shí)較高, W1、W0則分別在200～220 cm、80～100 cm出現(xiàn)累積峰, 由此說明, 隨著試驗(yàn)?zāi)攴莸耐七M(jìn), 硝態(tài)氮累積向下層土壤移動(dòng), 灌水量增大顯著加快硝態(tài)氮向下淋洗。不同水氮減量處理下, N300和N225硝態(tài)氮含量顯著高于N150、N75、N0, 且隨著灌水量的變化波動(dòng)幅度明顯, 說明施氮和灌水顯著影響硝態(tài)氮含量和向下的遷移, 施氮量增大, 含量越大, 灌水增多, 向下遷移加快。

圖2 2018–2020年玉米收獲后0～200 cm、0～300 cm土層土壤硝態(tài)氮含量剖面圖

N300: 施氮量為300 kg hm–2; N225: 施氮量為225 kg hm–2; N150: 施氮量為150 kg hm–2; N75: 施氮量為75 kg hm–2; N0: 施氮量為0 kg hm–2; W2: 拔節(jié)期和抽雄期共灌水800 m3hm–2; W1: 拔節(jié)期灌水 400 m3hm–2; W0: 不灌水, *表示在0.05概率水平差異顯著, **表示在0.01概率水平差異顯著, ***表示在0.001概率水平差異顯著。

N300: nitrogen application rate was 300 kg hm–2; N225: nitrogen application rate was 225 kg hm–2; N150: nitrogen application rate was 150 kg hm–2; N75: nitrogen application rate was 75 kg hm–2; 0: no nitrogen application; W2: irrigated 800 m3hm–2in jointing and tasseling stage; W1: irrigated 400 m3hm–2at jointing stage; W0: no irrigation. *, **, and *** indicate significant difference at the 0.05, 0.01, and 0.001 probability levels, respectively.

由圖3和圖4可知, 施氮量和灌水量對(duì)硝態(tài)氮?dú)埩粲酗@著影響。隨著施氮量的減小, 2018—2020 年硝態(tài)氮?dú)埩袅坎粩鄿p少, 因此, 減少施氮量可以減小硝態(tài)氮淋溶風(fēng)險(xiǎn)。從灌水來看, 2018—2020年0～100 cm硝態(tài)氮?dú)埩袅繛閃0>W1>W2, 而2018— 2019年在100～200 cm土層則是W2>W1>W0, 2020年100～200 cm土層為W0>W1>W2, 200～300 cm為W2>W1>W0, 其原因可能是因?yàn)楣嗨瓜鯌B(tài)氮不斷向下層土壤遷移。不同水氮減量處理下, 相比對(duì)照W2N300來說, 其他水氮減量處理硝態(tài)氮?dú)埩魷p小15.6%～91.9%。

圖3 不同水氮減量處理下玉米田0～200 cm土層硝態(tài)殘留量

N300: 施氮量為300 kg hm–2; N225: 施氮量為225 kg hm–2; N150: 施氮量為 150 kg hm–2; N75: 施氮量為75 kg hm–2; N0: 施氮量為0 kg hm–2; W2: 拔節(jié)期和抽雄期共灌水800 m3hm–2; W1: 拔節(jié)期灌水400 m3hm–2; W0: 不灌水。同列數(shù)據(jù)后不同小寫字母表示同一年份不同處理間差異顯著(< 0.05)。

N300: nitrogen application rate was 300 kg hm–2; N225: nitrogen application rate was 225 kg hm–2; N150: nitrogen application rate was 150 kg hm–2; N75: nitrogen application rate was 75 kg hm–2; 0: no nitrogen application; W2: irrigated 800 m3hm–2at jointing and tasseling stages; W1: irrigated 400 m3hm–2at jointing stage; W0: no irrigation. Values followed by different lowercase letters within a column indicate significant difference among treatments in the same year at< 0.05.

圖4 不同水氮減量處理下玉米田0～300 cm土層硝態(tài)殘留量

N300: 施氮量為 300 kg hm–2; N225: 施氮量為 225 kg hm–2; N150: 施氮量為 150 kg hm–2; N75: 施氮量為 75 kg hm–2; N0: 施氮量為 0 kg hm–2; W2: 拔節(jié)期和抽雄期共灌水 800 m3hm–2; W1: 拔節(jié)期灌水 400 m3hm–2; W0: 不灌水。同列數(shù)據(jù)后不同小寫字母表示同一年份不同處理間差異顯著(< 0.05)。

N300: nitrogen application rate was 300 kg hm–2; N225: nitrogen application rate was 225 kg hm–2; N150: nitrogen application rate was 150 kg hm–2; N75: nitrogen application rate was 75 kg hm–2; 0: no nitrogen application; W2: irrigated 800 m3hm–2at jointing and tasseling stages; W1: irrigated 400 m3hm–2at jointing stage; W0: no irrigation. Values followed by different lowercase letters within a column indicate significant difference among treatments in the same year at< 0.05.

2.4 不同水氮減量處理產(chǎn)量、氮肥利用、土壤硝態(tài)氮?dú)埩袅颗c施氮量的關(guān)系

3年試驗(yàn)結(jié)果(表4)表明, 施氮量與產(chǎn)量和土壤硝態(tài)氮?dú)埩舫蕵O顯著二次函數(shù)的關(guān)系(<0.001), 施氮量與氮肥農(nóng)學(xué)效率、氮肥回收效率、氮肥偏生產(chǎn)力顯著線性相關(guān)(<0.01), 均隨施氮量的減少呈增加趨勢(shì)。

2.5 不同水氮組合的綜合效應(yīng)評(píng)價(jià)

2.5.1 權(quán)重確定 通過層次分析法確定權(quán)重, 產(chǎn)量、吸氮量、NAE、NRE、NPFP和硝態(tài)氮所占權(quán)重依次為0.619、0.026、0.031、0.045、0.054和0.226, 由于層次分析法是評(píng)價(jià)者對(duì)評(píng)價(jià)問題本質(zhì)的分析和判斷, 因此, 此種方法指標(biāo)3年權(quán)重相同。

熵權(quán)法是一種客觀分析方法, 其中產(chǎn)量、吸氮量、NAE、NRE、NPFP為正向指標(biāo), 硝態(tài)氮為負(fù)向指標(biāo), 通過SPSSPRO軟件分析所得指標(biāo)權(quán)重分別為: 2018年產(chǎn)量、吸氮量、NAE、NRE、NPFP、硝態(tài)氮分別為0.108、0.114、0.198、0.213、0.247、0.121; 2019年分別為0.457、0.064、0.109、0.117、0.144、0.108; 2020年分別為0.094、0.139、0.186、0.184、0.225、0.173。

表4 夏玉米產(chǎn)量、氮肥利用率和0～200 cm土層硝態(tài)氮?dú)埩袅颗c施氮量的回歸分析模型

W2: 拔節(jié)期和抽雄期共灌水800 m3hm–2; W1: 拔節(jié)期灌水 400 m3hm–2; W0: 不灌水, Y: 產(chǎn)量; NR: 硝態(tài)氮?dú)埩袅? NAE: 氮肥農(nóng)學(xué)效率; NRE: 氮肥回收效率; NPFP: 氮肥偏生產(chǎn)力。*表示在0.05概率水平差異顯著,**表示在0.01概率水平差異顯著,***表示在0.001概率水平差異顯著。

W2: irrigated 800 m3hm–2at jointing and tasseling stages; W1: irrigated 400 m3hm–2at jointing stage; W0: no irrigation; Y: yield; NR: residual nitrate; NAE: nitrogen agronomic efficiency; NRE: nitrogen recovery efficiency; NFPF: N partial factor productivity.*,**, and***indicate significant difference at the 0.05, 0.01, and 0.001 probability levels, respectively.

由于層次分析法和熵權(quán)法所得權(quán)重之間存在差異, 因此采用博弈論組合賦權(quán)的方法確定指標(biāo)的最終權(quán)重, 2018年產(chǎn)量、吸氮量、NAE、NRE、NPFP、硝態(tài)氮權(quán)重分別為0.337、0.120、0.108、0.122、0.144、0.168; 2019年分別為0.568、0.047、0.057、0.065、0.074、0.188; 2020年分別為0.336、0.088、0.107、0.125、0.147、0.197。

2.5.2 不同水氮組合的綜合評(píng)價(jià)方法-TOPSIS法

圖5表明貼合度Di與產(chǎn)量B11、吸氮量B21、氮肥農(nóng)學(xué)效率B22、氮肥回收效率B23的相關(guān)性達(dá)到極顯著水平(<0.001), 貼合度Di與氮肥偏生產(chǎn)力B24的相關(guān)性達(dá)到顯著水平(<0.01), 由此說明利用TOPSIS法確定水氮減量對(duì)夏玉米綜合評(píng)價(jià)指標(biāo)的影響是可行的。

通過TOPSIS法從高產(chǎn)、高效、環(huán)保3方面出發(fā), 確定不同水氮組合的綜合評(píng)價(jià)指標(biāo)排序(表5), 3年綜合排序排名前5的處理分別為W1N225、W2N150、W1N150、W2N225、W2N75, W1N225、W2N150、W1N150、W2N75、W1N300, W1N150、W1N225、W1N300、W2N75、W2N150。在同一灌水水平下, 與N300相比, N225、N150時(shí)綜合指標(biāo)分別增大10.3%、14.4%, 在同一施氮水平下, 與W2相比, 綜合指標(biāo)W1增大4.1%, 由此可知, 水氮減量優(yōu)于傳統(tǒng)水氮管理模式。氮肥減量25%～50%、灌水減少50%時(shí)各指標(biāo)評(píng)價(jià)值最高, 因此, 在關(guān)中平原灌溉區(qū)可以通過水氮減量實(shí)現(xiàn)玉米高產(chǎn)、節(jié)約資源和保護(hù)環(huán)境的目標(biāo)。由W2N300、W2N150、W1N225、W1N150、W0N300、W0N0可知, 水氮協(xié)同調(diào)控夏玉米綜合指標(biāo), 水氮減量(中水中肥)優(yōu)于高水高肥, 高水高肥優(yōu)于低水低肥,高水低肥優(yōu)于低水高肥, 因此, 在關(guān)中平原可以適當(dāng)減少施氮量來提高夏玉米綜合評(píng)價(jià)值。

將綜合評(píng)價(jià)值與施氮量進(jìn)行擬合(圖6), 綜合評(píng)價(jià)值與施氮量呈顯著的二次函數(shù)的關(guān)系, 在同一灌水水平下, 綜合評(píng)價(jià)值隨施氮量的增加先增后降。圖6中水氮減量(中水中肥)綜合評(píng)價(jià)值維持在較高水平, 且高水低肥優(yōu)于低水高肥, 因此為了提高綜合評(píng)價(jià)值可以施氮減少施氮量。在2018、2019、2020年W2、W1、W0水平下施氮量分別為182.6、180.6、183.9, 184.7、210.5、195.9, 159.8、208.8和153.7 kg hm–2時(shí), 綜合評(píng)價(jià)值最高為0.74、0.82、0.45, 0.76、0.80、0.67, 0.77、0.81、0.60, W2、W1、W0下減氮41.3%、33.3%、40.7%仍可達(dá)到最優(yōu)。通過模型模擬尋優(yōu), 得出在灌水量為W1 (400 m3hm–2), 施氮量為200 kg hm–2時(shí)綜合評(píng)價(jià)值最優(yōu)。

圖5 貼合度與不同指標(biāo)的相關(guān)性分析

Di: 貼合度; B11: 產(chǎn)量; B21: 吸氮量; B22: 氮肥農(nóng)學(xué)效率; B23: 氮肥回收效率; B24: 氮肥偏生產(chǎn)力; B31: 硝態(tài)殘留量。*表示在0.05概率水平差異顯著, **表示在0.01概率水平差異顯著, ***表示在0.001概率水平差異顯著。

Di: the degree of fit; B11: maize; B21: aboveground nitrogen uptake of summer maize; B22: nitrogen agronomic efficiency; B23: nitrogen recovery efficiency; B24: N partial factor productivity; B31: residual nitrogen. *, **, and *** indicates significant difference at the 0.05, 0.01, and 0.001 probability levels, respectively.

表5 基于TOPSIS 法確定的不同水氮處理的貼近度和綜合排序

TOPSIS: 優(yōu)劣解距離法; N300: 施氮量為 300 kg hm–2; N225: 施氮量為 225 kg hm–2; N150: 施氮量為 150 kg hm–2; N75: 施氮量為 75 kg hm–2; N0: 施氮量為0 kg hm–2; W2: 拔節(jié)期和抽雄期共灌水800 m3hm–2; W1: 拔節(jié)期灌水400 m3hm–2; W0: 不灌水; D+: 理想解和處理間距離; D–: 逆理想解和處理間距離; Di: 貼合度。同列數(shù)據(jù)后不同小寫字母表示同一年份不同處理間差異顯著(< 0.05)。

TOPSIS:technique for order preference by similarity to an ideal solution; N300: nitrogen application rate was 300 kg hm–2; N225: nitrogen application rate was 225 kg hm–2; N150: nitrogen application rate was 150 kg hm–2; N75: nitrogen application rate was 75 kg hm–2; 0: no nitrogen application; W2: irrigated 800 m3hm–2at jointing and tasseling stages; W1: irrigated 400 m3hm–2at jointing stage; W0: no irrigation; D+: the distance between the ideal solution and the treatment; D–: the distance between the inverse ideal solution and the treatment; Di: the degree of fit. Values followed by different lowercase letters within a column indicate significant difference among treatments in the same year at< 0.05.

圖6 不同灌水條件下綜合評(píng)價(jià)貼合度與施氮量的關(guān)系

W2: 拔節(jié)期和抽雄期共灌水 800 m3hm–2; W1: 拔節(jié)期灌水 400 m3hm–2; W0: 不灌水。

W2: irrigated 800 m3hm–2at jointing and tasseling stages; W1: irrigated 400 m3hm–2at jointing stage; W0: no irrigation.

3 討論

3.1 水氮減量對(duì)夏玉米產(chǎn)量和氮素利用的影響

施氮和灌水是作物增產(chǎn)的主要手段, 二者相互協(xié)調(diào)可以促使玉米高產(chǎn)。農(nóng)業(yè)生產(chǎn)中多通過增施氮肥來增產(chǎn), 但實(shí)際生產(chǎn)中, 作物產(chǎn)量卻隨施氮量的增加而減少[28], 玉米生育期內(nèi)耗水量高, 只有合理灌溉才可以提高氮素利用率并增產(chǎn)[29]。本研究發(fā)現(xiàn), 減水50%和減氮25%～50%產(chǎn)量小幅增加, 這與邢維芹等[30]在半干旱地區(qū)進(jìn)行的研究結(jié)果相似, 適宜水氮減量玉米產(chǎn)量下降幅度小于15.26%, 且水分利用率提高。本研究中減水50%和減氮25%～50% NAE、NRE、NPFP隨施氮量減少呈增加趨勢(shì), 氮素利用保持在較高水平, 植株吸氮量與傳統(tǒng)水氮管理模式無顯著差異。前人研究發(fā)現(xiàn), 與習(xí)慣灌水和施氮量相比, 水氮減量處理提高氮素利用率且對(duì)夏玉米產(chǎn)量無顯著影響[31]; 減少施氮量且水分為田間持水量的75% ± 5%的土壤條件時(shí), 可以提高植株氮素積累量, 合理的水氮運(yùn)籌方式有利于高產(chǎn)群體的構(gòu)建[32]; 適宜減少施氮量顯著提高籽粒氮素積累, 提高植株氮素吸收[14]。造成以上現(xiàn)象的原因: 一是適宜氮肥用量可以提高葉片的葉綠素含量, 提高葉片光合碳同化能力, 延長光合時(shí)間, 促進(jìn)光合同化物向籽粒轉(zhuǎn)移, 進(jìn)而提高產(chǎn)量[33]。二是過量施氮其增產(chǎn)效果會(huì)隨施氮量增加逐漸減弱, 在土壤水分不足時(shí), 水分制約氮肥發(fā)揮效用, 當(dāng)水分過多則會(huì)增加氮素?fù)p失, 進(jìn)而氮素利用降低[34]。因此, 在關(guān)中平原玉米生產(chǎn)中可以適當(dāng)減少灌溉量和施氮量, 會(huì)有小幅增產(chǎn), 且提高氮素利用效率, 減少資源浪費(fèi)。

3.2 水氮減量對(duì)土壤硝態(tài)氮?dú)埩舻挠绊?/h3>

施氮和灌水是影響土壤硝態(tài)氮含量及其殘留的重要因素, 二者增加會(huì)使土壤中硝態(tài)氮的殘留量增加[35-37], 同時(shí)硝態(tài)氮向下遷移的速度加快[38]。本研究中, 土壤硝態(tài)氮含量N300>N225>N150>N75>N0, 且殘留量W2>W1>W0。2019、2020年灌水處理N300下硝態(tài)氮隨土層的加深出現(xiàn)2個(gè)累積峰。其原因可能是土壤質(zhì)地導(dǎo)致, 塿土中有黏化層的存在(多在60～140 cm), 黏化層上硝態(tài)氮分部較均勻, 高施氮量下硝態(tài)氮遷移到黏化層以下遷移變快, 在較深土層則會(huì)出現(xiàn)第2個(gè)累積峰[35]。同時(shí), 0～100 cm、100～200 cm、200～300 cm土層硝態(tài)氮?dú)埩袅砍霈F(xiàn)顯著的差異。其原因可能是由于土壤中NO3–-N的運(yùn)動(dòng)一般與水分同步或略滯后[39], 灌水量的差異致使不同土層殘留量的不同。因此, 在關(guān)中平原農(nóng)業(yè)生產(chǎn)中實(shí)施水氮減量可以減少土壤中硝態(tài)氮含量和殘留,降低土壤、地下水污染的風(fēng)險(xiǎn)。

3.3 基于TOPSIS的水氮減量方案模擬尋優(yōu)

水氮管理模式的優(yōu)選, 通常是水氮用量對(duì)作物產(chǎn)量、氮素利用等的單變量回歸分析, 從養(yǎng)分資源效率最大化目標(biāo)確立適宜的水氮用量, 單變量回歸多適用于指標(biāo)較少的評(píng)價(jià), 不適用于多指標(biāo)判定。前人通過綜合評(píng)價(jià)體系建立多變量回歸分析探究作物對(duì)水肥用量的響應(yīng)[40-41], 研究表明, 各指標(biāo)對(duì)應(yīng)的最佳水氮組合并不是水氮投入越多越優(yōu)。本研究通過綜合評(píng)價(jià)體系建立多變量回歸分析, 運(yùn)用數(shù)學(xué)方法定量化研究產(chǎn)量、氮素利用、環(huán)境等多指標(biāo)對(duì)水肥用量的綜合效果, 確定最優(yōu)水氮減量方案的灌溉量和施氮量 (灌水為400 m3hm–2, 施氮200 kg hm–2)。前人通過綜合評(píng)價(jià)法[42]和綜合指數(shù)法[9]的研究也表明, 綜合得分隨施氮量的增加呈先增后降的趨勢(shì), 選取綜合得分高于0.8的確定為適宜施氮量, 推薦施氮186～225 kg hm–2可以實(shí)現(xiàn)高產(chǎn)高效、農(nóng)田環(huán)境友好氮肥體系; 綜合指標(biāo)值定量地顯示了減氮20%的包膜尿素應(yīng)用綜合效果最佳。因此, 在關(guān)中平原夏玉米拔節(jié)期灌水量400 m3hm–2和總施氮量200 kg hm–2可以實(shí)現(xiàn)高產(chǎn)高效、資源節(jié)約、保護(hù)環(huán)境的目標(biāo)。

4 結(jié)論

在關(guān)中平原灌區(qū), 在目前常規(guī)管理中灌水800 m3hm–2和施氮量300 kg hm–2基礎(chǔ)上, 灌水減量50%、施氮減量25%～50%時(shí), 夏玉米獲得較高產(chǎn)量, 氮素利用效率保持較高水平, 且減少土壤硝態(tài)氮?dú)埩?。水氮減量顯著影響夏玉米綜合評(píng)價(jià)指標(biāo), 綜合各指標(biāo)對(duì)水氮減量的響應(yīng), 通過TOPSIS法對(duì)水氮減量方案模擬尋優(yōu), 拔節(jié)期灌水量400 m3hm–2和總施氮量200 kg hm–2可以作為關(guān)中平原夏玉米節(jié)水節(jié)肥、高效環(huán)保的生產(chǎn)模式。

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Water and nitrogen reduction scheme optimization based on yield and nitrogen utilization of summer maize

LI Hui, WANG Xu-Min, LIU Miao, LIU Peng-Zhao, LI Qiao-Li, WANG Xiao-Li, WANG Rui, and LI Jun*

1College of Agronomy, Northwest A&F University, Yangling 712100, Shaanxi, China;2Key Laboratory of Crop Physio-ecology and Tillage Science in Northwestern Loess Plateau, Ministry of Agriculture and Rural Affairs, Yangling 712100, Shaanxi, China

The objective of this study is to solve the problems of excessive water and nitrogen input in current summer maize cropping system and lacking comprehensiveevaluation approach and evaluatethe current water and nitrogen management scheme for yield, nitrogen utilization of summer maize and soil nitrate nitrogen content. AHP, entropy method, and game theory were combined to determine index weight, TOPSIS was used to evaluate water and nitrogen reduction scheme, thus the results can provide a theoretical basis for water-saving, nitrogen-reducing and high efficient cultivation scheme of summer maize in Guanzhong plain. The two-factor split-plot field experiment during 2018–2020 was conducted in Yangling, Shaanxi province, where three irrigation levels were traditional 800 m3hm–2(W2) as the control, reduced to 400 m3hm–2(W1), and no irrigation (W0). Each water treatment was the five N rate treatments [300 kg hm–2(N300) as the control, reduced 25% (225 kg hm–2), reduced 50% (150 kg hm–2), reduced 75% (75 kg hm–2), and no N fertilizer (0)]. Maize yield, nitrogen use efficiency, and soil nitrate nitrogen content under different water and nitrogen reduction treatments were analyzed and to choose optimal scheme with modeling by TOPSIS. Compared with W2N300 (CK), W1N225 had best effect on yield, and increased significantly by 5.4%. Meanwhile, W2N225, W2N150, and W1N150 had significantly effect on yield, and increased significantly by 2.4%, 0.7%, and 0.3%, respectively. W1N225 and W1N150 enhanced the N-use efficiency, agronomic efficiency, and partial factor productivity, andincreased significantly by 29.7%, 16.2%, 24.5%; 36.5%, 25.4%, 28.8%; 53.4%, 36.7%, 32.8%; 46.5%, 35.2%, 47.4%; 43.6%, 37.3%, 48.0%; and 66.9%, 43.1%, 54.5% than CK in 2018, 2019, 2020, respectively. W1N225, W1N150 reduced soil nitrate nitrogen leaching, and decreased by 28.6% and 53.8% than CK, respectively.Using TOPSIS for comprehensive evaluation, it was found that the evaluation value of each index was the highest when nitrogen fertilizer was reduced by 25%–50% (with nitrogen application rate of 150–225 kg hm–2) and irrigation water was reduced by 50% (irrigated 400 m3hm–2in jointing stage). Water and nitrogen reduction (medium fertilizer in middle water) were better than high water and high fertilizer, high water and high fertilizer were better than low water and low fertilizer, and high water and low fertilizer were better than low water and high fertilizer. Through TOPSIS optimization, the comprehensive evaluation value was the best when the irrigation amount was W1 (irrigated 400 m3hm–2at jointing stage) and the nitrogen application amount was 200 kg hm–2. Therefore, reduced irrigation (irrigated 400 m3hm–2in jointing stage) and reduced 33.3% nitrogen (with nitrogen application rate of 200 kg hm–2) mode can be used to realize the water-saving and nitrogen reduction production of summer maize in Guanzhong Plain.

summer maize; irrigation and nitrogen fertilizer reduction; nitrogen use efficiency; yield; technique for order preference by similarity to an ideal solution

10.3724/SP.J.1006.2023.23046

本研究由國家科技支撐計(jì)劃項(xiàng)目(2015BAD22B02)和國家自然科學(xué)基金項(xiàng)目(31801300)資助。

The study was supported by the National Science and Technology Support Program of China (2015BAD22B02) and the National Natural Science Foundation of China (31801300).

李軍, E-mail: junli@nwsuaf.edu.cn

E-mail: 17852021052@163.com

2022-06-01;

2022-09-05;

2022-09-17.

URL: https://kns.cnki.net/kcms/detail/11.1809.S.20220916.1121.004.html

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).