施肥对蔬菜中硝酸盐含量的影响

通过对山东省蔬菜面积较大的潍坊和青岛市的蔬菜进行了取样分析及有关的试验,结果表明:依据国家标准(GB18406 1—2001)在所测的所有样品中,蔬菜硝酸盐含量均没有超标。而依据FAO/WHO(1973年)规定,瓜果类和根茎类蔬菜硝酸盐含量均不超标,而叶菜类有近30%超标,超标蔬菜达到了生食盐渍不宜,熟食允许的程度;同一种类蔬菜露天栽培比保护地栽培的硝酸盐积累量少;氮磷钾合理配合施用能减少蔬菜硝酸盐积累。本文提出了控制蔬菜硝酸盐积累的施肥措施。     

Zinc accumulation characteristics of some leafy vegetables

Abstract

Twelve leafy vegetables were grown on field plots treated with 0, 10, 50, 100, 200, 400, and 800 pounds Zn per acre incorporated into the 0‐ to 10‐inch soil depth. At harvest maturity the edible parts of the plants were sampled and analyzed for Zn.

Of the 12 crops grown, only Swiss chard and spinach showed any tendency to be Zn accumulators. Even these crops would tolerate extremely high levels of available soil Zn before accumulating what might be considered hazardous Zn concentrations. Swiss chard and spinach were the only crops which showed visible growth depression when grown on plots treated with 800 lbs. Zn per acre.     

几种新型氮肥对叶菜硝酸盐累积和土壤硝态氮淋洗的影响

应用土柱模拟试验的方法,研究了在高肥力菜田土壤条件下,施用几种新型氮肥对两茬叶菜硝酸盐积累和土壤硝态氮淋洗的影响。结果表明,在高肥力菜田土壤上,施用几种新型氮肥都未能明显提高第一茬油菜的生物量,硫硝铵（A SN）却降低了生物量,而第二茬菠菜不施肥处理生物量下降。尿素＋硝化抑制剂DM PP（En tec46）、尿素＋硝化抑制剂DCD（U＋DCD）和有机无机复混肥（OIF）3种氮肥显著降低了油菜硝酸盐含量。尿素＋玉米秸秆（U＋M S）和硫硝铵＋硝化抑制剂DM PP（En tec26）减少了土壤NO3^--N的向下淋洗,而尿素＋保水剂（U＋SAP）增加土壤NO3^--N的向下淋洗。     

用硝酸根电极快速测定蔬菜中的硝酸盐含量

详细介绍了硝酸根电极测定蔬菜硝酸盐氮的方法。从回收率试验、对比试验和精密度试验结果评价,该方法简便、快捷、准确,可用于蔬菜硝酸盐的快速测定。     

用硝酸根电极快速测定蔬菜中的硝酸盐含量

详细介绍了硝酸根电极测定蔬菜硝酸盐氮的方法。从回收率试验、对比试验和精密度试验结果评价，该方法简便、快捷、准确，可用于蔬菜硝酸盐的快速测定。     

不同氮肥用量对蔬菜硝酸盐累积的影响研究

通过田间试验研究不同氮肥用量对多种蔬菜硝酸盐含量的影响。结果表明:随着氮肥用量的增加小白菜、番茄中硝酸盐的含量随之增大。在同一施肥水平下,小白菜硝酸盐含量高于番茄上百倍,说明叶菜类较茄果类易富集硝酸盐。     

Effects of Bentonite Application and Urea Fertilization Time on Growth,Development and Nitrate Accumulation in Spinach (Spinacia oleraceae L.)

Under excessive application of nitrogen fertilizer, vegetables can accumulate high levels of nitrate in their vegetative body and, when consumed by living organisms, pose serious health-related risks for humans. Regarding such problems, it is necessary to minimize the accumulation of nitrate in leafy vegetables. Therefore, a pot experiment was conducted to evaluate bentonite levels (0, 20, 40, 60, 80 g/kg soil) application and urea fertilization times (25, 50, 75 days after sowing; at the rate of 0.2 g per pot) on the growth, development and nitrate accumulation of spinach. Results showed that urea fertilization on 25 days after sowing date had the highest effect on the quality, while application of 60 gr bentonite had the highest effect on the improvement of growth parameters of spinach. The lowest nitrate and nitrite accumulation rate was observed at urea fertilization on 50 days after planting and lack of bentonite application, whereas the lowest oxalic acid content was obtained at urea fertilization on 25 days after planting in a soil without bentonite application. The results showed that implementing an appropriate rate of bentonite and urea fertilization times may bring about favorable results for spinach production.     

泉州蔬菜硝酸盐污染的调查及探讨

调查了 1 1类型 5 9种蔬菜 ,发现泉州蔬菜硝酸盐污染普遍 ,严重超标。其NO3- 累积量一般规律是 :叶菜类 >根菜类 >薯芋类 >茄果类 >葱蒜类 >芽苗菜类、瓜类 >豆类 >水生类 >多年生类 >食用菌类。另外 ,从调查分析中 ,发现了施肥和土壤肥力水平对蔬菜体内NO3- 含量影响相当大。     

集约化种植条件下土壤硝态氮动态变化及累积特征研究

选取江阴市沿江平原地区的3种典型农业种植区,即大棚葡萄集约化种植基地、蔬菜集约化种植基地和常规种植农田为研究对象,通过田间现场采样分析的方法研究了不同种植方式下土壤剖面硝态氮含量的动态变化和累积特征.结果表明,葡萄种植基地0-100 cm各土层硝态氮含量随时间的变化波动较大,而蔬菜种植基地和常规种植农田的表层土壤硝态氮含量变化幅度大于深层土壤;3种典型种植区的土壤硝态氮含量均呈现随着土层深度的增加而逐渐减小的趋势,其中土壤硝态氮含量最大值出现在葡萄种植基地的20-40 cm土层中;葡萄种植基地各土层硝态氮平均累积量均高于蔬菜种植基地和常规种植农田,大棚葡萄集约化种植基地0-00 cm土层硝态氮平均累积总量高达400.96 kg/hm2,显著高于蔬菜集约化种植基地和常规种植农田的累积总量,这进一步表明不合理过量追肥导致土壤中硝态氮大量累积,增大了氮素淋失和地下水环境污染的风险.     

田间条件下氮的矿化及硝态氮淋溶研究

采用SRC（Soil-Resin-Core）装置，研究了重庆市主要土壤类型的氮矿化差异以及与硝态氮淋溶的关系。研究结果表明，微酸性紫色土（菜地）的氮索矿化量、硝态氮淋失量和有效氮的变幅均较大，而其它两种坡耕地变化的氮素矿化景和硝态氮的淋失量变幅均较小。相关分析表明：在微酸性紫色土中，影响硝态氮淋失的主要因素是矿化量，且二者呈显著正相关；而其它两种坡耕地土壤的矿化量与硝态氮淋失量不表现相关性。这就表明不同土壤矿化、硝态氮淋失的情况有差异。     

蔬菜间作对土壤和蔬菜硝酸盐累积的影响

大量氮肥施用,易造成菜地土壤硝酸盐累积并引起地下水硝酸盐污染和蔬菜硝酸盐含量超标。为降低菜田氮素累积及环境污染风险,采用根深差异蔬菜间作的方法,研究其对土壤硝态氮时空变异规律和蔬菜硝酸盐含量的影响,选择根系较深的萝卜和根系较浅的芹菜进行间作种植大田试验。结果表明,无论在作物的生长前期还是收获期,此种间作增加了0～20cm土层NO3^- -N含量,同时降低了20cm以下土层NO3^- -N含量,能够减少土壤中NO3^- -N的向下移动。从土壤NO3^- -N累积剖面分布规律看,间作区0～40cm土层NO3^-—N累积量高于单作区,而40～100cm土层NO3^- -N累积量低于单作区,间作区土壤0—100cm土层NO3^- -N总累积量减少,收获期分别比萝卜和芹菜单作区降低1．4％、9．0％。间作有降低萝卜和芹菜硝酸盐的趋势,而间作区萝卜全氮含量显著高于单作区,同时间作显著提高了萝卜产量,此种间作还能够减少氮素的表观损失。总之,合理搭配的蔬菜间作既能够增强土壤对氮素的保蓄能力,减少土壤NO3^- -N淋移,对蔬菜产量和品质也有一定正效应。     

河北太行山山前平原葡萄园土壤硝态氮累积特征及影响因素

为进一步摸清农户生产实践条件下果园土壤硝态氮分布特征及影响因素,以河北太行山山前平原的保定地区葡萄园为研究对象,调查28个果园生产管理现状,测定分析葡萄园和临近农田共31个样点0—200 cm土壤硝态氮含量、累积量及主要影响因素。结果表明:葡萄生产中氮肥施用量偏高,每季平均为297 kg/hm²,过量的养分投入导致氮素在土壤中累积,0—200 cm土层硝态氮淋洗现象明显,平均累积量高达1 555 kg/hm²。不同树龄、施氮量、灌溉量水平下,土壤硝态氮含量有所不同,但均表现出随土层深度增加而增加的趋势,并且明显高于农田土壤。相关性分析表明,硝态氮累积量与树龄和施氮量均呈极显著正相关,与灌溉量呈显著负相关。通径分析表明,对土壤硝态氮累积量影响最大的因素为施氮量,其次为树龄和施肥次数,最后为灌溉量,施肥次数主要通过影响施氮量来间接影响硝态氮累积量。研究区域葡萄园氮素盈余严重,土壤硝态氮大量累积,并向深层土壤淋洗,影响该地区硝态氮累积的主要因素为施氮量、树龄和灌溉量。     

陕西关中设施栽培蔬菜的硝酸盐累积状况分析

研究了陕西关中主要蔬菜产区设施栽培蔬菜的硝酸盐累积现状,探讨了施氮量对蔬菜硝酸盐累积的影响。结果表明,宝鸡、杨凌、咸阳、西安四地的新鲜大棚蔬菜硝酸盐污染严重,部分对硝酸盐敏感的蔬菜如萝卜、芹菜等硝酸盐含量超过无公害蔬菜卫生限量标准。施氮对蔬菜硝酸盐累积量的影响显著,随施氮量的增加,蔬菜可食部分的硝酸盐含量增加。     

Nitrate nitrogen and nitrate reductase activity in Verna lemon tree leaves

The determination of the leaf nitrate concentration, as well as the nitrate reductase activity have been proposed as a parameters for the estimation of the nitrogen requirements of citrus plants. Because this, it is interesting to dispose of a well criteria for their suitable diagnosing. On nutritionally normal Verna lemon trees we study the annual evolution of the leaf nitrate levels as well as the nitrate reductase activities. At the same time, the cause of the nitrogen alterations induced by iron chlorosis are determined. The results show that is the ferredoxin the iron compound responsible of this nitrogen unbalance.     

施肥与灌水对硝态氮在土壤中残留的影响

通过田间试验研究不同施氮量与灌水量对春玉米和冬小麦田土壤中硝态氮分布与累积的影响,结果表明,春玉米收获后0~2 m土壤中累积硝态氮185.7~748.0 kg/hm2,其中1 m以上占57.9%~70.1%。由于施用氮肥而增加的硝态氮占施N量的1.8%(N 112.5 kg/hm2),50.7%(N 225 kg/hm2),56.7%(N 337.5 kg/hm2)和77.0%(N450 kg/hm2)。不施N和施N 112.5 kg/hm2时春玉米田土壤剖面没有明显累积峰;施N等于或高于225 kg/hm2时在60~80 cm土层有明显累积峰,施氮量高的峰值较高;施N 450 kg/hm2时在120~140 cm深度出现另一个累积高峰。冬小麦收获后土壤0~2 m硝态氮累积量为74.9~328.8 kg/hm2,其中1m以上占67.8%~90.7%。由于施用氮肥而增加的硝态氮占施N量的19.5%(N 112.5 kg/hm2),35.6%(N 225 kg/hm2),58.9%(N 337.5 kg/hm2)和56.4%(N 450 kg/hm2)。冬小麦田收获后土壤深层(1~2 m)没有明显的硝态氮累积,即使施氮量高达450 kg/hm2时也只在表层40 cm以上累积较多。不论是春玉米还是冬小麦,当生育期施氮量大于225 kg/hm2时0~2 m土层均有明显的硝态氮累积,施氮量高的累积量较高。施氮量是造成土壤中硝酸盐累积的主要因素,灌水量对春玉米田硝态氮的向下迁移有显著影响。     

玉米硝酸盐累积及其在适应持续低氮胁迫中的作用

旱地作物吸收氮素的主要形态是硝酸盐,硝酸盐的积累与再利用对植物适应低氮土壤环境具有重要意义。本试验利用两个硝酸盐累积能力不同的玉米自交系478（硝酸盐积累低）和W312（硝酸盐积累高）为研究材料,研究玉米的硝酸盐累积及其在适应持续低氮胁迫中的作用。结果表明,W312的硝酸还原酶活性和NR基因的表达都弱于478,而体内氨基酸含量显著较低。对一个可能与液泡膜硝酸盐转运有关的氯离子通道蛋白基因（ZmCLC）的表达分析发现,478的ZmCLC表达显著强于W312。说明W312硝酸盐积累能力强主要是由于其较弱的氮同化能力,而不是硝酸盐向液泡的运输能力强。在砂培体系并持续缺氮条件下,W312叶绿素含量（SPAD值）显著高于478,表明植株体内较高硝酸盐累积有助于W312适应持续缺氮的土壤环境。     

Soil nitrate distribution,N2O emission and crop performance after the application of N fertilizers to greenhouse vegetables

The impacts of nitrogen (N) application rates on soil nitrate, electrical conductivity (EC), pH, soil N₂O emission, tomato yield and fruit quality were investigated in a 20‐yr vegetable field experiment under greenhouse cultivation in Northeast China. The treatments included no N control (N0), the recommended N rate (N1; mean annual 300 kg/ha) and the commonly used N rate by farmers (N2; mean annual 600 kg/ha). Soil nitrate content and EC increased significantly to 120 cm depth with increasing rates of applied N. An opposite trend was found for soil pH within the upper 20 cm. Cumulative N₂O emission and maximum N₂O emission rates both increased significantly with increasing N rates. Tomato yield increased significantly from the N0 to N1 rate, but remained constant from the N1 to N2 one. Nitrate concentration in tomatoes also increased significantly with N rates. A contrasting trend was found for soluble sugar and organic acid concentrations. The results indicate that the commonly used N2 rate is excessive and causes adverse effects on tomato quality and on the environment. The recommended N1 rate is optimal for sustainable greenhouse vegetable production. In greenhouses, daily soil N₂O emission rates are strongly influenced by N application and fluctuate with irrigation frequency and the incidence of wetting/drying cycles.     

不同施肥模式对春玉米产量、水分利用效率及硝态氮残留的影响

通过2年田间试验,研究了减量施氮和减氮配施不同比例控释肥对黄土旱塬春玉米产量、水分利用效率及土壤硝态氮残留量的影响,旨在为黄土高原旱作农业区提供合理的施肥管理模式。试验于2017年4月至2018年9月在黄土旱塬雨养农业区进行,供试作物为春玉米,采用半覆膜种植方式,一年一熟制。试验共设置CK(不施氮肥)、N1C1(控释尿素65%+普通尿素35%,N200kg/hm^2)、N1C2(控释尿素50%+普通尿素50%,N200kg/hm^2)、N1C3(控释尿素35%+普通尿素65%,N200kg/hm^2)、N1(减氮模式,普通尿素,N200kg/hm^2)、N2(传统施氮模式,普通尿素,N250kg/hm^2)6个处理,测定土壤含水量、收获期土壤剖面(0—300cm)中的硝态氮含量及春玉米产量。结果表明:与N2处理相比,减氮处理(N1)并没有减少作物产量,反而显著增加作物产量(p<0.05),2017年、2018年分别增加9.6%和6.9%,土壤水分利用效率分别提高13.3%和10.2%(p<0.05)。同等施氮量(200kg/hm^2)下,与全尿素N1处理相比,2017年配施不同比例控释肥的各处理降低了春玉米的产量和水分利用效率;2018年N1C2处理较N1处理显著增加春玉米的产量和水分利用效率(p<0.05),分别增加7.7%和11.6%。此外,试验2年后减氮模式N1和减氮配施一定比例的控释肥处理显著减少土壤剖面(0—300cm)中硝态氮的残留量(p<0.05),与N2处理相比,N1处理减少了61.2%;同等施氮量(200kg/hm^2)下,与N1处理相比,N1C2处理降低了50.8%。     

茄子/大葱间作及氮肥调控对植株硝酸盐含量及养分吸收的影响

作物根系分布深度不同,其吸收养分的土壤区域也有所不同。采用大田试验方法,选择深根系的茄子和浅根系的大葱进行间作种植,并辅以氮素调控措施,研究其对蔬菜硝酸盐含量及养分吸收的影响。研究表明,无论是常规施肥还是减量施肥,间作均能降低蔬菜体内硝酸盐含量。间作区茄子的生物量和吸氮、磷、钾量均高于单作区,而间作区大葱的生物量及吸氮、磷、钾量均有所降低。说明在这一间作模式中,茄子处于优势地位,而大葱处于劣势地位。     

Sequential Injection Determination of Nitrate in Vegetables by Spectrophotometry with Inline Cadmium Reduction

Abstract

A sequential injection system for the determination of nitrate (NO₃ ^?) in vegetables was developed to automate this determination, allowing for substantially reduced reagent consumption and generated waste using low‐cost equipment. After extraction with water and filtration, the extracted nitrate is reduced inline to nitrite in a copperized cadmium (Cd) column and determined as nitrite. According to the Griess–Ilosvay reaction, nitrate is diazotized with sulfanilamide and coupled with N‐(1‐naphtyl)‐ethylenediamine dihydrochloride to form a purple‐red azo dye monitored at 538 nm.

Nitrate can be determined within a range of 1.35–50.0 mg L^?1 of NO₃ ^? (corresponding to 0.270–10.0 g of NO₃ ^? per kg of vegetable), with a conversion rate of nitrate to nitrite of 99.1±0.8%. The results obtained for 15 vegetable extracts compare well with those provided by the classical procedure, with a sampling throughput of 24 determinations per hour and relative standard deviations better than 1.2%.