Analysis of the inducing factors of kiwifruit leaf chlorosis based on selection of diagnostic indicators for iron deficiency
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摘要:目的
筛选适宜的缺铁诊断指标,据此分析导致陕西关中地区猕猴桃园叶片黄化的主要因子,并利用施肥矫治试验对该因子进行验证,为猕猴桃叶片黄化防控提供理论依据。
方法在陕西关中地区,依据叶片黄化后土施Fe-EDDHA可以复绿确定了3个缺铁猕猴桃果园,采集当年强旺营养枝顶端第2~3个叶片,共采集不同黄化度叶片64份,缺铁叶片样品的黄化度以SPAD值表征,将SPAD值与5个缺铁诊断指标进行相关分析。在关中地区选择5个健康果园、80个出现不同程度黄化症状的猕猴桃果园,采集叶片样品,将黄化果园叶片按照黄化程度分为绿叶、轻度黄化叶和重度黄化叶,测定12种元素、活性铁和硝态氮含量及SPAD值,并将其与SPAD值进行相关分析。在85个果园各采集1份土壤样品,分析其基础理化性状。选择两个黄化果园进行施肥矫治效果验证。
结果64份缺铁黄化叶片中,鲜样邻二氮菲浸提铁与其SPAD值的相关性明显高于干样全铁、0.1 mol/L盐酸浸提铁、1 mol/L盐酸浸提铁和鲜样1 mol/L盐酸浸提铁,说明鲜样邻二氮菲浸提铁最适于猕猴桃缺铁的黄化诊断。健康园绿叶和黄化园绿叶中所测的12种元素、活性铁和硝态氮含量均无显著差异。SPAD和邻二氮菲浸提铁含量的顺序为黄化园绿叶>轻度黄化叶>重度黄化叶,而叶片硝态氮、磷、钾和硼含量则相反。轻度和重度黄化叶钙、全铁和锰含量低于绿叶。相关分析表明,猕猴桃叶片SPAD与叶片邻二氮菲浸提铁、全铁、锰和钙含量正相关,而与叶片钾、磷、硝态氮、全氮、硼、铜等含量负相关。随机森林和通径分析进一步表明,与猕猴桃叶片黄化关系最密切的指标为邻二氮菲浸提铁、钾及硝态氮。线性加平台函数拟合表明,邻二氮菲浸提铁5.084 mg/kg是猕猴桃叶片缺铁黄化诊断的临界值。土壤分析结果表明,黄化园土壤pH和碳酸氢根含量均偏高,而速效钾和硝态氮含量均适宜,说明土壤重碳酸盐诱发缺铁很可能是导致叶片黄化的主要原因。与健康园相比,黄化园土壤阳离子交换量偏低,说明叶片黄化还与土壤阳离子交换能力不足有关。施用Fe-EDDHA和蓝铁矿[Fe3(PO4)2·8H2O)]均可提高叶片SPAD和邻二氮菲浸提铁含量,降低叶片钾和硝态氮含量,从而矫治猕猴桃叶片缺铁黄化。
结论叶片鲜样中邻二氮菲铁最适于猕猴桃缺铁黄化诊断,其临界浓度为5.084 mg/kg。陕西关中地区猕猴桃园叶片黄化主要是由土壤重碳酸盐诱发缺铁所致,且与土壤阳离子交换能力不足有关;黄化叶中钾和硝态氮的累积是由缺铁造成的。因此,生产上应注意黄化园铁肥的补充和土壤阳离子交换能力的提升。
Abstract:ObjectivesAppropriate indicator for iron (Fe) deficiency diagnosis was selected. Based on this, the main factors causing kiwifruit leaf chlorosis in central Shaanxi Province were analyzed and verified using a fertilizer trial, which will provide a theoretical basis for preventing and controlling kiwifruit leaf chlorosis.
MethodsIn central Shaanxi Province, three Fe-deficient kiwifruit orchards were identified through chlorotic leaf re-greening after Fe-EDDHA soil application. Sixty-four leaf samples with different chlorosis degrees were collected from the second and third fully expanded leaves at the top of the currently and vigorously vegetative shoots in these Fe-deficient orchards. The SPAD values of these leaf samples were correlated with five Fe-deficiency-diagnosis indicators. Moreover, five healthy and eighty chlorotic kiwifruit orchards in central Shaanxi Province were selected to sample leaves with different chlorosis degrees (green, slightly chlorotic, and severely chlorotic), for determining twelve elements, active Fe, nitrate nitrogen (NO3−-N) and SPAD values, and correlated these elements with SPAD values. Eighty-five soil samples were collected for analyzing physical and chemical properties. Additionally, fertilizer trial in two chlorotic orchards was performed to test the correction of leaf and soil analyses.
ResultsIn 64 Fe-deficient leaf samples, the correlation coefficient of leaf SPAD and phenanthroline Fe extracted from fresh samples was considerably higher than those of total Fe, 0.1 mol/L HCl Fe, and 1 mol/L HCl Fe, which were extracted from dry leaf samples, as well as 1 mol/L HCl Fe extracted from fresh leaf samples, indicating that phenanthroline-extractable Fe may be a better indicator for kiwifruit Fe deficiency diagnosis. No difference was found in contents of twelve elements, active Fe and NO3−-N between green leaves of healthy and chlorotic kiwifruit orchards. The descending order of leaf SPAD and phenanthroline-extractable Fe concentration was green leaf in chlorotic orchard > slightly chlorotic leaf > severely chlorotic leaf. The opposite was true for leaf NO3−-N, phosphorus (P), potassium (K) and boron (B) concentration. The calcium (Ca), total Fe and manganese (Mn) concentration was lower in slightly and severely chlorotic leaves than in green leaf. Correlation analysis indicated that leaf SPAD was positively correlated with leaf phenanthroline-extractable Fe, total Fe, Mn, and Ca, but negatively correlated with leaf K, P, NO3−-N, total N, B and Cu. Moreover, random forest and path analyses indicated that the most closely related indicators to leaf chlorosis were phenanthroline-extractable Fe and K as well as NO3−-N. Linear plus plateau function fitting model indicated that 5.084 mg/kg of phenanthroline-extractable Fe concentration was the critical concentration for diagnosing Fe deficiency in kiwifruit chlorotic leaves. When compared with the optimum ranges, the soil pH and HCO3− were higher but available K and NO3−-N were suitable in chlorotic orchards, indicating that bicarbonate-induced Fe deficiency in soils may be the main reason of causing kiwifruit leaf chlorosis. Moreover, soil cation exchange capacity was lower in chlorotic orchards than in healthy orchards, suggesting that leaf chlorosis was associated with the weak capacity of soil cation exchange. Application of Fe-EDDHA or vivianite [Fe3(PO4)2·8H2O)] increased leaf SPAD and phenanthroline-extractable Fe concentration, reduced leaf K and NO3−-N concentrations, and thus correcting kiwifruit leaf yellowing induced by Fe deficiency.
ConclusionsPhenanthroline-extractable Fe in leaves is the most suitable indicator for kiwifruit Fe deficiency diagnosis, and its critical concentration is 5.084 mg/kg. In central Shaanxi Province, the leaf yellowing of kiwifruit orchards is mainly caused by bicarbonate-induced Fe deficiency in soils, and also related with the poor capacity of soil cation exchange. The accumulation of K and NO3−-N in chlorotic leaves is the results of Fe deficiency. Therefore, more attention should be paid to the supplement of Fe fertilizers and the improvement of soil cation exchange capacity in chlorotic kiwifruit orchards.
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陕西关中地区是我国乃至世界上猕猴桃生产最集中的地区之一,2021年猕猴桃产量达122.2万t[1],分别占我国和世界总产量的51.3%和27.4%[2]。随着种植年限的延长和栽培区域的扩大,关中地区猕猴桃果园黄化问题日益严重。猕猴桃果园黄化病的主要发生期为每年5月到7月,表现为新梢叶片从顶部向基部逐渐失绿,较轻时表现为黄色,严重时为黄白色,甚至白色[3−4],进而影响果实产量和品质及树体长势[5]。
猕猴桃叶片黄化多与叶片缺铁有关[6−8]。然而,由于果树存在“铁黄化悖论”现象(即缺铁黄化叶全铁含量等于甚至高于绿叶)[9],导致叶片全铁含量不能很好反映果树铁素的丰缺。所以有学者认为,活性铁比全铁更适于果树缺铁营养诊断[10−11],但有关活性铁浸提方法尚无统一标准[12−15],且不同浸提方法对猕猴桃缺铁诊断效果的研究鲜见报道[15]。研究还表明,猕猴桃叶片黄化与多种养分失调有关,但除铁外,其他导致黄化的元素尚无定论[6−7, 16],主要是由于这些研究多是在小区域、少量果园、部分元素上的研究结果。此外,导致猕猴桃叶片黄化的叶片养分和土壤肥力分析及施肥矫治效果试验往往彼此分离[6−8, 16−17],不能很好地相互佐证。
鉴于此,本研究选取3个缺铁黄化猕猴桃园,筛选适宜的缺铁诊断指标,在此基础上对陕西关中地区80个代表性猕猴桃黄化园的12种叶片元素和18个土壤肥力参数进行测定,分析导致猕猴桃叶片黄化的主要因子,然后选择2个黄化园进行主要致黄因子诊断和施肥矫治,为该地区猕猴桃叶片黄化病专用配方肥及其配套绿色高效栽培技术的研发提供科学依据。
1. 材料与方法
1.1 猕猴桃缺铁诊断指标筛选试验样品的采集
试验于2021年6月上旬在陕西关中地区3个缺铁猕猴桃果园进行(图1a),判断依据为这些果园每树土施约30~60 g EDDHA铁肥后新梢复绿[8, 18]。田间观察发现,猕猴桃缺铁黄化现象在同一地块不同植株甚至相同植株不同枝梢之间差异较大,且对缺铁复绿响应最敏感的为当年强旺营养枝的上部叶。所以,本试验将黄化度接近的叶片作为1份叶样,采样部位为当年强旺营养枝顶端往下第2~3片完全展开成熟叶。每份叶样由15片叶组成,每株采集5片叶,共采集3株。从3个果园共采集不同黄化度的叶样64份。将叶样装入干净塑料袋中,立即放入有冰块的泡沫保温箱中保存,带回实验室进行前处理。
1.2 猕猴桃黄化园调查试验叶片和土壤样品的采集
试验于2021年7月上旬在陕西关中地区8个县(市、区)共85个猕猴桃园进行(图1a)。采样点的多寡依当地猕猴桃栽培面积和黄化病严重程度等因素综合而定,使采样点分布尽量均匀且有代表性。其中,猕猴桃黄化园80个,包括眉县32个,周至县21个,扶风县3个,杨凌区2个,武功县4个,兴平市1个,渭南市临渭区11个,渭南市华州区6个。与此同时,在黄化园附近随机选择健康园5个,包括眉县3个、周至县1个、杨凌区1个。品种为生产上缺铁黄化较为普遍的猕猴桃主栽品种‘徐香’(Actinidia chinensis var. deliciosa ‘Xuxiang’)和‘秦美’(A. chinensis var. deliciosa ‘Qinmei’)[19]。黄化园由45个徐香园和35个秦美园组成,健康园均为徐香园。树龄5~25年生不等。
从黄化园采集3类叶片:黄化园绿叶、轻度黄化叶和重度黄化叶。其中,黄化园绿叶是指叶子表面整体保持绿色的叶片;轻度黄化叶是指叶脉保持绿色、叶脉之间明显变黄的叶片;重度黄化叶是指叶片全部黄化,少量叶片发白甚至叶缘焦枯卷曲的叶片(图1b)。每份叶样由黄化度类似的20片叶组成,每株采集4片叶,共采集5株。采样部位为当年强旺营养枝顶端往下第2~3片完全展开成熟叶。从80个黄化园共采集240份叶样。每个黄化园采集1份土样,土样采集方法为:用内径为5 cm的土钻,在距离主干0.8~1.2 m附近采集0—40 cm土层的土壤,每个果园呈S形随机采集6钻土,装入干净塑料袋带回实验室分析。同时,采集健康园绿叶和土样各5份。
1.3 猕猴桃黄化园主要致黄因子诊断与施肥矫治试验的设计及样品的采集
前两个试验的分析结果表明,缺铁是导致陕西关中地区猕猴桃叶片黄化的主要因子,故开展了缺铁诊断与矫治工作。试验于2023年4月下旬在陕西省周至县富仁镇渭丰村的2个典型猕猴桃黄化园进行。其中,园1为5年生‘翠香’(A. chinensis var. deliciosa ‘Cuixiang’),园2为5年生‘徐香’。于2023年4月21日,每园采集不同黄化度叶片各3份,测定叶片SPAD值和铁含量。在进行缺铁诊断后,每园选择黄化度中等、长势接近的9棵树作为待处理植株,在距黄化树主干约40 cm处挖约5 cm深、20 cm宽的环形沟,并设置3个处理:1)以浇灌20 L清水作为对照;2)浇灌20 L含30 g EDDHA铁肥的溶液(Fe-EDDHA);3)浇灌20 L由100 g磷酸一铵和300 g硫酸亚铁配制的蓝铁矿[Fe3(PO4)2·8H2O]溶液(蓝铁矿)[20]。分别于2023年5月1日和5月15日各进行1次灌根处理。每处理重复3次,单株重复。每个处理植株标记典型黄化梢6条,于2023年5月1日、5月15日和6月1日,测定标记黄化梢顶端第2~3片完全展开叶SPAD值,并于6月1日采集第2片和第3片完全展开叶用于养分测定。
1.4 叶片黄化度的测定
叶片样品的黄化度用SPAD-502叶绿素仪(日本Konica Minolta公司)测定。为保证测定结果的准确性,每次测定前用标准色板校正仪器基准数值。为保证测定结果的代表性,测定每个叶片时避开叶脉,测定中部2个点,测定每份叶样所有叶片的SPAD值,取平均值为该份叶样的SPAD值。所以,缺铁诊断方法评价试验中每份叶样的SPAD值为30个测定值的平均值,黄化园调查试验为40个测定值的平均值,黄化矫治试验为24个测定值的平均值。
1.5 叶片样品的前处理和测定
采集的叶样先用加0.1%中性洗涤剂的自来水清洗1次,再用自来水、0.1 mol/L盐酸和去离子水各清洗1次,用纸巾擦干。用不锈钢剪刀去除叶柄后,将叶片沿叶片主脉剪为均等的两半,一半立即置于鼓风干燥箱内105℃杀青30 min,65℃烘至恒重,磨碎后过0.85 mm尼龙筛保存于塑料自封袋中,用于干样元素含量的测定;另一半暂存于4℃冰箱,并于24 h内进行鲜样铁的提取。
黄化园叶片干样在干灰化后,用电感耦合等离子体发射光谱仪(ICP-OES),测定全铁(FeTotal)、磷、钾、钙、镁、锰、铜、锌、硼、钠等元素含量[21];样品经浓硫酸−双氧水消化后,用连续流动分析仪进行奈氏比色法测定全氮(NTotal)含量[21];用沸水浴提取—硝酸银比浊法测定氯含量[22];用水浴提取—水杨酸比色法测定硝态氮含量[23]。叶片鲜样活性铁分别用1.5%邻二氮菲(pH=3,FePhen)和1 mol/L盐酸(Fe1MHCl·FW)提取[24],叶片干样活性铁分别用0.1 mol/L盐酸(Fe0.1MHCl·DW)和1 mol/L盐酸(Fe1MHCl·DW)提取[15],用原子吸收分光光度法测定铁含量。除各类活性铁和硝态氮外,其余元素指标均用植株组织标准物质GBW07603(GSV-2)控制测试质量。
1.6 土壤样品的前处理和测定
采集的土样在剔除石块、动植物残体等杂质后,在室内风干,磨碎后过0.85 mm (20目)筛,用于除有机质外的土壤肥力指标的测定。用四分法取部分过0.85 mm (20目)筛的土样,进一步磨碎过0.15 mm(100目)筛,用于有机质含量的测定。
土壤pH用pH酸度计(土水比1∶5)测定,用电导率仪测定相同溶液电导率后,计算土壤可溶性盐含量[25];土壤有效氯采用土水比1∶2.5提取,用硝酸银滴定法测定;土壤有机质用外加热重铬酸钾容量法测定;土壤阳离子交换量用乙酸钠浸提—火焰光度法测定;土壤硝态氮和铵态氮采用1 mol/L氯化钾浸提,连续流动分析仪测定;土壤速效磷采用碳酸氢钠浸提,钼锑抗比色法测定;土壤速效钾和交换性钙、镁、钠采用1 mol/L乙酸铵浸提,原子吸收分光光度法测定;土壤有效铁、锰、铜、锌采用DTPA提取剂浸提,原子吸收分光光度法测定;土壤有效硼采用沸水浸提,姜黄素比色法测定;土壤碳酸氢根采用酸碱滴定法测定[21]。
1.7 数据分析
试验数据用Excel 2007进行处理。利用SPSS 16.0软件对不同黄化度叶片之间和施肥处理之间相关指标进行方差分析,LSD法进行多重比较,用独立样本t检验进行健康园和黄化园之间土壤肥力参数的比较。通径分析参考袁志发等[26]的方法。用ArcGIS 10.7软件进行采样点分布图的绘制,用Origin 2022软件进行曲线拟合散点图和柱状图的绘制,用R4.3.0软件进行Pearson相关系数的计算和相关性热图的绘制及随机森林分析。变量相对重要性用均方差增量(increase in mean squared error)表征[27]。
2. 结果与分析
2.1 猕猴桃叶片缺铁诊断指标的筛选
以64份不同黄化度的缺铁叶样为研究对象,通过分析叶片黄化度(以SPAD值表征)与不同浸提铁的相关性,筛选最适于猕猴桃缺铁黄化诊断的指标。结果表明,缺铁导致的猕猴桃叶片黄化与鲜样邻二氮菲铁(FePhen)相关性最高(R2=0.7004),其后依次为1 mol/L盐酸干样铁(Fe1MHCl·DW,R2=0.5264)、0.1 mol/L盐酸干样铁(Fe0.1MHCl·DW,R2=0.5107)和1 mol/L盐酸鲜样铁(Fe1MHCl·FW,R2=0.4706),与叶片干样全铁相关性最低(FeTotal,R2=0.2521) (图2)。这说明,用邻二氮菲提取的叶片鲜样铁最适于猕猴桃叶片缺铁诊断,故后续研究以FePhen作为猕猴桃缺铁诊断的主要指标。
图 2 猕猴桃叶片SPAD与不同方法浸提铁的相关性注:FePhen—鲜样, 邻二氮菲浸提铁;Fe1MHCl·DW—干样,1 mol/L盐酸浸提铁;Fe0.1MHCl·DW—干样,0.1 mol/L盐酸浸提铁;Fe1MHCl·FW—鲜样,1 mol/L盐酸浸提铁;FeTotal—干样,全铁。n=64,R20.001=0.1614。Figure 2. Correlations between kiwifruit leaf SPAD and iron concentrations in various extractsNote: FePhen—Phenanthroline extracted Fe in fresh leaves; Fe1MHCl·DW—1 mol/L HCl extracted Fe in dry leaves; Fe0.1MHCl·DW—0.1 mol/L HCl extracted Fe in dry leaves; Fe1MHCl·FW—1 mol/L HCl extracted Fe in fresh leaves; FeTotal—Total Fe in dry leaves. n=64, R20.001=0.1614.2.2 猕猴桃黄化园叶片养分的特征及其与叶片黄化的关系
为了探明导致猕猴桃园叶片黄化的主要养分,首先对80个黄化园不同黄化度叶片养分含量进行方差分析,然后利用相关分析、随机森林和通径分析鉴定导致叶片黄化的关键养分。鉴于不同黄化度叶片养分特征在‘徐香’和‘秦美’两个猕猴桃品种之间基本一致(数据未列出),故仅对全体样本的不同黄化度叶片进行比较分析。结果表明,健康园绿叶和黄化园绿叶的SPAD值和各种元素含量均无显著差异(表1和图3,P<0.05),说明绿叶养分处于平衡状态。对黄化园而言,绿叶SPAD值和FePhen含量最高,轻度黄化叶次之,重度黄化叶最低(表1)。相反,黄化园绿叶硝态氮、磷、钾和硼含量最低,轻度黄化叶居中,重度黄化叶最高(图3)。与黄化园绿叶相比,轻度黄化叶和重度黄化叶钙、全铁和锰含量较低、氯含量较高(图3)。此外,相较黄化园绿叶,重度黄化叶全氮、镁、铜和钠含量较高(图3)。
表 1 不同黄化度猕猴桃叶片的SPAD值和邻二氮菲铁含量Table 1. SPAD and phenanthroline-extractable iron concentration in kiwifruit leaves in different chlorosis degrees叶片
LeavesSPAD 邻二氮菲铁 FePhen
(mg/kg, FW)健康园绿叶
Green leaves in healthy orchard45.19±2.73 a 5.64±0.38 a 黄化园绿叶
Green leaves in chlorotic orchard45.84±3.81 a 5.66±0.19 a 轻度黄化叶
Slightly chlorotic leaves25.28±3.57 b 2.94±0.14 b 重度黄化叶
Severely chlorotic leaves10.64±2.61 c 2.21±0.11 c 注:同列数据后不同小写字母表示相同指标在不同黄化度叶样间差异显著 (P<0.05)。
Note: Values followed by different lowercase letters in a column represent significant difference among various chlorosis-scale leaves for the same parameter (P<0.05).图 3 猕猴桃果园不同黄化度叶片养分含量的差异注:柱上不同小写字母表示相同指标在不同黄化度叶样间差异显著,ns表示差异不显著(P<0.05)。Figure 3. Differences in leaf nutrient concentration among various chlorosis-scale leaves of kiwifruit orchardsNote: Different small letters above the bars represent significant difference among various chlorosis-scale leaves for the same parameter, and ns represents no significant difference (P<0.05).相关分析表明,猕猴桃叶片SPAD与叶片FePhen、全铁、锰和钙含量显著正相关,而与叶片钾、磷、硝态氮、全氮、硼、铜、氯、钠和镁含量显著负相关(P<0.05) (图4a)。所有与叶片SPAD正相关的养分之间均呈显著正相关,且以FePhen与SPAD的相关性最高(r=0.727) (图4a)。在与叶片SPAD负相关的养分中,钾、磷、硝态氮、全氮、硼和铜之间呈显著正相关,且以钾、磷、硝态氮与SPAD的相关性较高(r分别为−0.802、−0.749和−0.718) (图4a)。随机森林分析和通径分析均表明,对猕猴桃叶片黄化贡献较大的指标为FePhen和钾及硝态氮,其余指标贡献较小(图4b和表2)。这些结果说明,陕西关中地区猕猴桃园叶片黄化主要与叶片铁缺乏和钾、硝态氮过量有关。
图 4 猕猴桃不同黄化度叶片SPAD与叶片元素含量的相关性(a)及其随机森林分析(b)注:图4a中红色圆点表示正相关,蓝色圆点表示负相关;圆点越大、颜色越深,表示相关性越高;仅有显著相关的两个指标之间以圆点显示(P<0.05),不相关的指标之间为空白。n=245。Figure 4. Correlations (a) and random forest analysis (b) between SPAD and nutrient concentrations of various chlorosis-degree kiwifruit leavesNote: In Fig. 4a, the red and blue color of the circles represent the positive and negative sign of the correlations, respectively. Both the size and the color shade of the circles are proportional to the correlation coefficient value. Only significant correlations (P<0.05) are displayed and the non-significant correlations are left blank. n = 245.表 2 猕猴桃黄化园叶片养分对叶片SPAD值的通径分析Table 2. Path analysis of leaf elements on leaf SPAD value in chlorotic kiwifruit orchards养分
Nutrient直接通径系数
Direct path coefficient间接通径系数 Indirect path coefficient 决策系数
Decision coefficientK FePhen NO3−-N P FeTotal Mn Mg Na Cl K −0.367 −0.199 −0.183 −0.079 0.049 −0.038 0.0198 −0.0034 −0.0026 0.454 FePhen 0.354 0.206 0.119 0.047 −0.088 0.046 0.0286 0.0042 0.0101 0.390 NO3−-N −0.283 −0.237 −0.149 −0.060 0.033 −0.011 −0.0032 −0.0042 −0.0036 0.327 P −0.095 −0.306 −0.175 −0.180 0.040 −0.028 0.0011 −0.0076 0.0013 0.133 FeTotal −0.126 0.143 0.247 0.074 0.030 0.034 0.0114 0.0005 0.0004 −0.120 Mn 0.155 0.089 0.105 0.020 0.017 −0.027 −0.0193 −0.0011 −0.0049 0.079 Mg −0.124 0.059 −0.082 −0.007 0.001 0.012 0.024 −0.0095 −0.0088 0.018 Na −0.067 −0.019 −0.022 −0.018 −0.011 0.001 0.003 −0.0176 0.0025 0.015 Cl −0.063 −0.015 −0.057 −0.016 0.002 0.001 0.012 −0.0174 0.0026 0.015 为了更好地指导生产,对叶片SPAD和FePhen进行线性加平台函数拟合,求取猕猴桃叶片缺铁黄化诊断的临界值。结果表明,当叶片FePhen含量低于5.084 mg/kg时,猕猴桃叶片SPAD随着叶片FePhen含量的增加而增加;当叶片含量≥5.084 mg/kg时,叶片SPAD达到平台期(图5)。这表明,5.084 mg/kg是陕西关中地区猕猴桃叶片缺铁黄化诊断的临界值。
2.3 猕猴桃黄化园土壤肥力的特征及其与叶片黄化的关系
为了探究导致猕猴桃园叶片黄化的土壤肥力原因,对健康园和黄化园的18个土壤肥力相关参数进行t检验。结果表明,黄化园土壤硝态氮和速效钾含量均基本处于适宜范围(图6),说明硝态氮和钾不是导致果园叶片黄化的主要原因。相反,黄化园土壤pH和碳酸氢根含量均偏高(图6),符合石灰性土壤重碳酸盐诱发缺铁的主要特征[32],结合叶片分析结果(表1、表2和图4)可知,土壤重碳酸盐诱发缺铁是导致陕西关中地区猕猴桃叶片黄化的主要原因。
图 6 猕猴桃黄化园与健康园土壤肥力参数的差异注:JY代表健康园,HY代表黄化园。CEC—阳离子交换容量。图中虚线旁数值代表适宜范围的高值和低值边界,图中单个虚线代表高值边界,碳酸氢根数值代表诱发黄化的临界浓度范围。土壤肥力参数的适宜范围除pH、碳酸氢根和阳离子交换量分别参考李百云等[28]、Boxma[29]和郭兆元[30]外,其余参数均参考Wang等[31]。Figure 6. Comparison in soil fertility parameters between healthy and chlorotic kiwifruit orchardsNote:JY represents healthy orchard, and HY represents chlorotic orchard. CEC—Cation exchange capacity. The values next to dashed lines represent the high and low limits of optimum ranges, single dashed line in one figure represent the high limit of the optimum ranges, and the values in the HCO3− figure represent the critical concentration range for bicarbonate-induced chlorosis. The optimum range is summed from Li et al (pH)[28], Boxma (HCO3−)[29], Guo ( CEC)[30] and Wang et al (other parameters)[31].与健康园相比,黄化园土壤阳离子交换量偏低(P<0.05, 图6)。黄化园土壤有机质、交换性钙和水溶性硼含量亦略低于健康园,但水溶性氯含量则略高于健康园(P<0.20, 图6)。不仅如此,土壤有机质和交换性钙均与土壤阳离子交换量正相关(数据未列出)。这些结果说明,陕西关中地区猕猴桃园叶片黄化还与土壤阳离子交换能力不足有关。
值得注意的是,土壤pH和碳酸氢根含量在健康园和黄化园之间无差异(图6),但健康园却无黄化现象,说明即使在高pH和碳酸氢根条件下,只要其他栽培管理措施得当,亦能够有效克服猕猴桃缺铁黄化问题。
2.4 猕猴桃黄化园施肥矫治效果评价
叶片和土壤分析结果表明,土壤缺铁是导致陕西关中地区猕猴桃园叶片黄化的主要因子。为了验证叶片黄化诱因分析结果的可靠性,我们随机选择了2个猕猴桃黄化园开展施肥矫治试验。结果表明,本试验所选的两个猕猴桃园黄化叶FePhen含量均低于绿叶(图6),说明这两个果园均存在缺铁问题。施用EDDHA铁或蓝铁矿15和31天后,猕猴桃叶片SPAD持续升高(图6)。施用铁肥31天后,猕猴桃叶片FePhen升高,钾和硝态氮下降,全铁含量略有升高,但未达显著水平(图6)。这不仅证实了缺铁是造成猕猴桃叶片黄化的主要原因,还说明钾和硝态氮含量偏高是叶片黄化的结果,而非原因。
3. 讨论
果树缺铁黄化在石灰性土壤上十分常见[32],但由于存在“铁黄化悖论”现象[9],导致果树上缺铁的准确高效诊断较为困难。为此,有学者提出了活性铁的概念,即植物体内参与代谢反应或分子同化,特别是叶绿素合成的那部分铁,以二价铁为主[10−11];认为较之全铁,活性铁与果树叶片黄化关系更为密切,能更好地反映植株体内的铁水平。然而,关于活性铁的提取方法尚无统一标准[12−15]。在猕猴桃上,黄宏文[15]提出了0.1 mol/L盐酸浸提铁诊断效果优于1 mol/L盐酸浸提铁,毛富春等[17]进一步证实了0.1 mol/L盐酸浸提铁诊断效果好于全铁。但有研究表明,1 mol/L盐酸浸提铁[6, 8]和全铁[7]也能够较好地用于猕猴桃缺铁诊断。这些结果说明,关于猕猴桃缺铁诊断最优方法尚无定论。鉴于此,本研究比较了当前果树上应用较广泛的几种铁提取方法:干样全铁、0.1 mol/L盐酸干样铁、1 mol/L盐酸干样铁、1 mol/L盐酸鲜样铁和鲜样邻二氮菲铁。结果表明,鲜样邻二氮菲铁对猕猴桃缺铁黄化的诊断效果最佳,盐酸铁(包括0.1 mol/L干样、1 mol/L干样和鲜样)诊断效果次之,干样全铁诊断效果最差(图2)。这与桃树[33]和鳄梨[24]上的诊断指标评价结果基本一致。邻二氮菲浸提铁在猕猴桃缺铁诊断上效果较好的原因可能有二:其一,相较盐酸,邻二氮菲对二价铁提取的特异性更高,而二价铁的准确高效提取是果树缺铁诊断成败的关键;其二,猕猴桃叶片汁液因呈粘稠状而不易被氧化,故有利于维持在邻二氮菲提取过程中活性铁的初始价态,但对强氧化性、高穿透力盐酸提取过程中铁的初始价态保护效果较差。事实上,目前国内果树上活性铁的提取多采用盐酸[8, 34],本研究中所用的鲜样邻二氮菲铁提取法可为一些以盐酸为浸提剂时缺铁诊断效果不佳的果树种类提供有益借鉴。
方差分析和相关分析均表明,陕西关中地区猕猴桃叶片黄化可能与铁、锰或钙缺乏有关(表1,图3和图4a)。然而,到底是哪种养分导致了猕猴桃叶片黄化呢?为此,本研究进行了随机森林分析和通径分析。这两种分析方法为筛选导致猕猴桃叶片黄化的关键元素提供了重要手段。随机森林分析中的变量相对重要性越大,说明该变量对猕猴桃叶片黄化影响越大[27]。通径分析中决策系数的排序反映了各变量对叶片黄化综合作用的大小,不同于偏回归和相关系数的简单排序,能够探明主要决定性变量[26]。张炎等[35]利用随机森林和通径分析表明,镁对福建省平和县琯溪蜜柚叶片黄化影响最大。本研究表明,邻二氮菲铁是影响猕猴桃叶片黄化的最主要因子,锰和钙对叶片黄化影响甚微(图4b和表2)。这说明,陕西关中地区猕猴桃叶片黄化主要与缺铁有关。
陕西关中地区猕猴桃果园为石灰性土壤[36],而石灰性土壤诱发的叶片缺铁黄化往往伴随着多种养分的失调,如钾、磷、硼的累积和钙、锰的不足(图3,4a)[16],这与柑橘、苹果、梨、桃等果树上的报道一致[37−40]。然而,缺铁黄化叶片氮的变化规律尚存争议[40−43]。考虑到缺铁黄化会影响叶片氧化还原状态[38, 44]而硝态氮能够反映叶片氧化状态,所以本研究同时分析了叶片的全氮和硝态氮含量。结果表明,随着猕猴桃叶片黄化的加重,叶片全氮和硝态氮含量均升高(图3),但硝态氮与叶片黄化度的相关性(r=−0.718)高于全氮(r=−0.510) (图4a);而施铁叶片复绿伴随着高硝态氮含量回落到正常水平(图7),这说明缺铁黄化主要导致了猕猴桃叶片硝态氮而非全氮的累积,可能与硝态氮在叶绿体中的同化过程需要铁氧还蛋白和铁硫蛋白的参与有关[23, 45]。该结果的意义在于:1)在硝态氮导致土壤环境碱化的基础上,进一步解释了生产上过量施用硝态氮易导致果树叶片缺铁黄化的现象[44];2)解释了生产上铁肥与尿素、氨基酸等含氮化合物配施或制成螯合剂矫治缺铁效果较好的原因,因为硝态氮的累积会导致黄化叶片铵态氮、各类氨基酸等含氮物质合成受阻[45],进而导致其相对匮乏;3)解释了缺铁黄化叶片钾累积的原因,因为钾是硝酸根的陪伴离子,二者在植物体内的吸收转运过程中彼此促进[46],故缺铁黄化叶片硝酸根的累积导致了钾的累积。反过来,增大钾肥施用量也会导致果树叶片铁含量的下降[37, 47],这很可能与叶片硝态氮含量的升高有关。总之,该结果为阐明石灰性土壤上果树缺铁黄化潜在机理和研发缺铁黄化综合防控技术提供了重要理论依据。
图 7 猕猴桃黄化园施用铁肥对叶片SPAD和元素含量的影响注:柱上不同小写字母表示相同指标在不同黄化度叶样间或不同施肥处理间差异显著,ns表示差异不显著(P<0.05)。Figure 7. Effects of Fe fertilizers on leaf SPAD and element concentration in chlorotic kiwifruit orchardsNote: Different small letters above the bars represent significant difference among various chlorosis-scale leaves or different fertilizer treatments for the same parameter, and ns represents no significant difference (P<0.05).土壤分析结果表明,本研究中的猕猴桃黄化园符合石灰性土壤诱发缺铁的主要特征(图6)[32],结合叶片分析结果可知(表1、表2和图4),缺铁是导致陕西关中地区猕猴桃叶片黄化的主要原因。然而,猕猴桃健康园和黄化园土壤pH和碳酸氢根含量均较高且无明显差异(图6)。类似地,王绍祖等[48]对葡萄缺铁黄化园的调查表明,健康园和黄化园土壤pH均较高且无明显差异。这说明,当土壤pH和碳酸氢根含量偏高时,只要其他栽培管理措施得当,亦能够有效克服猕猴桃缺铁黄化问题;相反,如果其他栽培管理措施不得当,则易造成缺铁黄化。换言之,高pH和碳酸氢根是诱发猕猴桃叶片缺铁黄化的必要不充分条件。本研究还表明,与健康园相比,黄化园土壤阳离子交换量偏低(P<0.05),有机质和交换性钙含量略低(P<0.20) (图6),且有机质和交换性钙均与阳离子交换量正相关(数据未列出)。据报道,当陕西关中地区土壤有机质小于2.8%时,随着有机质的增加,阳离子交换量增加[30]。这些结果说明,猕猴桃园叶片黄化与土壤阳离子交换能力不足有关。
为了验证猕猴桃叶片黄化诱因分析结果的可靠性,本研究开展了田间缺铁诊断和施肥矫治试验。结果表明,随着猕猴桃叶片黄化加重,叶片邻二氮菲铁含量下降(图6),说明本研究所选的2个黄化果园存在缺铁问题。值得注意的是,仅园1黄化叶邻二氮菲浸提铁含量低于缺铁诊断临界值5.084 mg/kg;而园2轻度和重度黄化叶邻二氮菲浸提铁含量分别为5.18和6.18 mg/kg,高于临界值5.084 mg/kg (图5,图6)。经了解,园2农户在缺铁诊断前1个月全园均匀喷施过含铁叶面肥,这说明前期叶片喷铁肥会影响猕猴桃叶片邻二氮菲浸提铁的绝对含量,但不影响绿叶和黄叶之间的差异,再次证实邻二氮菲浸提铁适于田间猕猴桃缺铁黄化诊断。相反,施用铁肥后,黄化叶片全铁含量虽略有升高,但和健康园差异未达显著水平(图6),再次说明在猕猴桃缺铁诊断方面,叶片全铁诊断效果不及邻二氮菲浸提铁。考虑到土施铁肥效果和持久性整体优于叶施,故本研究选择了两种在猕猴桃上土施效果较好的铁肥(EDDHA铁和蓝铁矿)进行了黄化矫治试验[20]。结果表明,施用铁肥31天后,黄化叶SPAD和邻二氮菲铁均升高(图6),矫治效果良好,这与桃[43]、葡萄[49]、梨[50]上的研究结果一致,说明土施EDDHA铁和蓝铁矿均可作为陕西关中地区猕猴桃缺铁黄化防治的有效方法。不仅如此,施铁能够消除黄化叶片中钾和硝态氮的累积(图6),与黄化叶养分特征的分析结果相吻合(图3,图4a),说明猕猴桃黄化叶片中钾和硝态氮的累积主要是由缺铁造成的。
4. 结论
叶片鲜样邻二氮菲铁最适于猕猴桃缺铁黄化诊断,其临界浓度为5.084 mg/kg。陕西关中地区猕猴桃园叶片黄化主要是由土壤重碳酸盐诱发缺铁引起的,并与土壤阳离子交换量偏低有关;黄化叶中钾和硝态氮的累积是由缺铁造成的。因此,生产上应注意黄化园铁肥的补充和土壤阳离子交换能力的提升。
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图 2 猕猴桃叶片SPAD与不同方法浸提铁的相关性
注:FePhen—鲜样, 邻二氮菲浸提铁;Fe1MHCl·DW—干样,1 mol/L盐酸浸提铁;Fe0.1MHCl·DW—干样,0.1 mol/L盐酸浸提铁;Fe1MHCl·FW—鲜样,1 mol/L盐酸浸提铁;FeTotal—干样,全铁。n=64,R20.001=0.1614。
Figure 2. Correlations between kiwifruit leaf SPAD and iron concentrations in various extracts
Note: FePhen—Phenanthroline extracted Fe in fresh leaves; Fe1MHCl·DW—1 mol/L HCl extracted Fe in dry leaves; Fe0.1MHCl·DW—0.1 mol/L HCl extracted Fe in dry leaves; Fe1MHCl·FW—1 mol/L HCl extracted Fe in fresh leaves; FeTotal—Total Fe in dry leaves. n=64, R20.001=0.1614.
图 3 猕猴桃果园不同黄化度叶片养分含量的差异
注:柱上不同小写字母表示相同指标在不同黄化度叶样间差异显著,ns表示差异不显著(P<0.05)。
Figure 3. Differences in leaf nutrient concentration among various chlorosis-scale leaves of kiwifruit orchards
Note: Different small letters above the bars represent significant difference among various chlorosis-scale leaves for the same parameter, and ns represents no significant difference (P<0.05).
图 4 猕猴桃不同黄化度叶片SPAD与叶片元素含量的相关性(a)及其随机森林分析(b)
注:图4a中红色圆点表示正相关,蓝色圆点表示负相关;圆点越大、颜色越深,表示相关性越高;仅有显著相关的两个指标之间以圆点显示(P<0.05),不相关的指标之间为空白。n=245。
Figure 4. Correlations (a) and random forest analysis (b) between SPAD and nutrient concentrations of various chlorosis-degree kiwifruit leaves
Note: In Fig. 4a, the red and blue color of the circles represent the positive and negative sign of the correlations, respectively. Both the size and the color shade of the circles are proportional to the correlation coefficient value. Only significant correlations (P<0.05) are displayed and the non-significant correlations are left blank. n = 245.
图 6 猕猴桃黄化园与健康园土壤肥力参数的差异
注:JY代表健康园,HY代表黄化园。CEC—阳离子交换容量。图中虚线旁数值代表适宜范围的高值和低值边界,图中单个虚线代表高值边界,碳酸氢根数值代表诱发黄化的临界浓度范围。土壤肥力参数的适宜范围除pH、碳酸氢根和阳离子交换量分别参考李百云等[28]、Boxma[29]和郭兆元[30]外,其余参数均参考Wang等[31]。
Figure 6. Comparison in soil fertility parameters between healthy and chlorotic kiwifruit orchards
Note:JY represents healthy orchard, and HY represents chlorotic orchard. CEC—Cation exchange capacity. The values next to dashed lines represent the high and low limits of optimum ranges, single dashed line in one figure represent the high limit of the optimum ranges, and the values in the HCO3− figure represent the critical concentration range for bicarbonate-induced chlorosis. The optimum range is summed from Li et al (pH)[28], Boxma (HCO3−)[29], Guo ( CEC)[30] and Wang et al (other parameters)[31].
图 7 猕猴桃黄化园施用铁肥对叶片SPAD和元素含量的影响
注:柱上不同小写字母表示相同指标在不同黄化度叶样间或不同施肥处理间差异显著,ns表示差异不显著(P<0.05)。
Figure 7. Effects of Fe fertilizers on leaf SPAD and element concentration in chlorotic kiwifruit orchards
Note: Different small letters above the bars represent significant difference among various chlorosis-scale leaves or different fertilizer treatments for the same parameter, and ns represents no significant difference (P<0.05).
表 1 不同黄化度猕猴桃叶片的SPAD值和邻二氮菲铁含量
Table 1 SPAD and phenanthroline-extractable iron concentration in kiwifruit leaves in different chlorosis degrees
叶片
LeavesSPAD 邻二氮菲铁 FePhen
(mg/kg, FW)健康园绿叶
Green leaves in healthy orchard45.19±2.73 a 5.64±0.38 a 黄化园绿叶
Green leaves in chlorotic orchard45.84±3.81 a 5.66±0.19 a 轻度黄化叶
Slightly chlorotic leaves25.28±3.57 b 2.94±0.14 b 重度黄化叶
Severely chlorotic leaves10.64±2.61 c 2.21±0.11 c 注:同列数据后不同小写字母表示相同指标在不同黄化度叶样间差异显著 (P<0.05)。
Note: Values followed by different lowercase letters in a column represent significant difference among various chlorosis-scale leaves for the same parameter (P<0.05).表 2 猕猴桃黄化园叶片养分对叶片SPAD值的通径分析
Table 2 Path analysis of leaf elements on leaf SPAD value in chlorotic kiwifruit orchards
养分
Nutrient直接通径系数
Direct path coefficient间接通径系数 Indirect path coefficient 决策系数
Decision coefficientK FePhen NO3−-N P FeTotal Mn Mg Na Cl K −0.367 −0.199 −0.183 −0.079 0.049 −0.038 0.0198 −0.0034 −0.0026 0.454 FePhen 0.354 0.206 0.119 0.047 −0.088 0.046 0.0286 0.0042 0.0101 0.390 NO3−-N −0.283 −0.237 −0.149 −0.060 0.033 −0.011 −0.0032 −0.0042 −0.0036 0.327 P −0.095 −0.306 −0.175 −0.180 0.040 −0.028 0.0011 −0.0076 0.0013 0.133 FeTotal −0.126 0.143 0.247 0.074 0.030 0.034 0.0114 0.0005 0.0004 −0.120 Mn 0.155 0.089 0.105 0.020 0.017 −0.027 −0.0193 −0.0011 −0.0049 0.079 Mg −0.124 0.059 −0.082 −0.007 0.001 0.012 0.024 −0.0095 −0.0088 0.018 Na −0.067 −0.019 −0.022 −0.018 −0.011 0.001 0.003 −0.0176 0.0025 0.015 Cl −0.063 −0.015 −0.057 −0.016 0.002 0.001 0.012 −0.0174 0.0026 0.015 -
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