Distribution of elemental interactions in Brussels sprouts plants, under the Treated Municipal Wastewater

Abstract

The distribution of the macro, micronutrients and heavy metal interactions in the various plant parts (roots, leaf, and sprout) of Brassica oleracea var. gemmifera (Brussels sprouts), was investigated in a greenhouse experiment of randomized block design, in Agrinion, Greece. The statistical design included two variables: (i) Treated Municipal Wastewater (TMWW), and (ii) fresh irrigation well water (control). The analytical data of plant and soil samples collected were processed statistically by means of regression analysis, ANOVA and t-test, using an SPSS package. The ultimate goal of the experiment was to establish a scientific basis for the safe re-use of TMWW in the irrigation of Brussels sprouts, and possibly of all vegetables, with least accumulation of heavy metals in the sprouts.

Keywords:

• distribution
• accumulation
• heavy metals
• essential nutrients
• elemental interactions
• Brussels sprouts
• irrigation
• Treated Municipal Wastewater

Introduction

Soil plant system is a vital part of the agricultural ecosystem. The continuous flow of nutrients, and heavy metals, originating from various natural or man made sources, does not only reflect the degree of their dynamics, but also it is directly related to plant growth, food production, contaminant pathways, and to environmental quality.

Increased supply of the system with either essential nutrients or heavy metals, via treated wastewater re-use, may actively affect their uptake by plants, and thereby influence, positively or negatively, their consecutive accumulation and plant growth. In this respect, the interactions between these elements seem to play an important role, either in the soil-root interface (Bolan et al. 2005), or within the plant (Mengel et al. 2001; Marschner 2002).

Although the mechanism of the interactions is not very well understood, a number of factors may cause their occurrence. These factors may be summarized as follows: in soils, various geochemical processes such as precipitation reactions, complexation of elements, and redox reactions (Bolan et al. 2005); In plants, ions of the same electrical charge, valency and diameter size compete with each other for binding sites due to the large number of competing ions (Marschner 2002). Under such conditions, the plasma membrane reacts similarly with the ions (Erdei and Trivedi 1991). As a result of the interactions, concentration changes of nutrients and heavy metals are continuously occurring, which eventually cause analogous effects on plant growth and on the environment.

The Treated Municipal Wastewater (TMWW) through its nutrient and heavy metal supply, in addition to the plant irrigation water (Kalavrouziotis et al. 2008), significantly enhances the possibility of interaction occurrence in the soil and in the plants (Kalavrouziotis et al. 2008a, b).

Elemental interactions occurring generally in plants have been reviewed by Adriano (2001) and Kabata-Pendias and Pendias (1995), Mortvedt et al. (1991) and Srivastava and Gupta (1996). However, most of the reported interactions refer to the leaves, and very few to the other plant parts (roots, edible parts), while others refer to the plant in general, without specifying the respective plant part (leaf, root etc.)

Preliminary work reported (Kalavrouziotis et al. 2008a, b) showed that significant interactions are taking place in the soil between the essential elements, and heavy metals, as well as the chemical and physical properties of the soil (Kalavrouziotis et al. 2008a). Similarly, in another work, which is in the process of being published, they report that the TMWW re-use in Brassica oleracea var. Italica (broccoli) favored and intensified the synergistic interactions: Ca×Fe, K×P and Fe×Ni in the plant roots. They also found that the interactions N×Zn and P×Zn are taking place concomitantly in the roots, leaves a heads of broccoli plants, while the Fe×Ni, Mn×B occur in the roots and heads. Furthermore it was shown that under the TMWW effect, a series of statistically significant interactions are taking place in the sprouts of Brussels sprouts plants such as: N×Zn, Mg×Fe, Fe×Zn, and many others which have been tabulated in a special table (Kalavrouziotis et al. 2009).

As the interactions could act as plant growth factors, and as a means for environmental quality upgrade, they merit more attention and a detailed study, especially under long-term TMWW re-use, which may cause significant elemental concentration changes in both soil and plants, affecting, respectively, crop quality, consumer's health status and environmental quality.

On the other hand, the lack of relevant information regarding the distribution in the various plant parts of the nutrients and especially of heavy metal interactions under the TMWW, increases the necessity for a meticulous and especially detailed investigation of these interrelationships, which reflect significant health and environmental quality implications.

Consequently, the purpose of the present study is to examine, identify and shed light on the dynamics of occurrence and distribution of the interactions between the essential nutrients (N, P, K, Ca, Mg, Mn, Zn, Fe, B, and Cu) and heavy metals (Cd, Ni, Co and Pb) in Brassica oleracea var. gemmifera (Brussels sprouts) plant, and more specifically in its various parts (roots, leaves and sprouts), under the effect of the TMWW re-use. The ultimate goal is to establish a scientifically sound basis for the TMWW re-use as a source for irrigation water of vegetables and of other crops as well.

Materials and methods

An experiment of randomized block design was conducted in a greenhouse of the University of Ioannina, Department of Environmental Management and Natural Resources, Agrinion, Greece, in order to study the comparative effects of the Treated Municipal Wastewater (TMWW) and ordinary well irrigation water (control), on the speciation of the interactions between macro, micronutrients, heavy metals, in the various plant parts of Brassica oleracea var. gemmifera (roots, leaves and sprouts).

The statistical design included two irrigation treatments, i.e. (a) TMWW, and (b) control (ordinary well irrigation water) in six replications with a total number of 2×6 = 12 experimental plots of 2.5×1.8 m = 4.5 m² size.

The plots were separated by dikes of 0.1 m height. Brussels sprout plants were transplanted in rows, 0.8 m apart from each other, while the distance between the plants in the row, was 0.5 m.

Transplanting was carried out on 11 December 2005 and sampling of roots and leaves eight, and 16 weeks, and of the sprouts 16 weeks, after planting, i.e. 20 April 2006. Also, soil samples were taken (0–30 cm depth) at the commencement of the experiment and eight and 16 weeks later, respectively.

The treated wastewater was supplied by the Biological Treatment Plant of the Messologion Municipality.

The TMWW and the Control were applied 13 times during the plant growth period, by means of a special watering can, at a rate of 30 l per application per 4.5 m², the total volume of each treatment applied being 13×30 = 390 l per 4.5 m² or 867 mm/ha, i.e. 867 m³/ha. The irrigation time was determined at 50–60% depletion of the soil water holding capacity.

The collected analytical data of plant and soil material was processed statistically by regression analysis, ANOVA, and t-test, using an SPSS package.

Chemical analyses

Plant material

Each root sample was placed in a plastic sieve and was flushed with low pressure tap water until the complete removal of the soil particles. Then, root, leaf, and sprout samples, were washed with deionized water, followed by cleaning with a dilute solution of 0.005% HCl, and then they were thoroughly washed, by means of a special detergent (alconox 0.1%), and rewashed repeatedly (four times) with distilled water, left to drain on a filter paper, and dried in a ventilated oven at 70°C. They were then ground by means of a special hammer mill to 20 mesh size, and were ready for chemical analysis. The plant samples were dry mineralized by ashing 1.000 g in a muffle furnace at 500°C for 10–12 h, and the ash was dissolved in a 50:50 (v/v) H₂O: HCI solution (Westerman 1990). The heavy metals Pb, Cd, Co and Ni, were determined by a Variant AAS (type AA-IO) (Sakata 1987).

Soil analysis

Soil samples were dried, ground and analyzed as follows: Available P by the method of Olsen et al. (1954). Exchangeable K and Mg were extracted with 1M MNH₄Ac pH7.0 (Lanyon and Heald 1982) and measured by flame photometry, while Mn, Zn, Cu and Fe, and the heavy metals, Pb, Ni, Co and Cd, were extracted with DTPA solution Ure (1995), and measured by means of Atomic Absorption Spectrophotometer, using a Variant AAS, type (AA-IO) (Sakata 1987). The EC was determined by a conductivity meter, CaCO₃ by means of Bernard asbestometer, organic matter (OM) by wet digestion of Walkley-Black, and pH by a commercial pH-meter, as classically suggested by Jackson (1958). The data on soil analysis are shown in Table 1.

Table 1. Chemical characteristics of the soil^a studied at the commencement of the experiment.

Chemical properties	Level^b	Available micronutrients	Level^b
PH	7.48	Mn mg/kg	12.94
CaCO3 %	1.75	Zn mg/kg	2.87
OM %	1.11	Fe mg/kg	2.03
EC mS/m	0.869	B mg/kg	0.28
Available macronutrients		Cu mg/kg	1.28
P-Olsen mg/kg	20.61	Available heavy metals
K-exch. mg/kg	131.7	Cd mg/kg	0.006
Ca-exch me/100g	1.37	Co mg/kg	0.270
Mg-exch. me/100g	0.19	Ni mg/kg	0.74
		Pb mg/kg	2.71
^aThe soil was treated for the first time with Treated Municipal Wastewater; ^bMean of six values.

Irrigation water and TMWW analysis

The well irrigation water and the TMWW were analyzed before their application by methods suggested by the Association of Official Analytical Chemists (AOAC 1996) as follows: pH was determined electrometrically by means of a commercial pH-meter, while SAR was calculated (Richards 1954). Total N was found by the Kjeldhal method, i.e. by digesting a water and TMWW sample with H₂SO₄ to convert organic N to NH₃, followed by distillation after alkalization, and total N determined titrimetrically.

The Cl^- anions were determined in 100 ml of irrigation water or in Treated Municipal Wastewater, to which 1 ml of acidified indicator was added, composed of 250 mg s-diphenylcarbazone, 4 ml HNO₃ and 30 mg of xylene cyanol FP in 100 ml alcohol. Then the solution was titrated with 0.0141 N Hg (NO₃)₂ to a definite purple end point.

Also, Ca and Mg were measured by titration with ethyldiaminetetraacetic acid (Versenate) (Richards 1954). Ammonium acetate and dispersed organic matter was removed from the sample prior to titration with versenate; evaporation of an aliquot from water or TMWW until its dryness, followed by treatment with aqua regia (three parts of conc. HCl and one part of conc. nitric acid). The residue was dissolved in a quantity of water equal to the original volume of the aliquot, taken for treatment. First Ca was determined by placing a 5 ml aliquot and by diluting it with distilled water to approximately 25 ml. Then, five drops of the 4N NaOH were added, and approximately 50 ml of ammonium purpurate indicator composed of 0.5 g of ammonium purpurate in 100 g of powered potassium sulfate. The solution was then titrated with 0.01N versenate using a 10 ml microburet, the end of the titration being determined by the color change, from orange to lavender or purple. In turn, (Ca + Mg) was determined in an aliquot of 5 ml, which was pipetted into a 125 Erlenmeyer flask. It was diluted to approximately 25 ml, and 0.5 ml (10 drops) of the ammonium chloride-ammonium hydroxide buffer solution was added, and also three to four drops of Eriochrom black T indicator, composed of 0.5 g Eriochrom T indicator (F241), 4.5 g of hydroxylamine hydrochloride in 100 ml of 95% alcohol and the solution was titrated. The calculations were made by means of the following relation:

The K in water or in the wastewater was determined by pretreatment in a buffer solution, and it was measured by using an Atomic Absorption Spectrophotometer (AOAC 1996).

Total P was determined by digesting an aliquot of the sample with persulfate, and it was measured by direct colorimetric analysis, by developing the phosphomolybdate complex, reduced to intensely blue color by means of ascorbic acid. The color intensity was measured colorimetrically. The water Fe, Mn, Zn, Cu and Cr contents were determined by filtering a known volume of the sample through 0.45 m membrane filter. The membrane with the residue was then transferred into a 250 ml beaker, and 3 ml of HNO₃ were added. They were covered with watch glass and heated gently to dissolve the membrane. The heat was then increased to evaporate the solution to dryness. After cooling, 3 ml of HNO₃ were added until digestion was complete. Then 2 ml of HCl (1 + 1) were added and reheated gently to dissolve the residue. The watch glass and the beaker were washed with H₂O and the solution was filtered. The filtrate was diluted to concentration within the range of the instrument. Then the metals in solution were determined by means of an Atomic Absorption Spectrophotometer by setting the instrument to the following wave lengths: Fe = 248.34 nm, Mn = 6274.5 nm, Zn = 213.9 nm, Cu = 324.7 nm and Cr = 357.9 nm.

Arsenic (As) was determined by evaporating 0.5 l to dryness, and by adding a small quantity of NaCO_3. The filter with the residue was then washed thoroughly with hot water. The alkaline filtrate was diluted to definite volume, and it was used for the determination of the AOAC (1996).

Soluble B was determined in the irrigation water without pretreatment, and in the treated wastewater by pretreatment of the sample, i.e. by filtering through 0.4–0.45 m filter and by acidification of the filtrate with HNO₃ up to pH < 2.0. Curcumine (Eastman No. 1179) was used for the development of the red color and its intensity was measured by means of a spectrophotometer at 540 nm, with minimum light path of 1 cm (American Public Health Association [APHA] 1992).

Finally, sodium (Na) in the wastewater was determined by pretreatment, following the same procedure mentioned above for the B, and the concentration of Na in the filtrate was measured by means of flame photometer. The relevant analytical data are given in a previous publication (Kalavrouziotis et al. 2008a).

Results and discussion

An important aspect associated with the TMWW re-use is the supply of plants with nutrients and heavy metals, which may accumulate in the various plant parts, including the edible ones.

The extent of this plant supply may either be due to the elements main effect or to the interactions, occurring between the various nutrients and heavy metals, either in the soil or within the plants. From the extensive and detailed regression analysis, between the macro, micronutrients and heavy metals (N, P, K, Ca, Mg, Mn, Zn, Fe, B, Cu, Cd, Co, Ni and Pb) contained in various plant parts of Brassica oleracea var. gemmifera, under both the control and the TMWW, respectively, the following were found:

In total 588 interactions occurred between these elements in roots, leaves and sprouts, of which 564 were statically significant. Also, 123 statistically significant interactions occurred in the soil. Table 2, reveals the following:

1. Most of these interactions in both plant and soil, were synergistic (in plants 322, in soil 69), being distributed under the two treatments studied, as follows: In plants: (i) Synergistic interactions: Under TMWW 150 or 53.38%, and under control 172 or 60.78%; (ii) Antagonistic interactions: Under TMWW 93 or 33.38%, and under control 76 or 26.86%. In soil: (i) Synergistic interactions under TMWW 41 or 59.42% and under control 28 or 51.86%, (ii) Antagonistic interactions: under TMWW 18 or 26.08% and under control 19 or 35.19%.

2. The various types of interactions, i.e. synergistic, antagonistic etc., were as to their total number, approximately equally distributed, under both the effect of TMWW, and control, respectively, in the roots, leaves and sprouts, i.e. (a) in roots: under TMWW 119, and under control 117, (b) in leaves: under TMWW 112, and under control 119, and (c) in sprouts: under TMWW 50 and under control 47. The differences observed in the number of the same type of interactions in a given plant part, under the effect of either the TMWW or control, respectively (for example, synergistic: roots TMWW 63 and control 72, were shown to be statistically non-significant according to t-test, but they were highly correlated (Table 3). A similar trend was found for the interactions that occurred in the soil.

3. The combined type of interactions, i.e. ‘Antagonistic-synergistic’ or vice versa, were generally very limited in number in both plant and soil, but in the plants they were much more under TMWW than under the control. However in the soil, the ‘Syn-ant’ interaction type were equally distributed under TMWW and control, respectively, but the ‘Ant-syn’ type were almost doubled under the control, in comparison to those under the TMWW (Table 3).

Table 2. Essential elements end heavy metal interactions occurring in Brassica olevacea var, gemmifera (Brussels sprouts) plants (roots, leaves and sprouts) as well as in soil, under the effect of Treated Municipal Wastewater (TMWW) and fresh irrigation water (control).

	Roots		Leaves		Sprouts		Total		Soil
Type of interactions	TMWW	Control	TMWW	Control	TMWW	Control	TMWW	Control	TMWW	Control
Synergistic	63 (52.94)	75 (64.10)	54 (48.2)	54 (45.38)	33 (66.0)	43 (91.49)	150 (53.38)	172 (60.78)	41 (59.42)	28 (51.86)
Antagonistic	42 (35.29)	39 (33.33)	48 (42.86)	36 (30.25)	3 (6.0)	1 (2.13)	93 (33.09)	76 (26.86)	18 (26.08)	19 (35.19)
‘Syn-Ant’	11 (9.25)	1 (0.86)	4 (3.58)	14 (11.76)	12 (24.0)	2 (4.25)	27 (9.62)	17 (6.00)	3 (4.35)	3 (5.55)
‘Ant-Syn’	3 (2.52)	2 (1.71)	6 (5.36)	15 (12.61)	2 (4.0)	1 (2.13)	11 (3.91)	18 (6.36)	7 (10.14)	4 (7.40)
Total	119 (100)	117 (100.00)	112 (100.00)	119 (100.00)	50 (100)	47 (100)	281 (100.00)	283 (100.00)	69 (100.00)	54 (100.00)
The figures in parentheses refer to percentage.

Table 3. Comparison by means of t-test, of the total number of the various types of interactions occurring in the roots, leaves and sprouts of Brassica olevacea var. gemmifera (Brussels sprouts) under the respective effects of TMWW and control.

	Correlation
Plant part	h	sign	t	Sign
Roots	0.985	0.015*	0.109	0.920ns
Leaves	0.954	0.046*	0.343	0.754ns
Sprouts	0.943	0.057ns	0.117	0.915ns
Total	0.974	0.024*	0.057	0.958ns
*Significant at p 0.05; ns, non-significant.

Based on the above findings, it may be concluded that the interactions between the essential elements, and heavy metals, in Brussels sprouts plants, under either TMWW or control, are basically characterized by synergism, and secondarily by antagonism, and to a very limited extent by ‘Syn-ant’ or vice versa.

Distribution of concomitantly occurring interactions in various plant parts

The interactions found were classified with respect to the space of their occurrence in the plant, and in relation to the two treatments studied, as follows:

1. Independently of the applied treatments and concomitantly occurring in the pathway of:

   1. ‘Root-leaf-sprout’

   2. ‘Root-leaf’

   3. ‘Leaf-sprouts’.

2. Occurring in only one of the three plant parts studied, i.e.:

   1. Only in roots

   2. Only in leaves

   3. Only in sprouts.

3. Occurring in dependence of the applied treatments:

   1. In the roots under the TMWW

   2. In the roots under the control

   3. In the leaves under the TMWW

   4. In the leaves under the control

   5. In the sprouts under the TMWW

   6. In the sprouts under the control.

In the present paper, due to the limited space, only the interactions related to the above (a) pathways, will be discussed.

Interactions occurring in the ‘root-leaf-sprout’ pathway

In order to study the distribution of the interactions in various plant parts, it is necessary to develop their regression equations in each part, respectively. In the present study, the distribution of the interactions that occurred in the various plant parts of Brassica oleracea var. gemmifera (Brussels sprouts) (Table 2) was carefully examined, and conclusions as to their concomitant occurrence in more than one plant organ (part) was studied. Thus, information was obtained as to the dynamics of the interactions in the Brussels sprout plants.

It is underlined that the present work is concerned only with interactions occurring concomitantly in the plants parts studied, i.e. roots, leaves and sprouts, and more specifically in the already mentioned pathways.

In a previous preliminary study of Kalavrouziotis et al. (2008b), the interactions N×Zn and P×Zn were also shown to be characterized by concomitant occurrence in the above three plant parts of Brassica oleracea var. Italica (broccoli). Quantification of the contribution of the interactions found in the present work, mentioned in Table 4, showed that they contributed significant quantities of essential plant nutrients along the ‘root-leaf-sprout’ pathway (Table 5).

Table 4. Regression equations of interactions between plant nutrients, concomitantly occurring in various ‘root-leaf-sprouts’ pathway of Brassica oleracea var. gemmifera (Brussels sprouts) under the effect of TMWW and control, respectively.

		TMWW			Control
Interactions	Plant part	Regression equation	R	Type	Regression equation	R	Type
N×K	Roots	K = − 0.509(N)^2+2.139(N) + 0.019	0.890**	S	K = − 1.034(N)^2+3.85(N) − 1.054	0.859**	S
	Leaves	K = − 0.324(N)^2+2.875(N) − 1.571	0.959***	S	K = − 0,004(N)^2+1.231(N) − 0.104	0.981***	S
	Sprouts	K = − 0.401(N)^2+3.209(N) − 3.174	0.998***	S	K = 0.690(N)^2−3.793(N) + 8.109	0.648ns	S
Zn×K	Roots	K = 0.003(Zn)^2−0.066(Zn)1.836	0.867**	S	K = 0.059(Zn) + 0.593	0.875**	S
	Leaves	K = − 0.005(Zn)^2+0.417(Zn) − 3.416	0.888**	S	K = − 0.011(Zn)^2+0.710(Zn) − 6.724	0.885**	S
	Sprouts	K = − 0.001(Zn)^2+0.119(Zn) − 0.438	0.865**	S	K = 0.002(Zn)^2−0.105(Zn) + 4.507	0.709ns	S
Cu×K	Roots	K = − 0.005(Cu)^2+0.191(Cu) + 0.867	0.860**	S	K = − 0.006(Cu)^2+0.216(Cu) + 0.698	0.687*	S
	Leaves	K = − 0.068(Cu)^2+1.41(Cu) − 2.041	0.927***	S	K = − 0.078(Cu)^2+1.498(Cu) − 2.193	0.802**	S
	Sprouts	K = − 0.225(Cu)^2+3.021(Cu) − 6.899	0.943***	S	K = 1.349(Cu)^2−15.19(Cu) + 45.558	0.562ns	S
K×N	Roots	N = 0.089(K)^2+0.7(K) − 0.275	0.873**	S	N = − 0.821(K)^2+4.26(K) − 3.187	0.810**	S
	Leaves	N = 0.001(K)^2+0.784(K) + 0.189	0.932**	S	N = − 0.044(K)^2+1.078(K) − 0.157	0.983***	S
	Sprouts	N = 1.20(K)^2−5.44(K) + 8.730	0.993**	S	N = − 7.5(K)^2+46.892(K) − 69.968	0.684ns	S
Zn×N	Roots	N = − 0.003(Zn)^2+0.172(Zn) − 1.051	0.813**	S	N = − 0.003(Zn)^2+0.24(Zn) − 1.810	0.931***	S
	Leaves	N = 0.172(Zn) − 1.245	0.952***	S	N = − 0.003(Zn)^2+0.315(Zn) − 2.837	0.900***	S
	Sprouts	N = 0.002(Zn)^2−0.056(Zn) + 2.604	0.885**	S	N = − 0.016(Zn)^2+1.269(Zn) − 21.103	0.872*	S
N×Mn	Roots	Mn = − 15.16(N)^2+51.445(N) − 14.648	0.611*	S	Mn = − 1.374(N)^2+9.53(N) + 13.568	0.620*	S
	Leaves	Mn = 3.4465(N)^2−11.053(N) + 46.522	0.804*	S	Mn = 2.334(N)^2−8.188(N) + 42.660	0.805**	S
	Sprouts	Mn = − 1.311(N)^2+13.09(N) − 7.16	0.834**	S	Mn = − 46.56(N)^2+289.55(N) − 424.78	0.858*	S
Zn×Mn	Roots	Mn = 0.139(Zn)^2+6.647(Zn) − 49.558	0.745*	S	Mn = − 0.022(Zn)^2+1.60(Zn) + 1.323	0.785*	S
	Leaves	Mn = 0.049(Zn)^2−0.853(Zn) + 41.440	0.664*	S	Mn = − 0.023(Zn)^2+1.666(Zn) + 17.723	0.517ns	S
	Sprouts	Mn = 0.001(Zn)^2+0.407(Zn) + 3.868	0.876*	S	Mn = − 0.057(Zn)^2+4.812(Zn) − 77.095	0.794*	S
N×Zn	Roots	Zn = − 16.574(N)^2+56.076(N) − 19.40	0.878**	S	Zn = − 9.809(N)^2+42.419(N) − 13.202	0.845**	S
	Leaves	Zn = 0.289(N)^2+3.261(N) + 10.35	0.957***	S	Zn = − 2.176(N)^2+15.957(N) − 0.494	0.954***	S
	Sprouts	Zn = − 3.923(N)^2+34.345(N) − 29.665	0.888*	S	Zn = − 30.592(N)^2+198.512(N) − 281.38	0.916**	S
K×Zn	Roots	Zn = − 8.308(K)^2−17.284(K) + 23.616	0.863**	S	Zn = 6.321(K)^2−7.847(K) + 14.771	0.882**	S
	Leaves	Zn = 0.96(K)^2−1.986(K) + 15.758	0.801**	S	Zn = − 1.715(K)^2+14.375(K) − 0.750	0.977***	S
	Sprouts	Zn = − 19.92(K)^2+127.12(K) − 160.494	0.877*	S	Zn = 13.75(K)^2−61.507(K) + 98.251	0.672ns	S
K×Cu	Roots	Cu = 5.114(K)^2−12.14(K) + 10.606	0.894**	S	Cu = 4.715(K)^2+21.561(K) − 15.31	0.762*	S
	Leaves	Cu = 0.352(K)^2−0.94(K) + 3.59	0.992***	S	Cu = − 0.182(K)^2+2.236(K) + 0.765	0.753*	S
	Sprouts	Cu = 7.92(K)^2−42.75(K) + 62.53	0.876*	S	Cu = 42.5(K)^2−258.934(K) + 399.49	0.991***	S
Zn×Fe	Roots	Fe = − 0.46(Zn)^2+18.34(Zn) + 161.62	0.321ns	A	Fe = − 0.017(Zn)^2+9.264(Zn) + 139.096	0.718ns	S
	Leaves	Fe = − 0.072(Zn)^2+5.947(Zn) − 16.87	0.749*	S	Fe = − 0.229(Zn)^2+12.6(Zn) − 79.172	0.778*	S
	Sprouts	Fe = − 0.26(Zn)^2+22.284(Zn) − 391.46	0.874*	S	Fe = − 0.199(Zn)^2+17.492(Zn) − 291.67	0.804*	S
S, synergistic; *, **, ***Significant at p 0.05, p 0.01, p 0.001 probability level, respectively.

Table 5. Elemental contribution in macro and micronutrients by concomitantly occurring interactions between the above elements in the ‘roots-leaf-sprouts’ pathway of Brassica oleracea var. gemmifera, under the effect of TMWW and control, respectively.

		TMWW			Control			Mean contribution^b
Interactions	Contributed element^a	Roots	Leaves	Sprouts	Roots	Leaves	Sprouts	TMWW	Control
N×K	K	0.722	4.162	0.715	1.053	4.576	0.000
Zn×K	K	1.452	4.623	0.546	1.941	4.697	0.000
Cu×K	K	0.584	4.572	0.601	0.983	3.893	0.000
Mean	K	0.919	4.452	0.541	1.326	4.389	0.000	1.971	1.905
K×N	N	1.065	2.986	0.980	1.805	3.734	0.000
Zn×N	N	0.880	3.956	1.257	2.339	3.721	1.194
Mean	N	0.973	3.471	1.119	2.072	3.728	0.597	1.854	2.132
N×Mn	Mn	12.236	34.460	5.092	9.831	21.069	6.329
Zn×Mn	Mn	11.682	29.068	6.240	11.290	13.469	8.128
Mean	Mn	11.959	31.764	5.666	10.561	17.269	7.229	16.463	11.686
N×Zn	Zn	13.149	19.647	10.125	21.255	11.902	9.970
K×Zn	Zn	16.779	14.193	9.523	28.568	12.027	0.000
Mean	Zn	14.964	16.920	9.824	24.912	11.965	4.985	13.903	13.954
K×Cu	Cu	8.828	4.404	1.675	0.000	16.961	0.095	4.969	5.685
Zn×Fe	Fe	0.000	65.24	35.159	0.000	53.934	37.582	33.47	30.505
^aK%, N%, Mn, Zn, Cu, and Fe in g/g; ^bIrrespective of the plant part.

Examination of the data of this table shows that the contribution in Mn and Fe by the above-mentioned interactions, under the influence of TMWW is higher than under the control. On the other hand, the mean contribution in K and Zn is approximately equal under both the TMWW and control, respectively. However, the contribution with respect to Cu is higher under the control, but the contribution in N, is much higher, even though it would have been expected the opposite, due to the higher concentration of N and Cu in the TMWW (Table 1). The explanation of this discrepancy is most possibly based on the extent of availability of these elements in the TMWW and control, respectively.

Thus, Cu may be organically bound, forming insoluble Cu-humic complexes in TMWW, which is rich in humic acid. Under such conditions, the amount of organically bound Cu increases above pH 7 (the mean pH of the TMWW is 7.56, Table 1), while the concentration of free Cu at higher pH is much lower (Stevenson and Cole 1999). Similarly, the availability of N in TMWW is lower than that in the control, where N is mostly found as available NO₃, while in the TMWW, N is mostly in organic form, which has to be subjected to nitrification, before it can become available to plants.

Interactions occurring along the ‘root-leaf’ pathway

It was found that 17 interactions between macro, micronutrients and heavy metals were taking place concomitantly along the ‘root- leaf’ pathway, under the TMWW and control, respectively (Table 6). It can be seen that these interactions differ from those of Table 4, which occur along the ‘root-leaf-sprout’ pathway, in that they are mainly antagonistic, and that they include both macro-, micronutrients, and heavy metals, while the former, are almost all synergistic, and include only essential macro and micronutrients.

Table 6. Regression equations of interactions between macro, micronutrients and heavy metals, concomitantly occurring in the ‘root-leaf’ pathway of Brassica oleracea var. gemmifer (Brussels sprouts), under the effect of TMWW and control, respectively.

		TMWW			C ontrol
Interactions	Plant part	Regression equation	R	Type	Regression equation	R	Type
N×Co	Root	Co = 1.836(N)^2−8.101(N) + 8.738	0.866**	A	Co = 0.497(N)^2−3.616(N) + 5.824	0.862**	A
	Leaf	Co = 0.413(N)^2−3.387(N) + 6.851	0.966***	A	Co = 0.394(N)^2−3.582(N) + 8.044	0.964***	A
Zn×Co	Root	Co = 0.003(Zn)^2−0.362(Zn) + 7.983	0.870**	A	Co = 0.007(Zn)^2−0.512(Zn) + 8.951	0.870**	A
	Leaf	Co = 0.009(Zn)^2−0.601(Zn) + 10.076	0.923***	A	Co = 0.003(Zn)^2−0.455(Zn) + 10.362	0.932***	A
Cu×Co	Root	Co = 0.067(Cu)^2−1.444(Cu) + 7.531	0.852**	A	Co = − 0.012(Cu)^2−0.305(Cu) + 4.206	0.698*	A
	Leaf	Co = 0.063(Cu)^2−1.353(Cu) + 6.595	0.890**	A	Co = 0.076(Cu)^2−1.588(Cu) + 8.030	0.778*	A
K×Cd	Root	Cd = 0.004(K)^2−0.841(K) + 1.917	0.831**	A	Cd = 0.553(K)^2−2.88(K) + 3.729	0.853**	A
	Leaf	Cd = 0.068(K)^2−0.724(K) + 1.906	0.991***	A	Cd = 0.05(K)^2−0.627(K) + 1.665	0.911***	A
Mn×Cd	Root	Cd = 0.001(Mn)^2−0.058(Mn) + 1.379	0.609*	A-S	Cd = 0.001(Mn)^2−0.076(Mn) + 2.01	0.636*	A
	Leaf	Cd = 0.001(Mn)^2−0.149(Mn) + 5.03	0.829**	A	Cd = 0.001(Mn)^2−0.142(Mn) + 4.616	0.750*	A
Co×Cd	Root	Cd = − 0.1(Co)^2+0.608(Co) − 0.026	0.934***	S	Cd = − 0.113(Co)^2+0.729(Co) + 0.013	0.973***	S
	Leaf	Cd = − 0.115(Co)^2+0.719(Co) − 0.021	0.990***	S	Cd = − 0.102(Co)^2+0.72(Co) − 0.026	0.953***	S
Zn×Cd	Root	Cd = 0.003(Zn)^2−0.169(Zn) + 2.70	0.917***	A	Cd = 0.002(Zn)^2−0.141(Zn) + 2.54	0.919***	A
	Leaf	Cd = 0.001(Zn)^2−0.117(Zn) + 2.339	0.852**	A	Cd = − 0.003(Zn)^2+0.075(Zn) + 0.723	0.857**	A
Cu×N	Root	N = − 0.018(Cu)^2+0.392(Cu) − 0.306	0.870**	S	N = − 0.014(Cu)^2+0.426(Cu) − 0.505	0.861**	S
	Leaf	N = − 0.078(Cu)^2+1.374(Cu) − 1.965	0.879***		N = − 0.076(Cu)^21.367(Cu) − 2.045	0.823**	S
Cd×N	Root	N = 1.083(N)^2−2.117(N) + 1.79	0.924***	A	N = 1.201(Cd)^2−2.823(Cd) + 2.382	0.992***	A
	Leaf	N = 3.156(Cd)^2−5.942(Cd) + 3.933	0.934***	A	N = 2.546(Cd)^2−5.539(Cd) + 4.053	0.966***	A
Cu×Mn	Root	Mn = − 0.694(Cu)^2+10.847(Cu) − 10.861	0.707**	S-A	Mn = 0.049(Cu)^2+0.889(Cu) + 16.166	0.662**	S
	Leaf	Mn = 0.977(Cu)^2−5.052(Cu) + 44.506	0.771*	S	Mn = − 0.412(Cu)^2+7.742(Cu) + 16.664	0.763*	S
Cd×Mn	Root	Mn = − 2.919(Cd)^2−9.681(Cd) + 27.827	0.598*	A	Mn = 7.301(Cd)^2−16.167(Cd) + 28.730	0.648*	A
	Leaf	M = 9.002(Cd)^2−28.765(Cd) + 58.291	0.669*	A	Mn = 6.931(Cd)^2−19.551(Cd) + 48.57	0.745*	A
Cu×Zn	Root	Zn = − 0.10(Cu)^2+3.221(Cu) + 6.058	0.833**	S	Zn = − 0.327(Cu)^2+6.889(Cu) − 5.043	0.670*	S
	Leaf	Zn = − 0.628(Cu)^2+9.074(Cu) − 5.390	0.819**	S	Zn = − 0.243(Cu)^2+4.805(Cu) + 4.615	0.723*	S
Cd×Zn	Root	Zn = 6.61(Cd)^2−20.687(Cd) + 27.514	0.900**	A	Zn = − 18.551(Cd)^2−38.00(Cd) + 32.912	0.868**	A
	Leaf	Zn = 24.654(Cd)^2−38.806(Cd) + 27.832	0.889**	A	Zn = 17.09(Cd)^2−31.374(Cd) + 28.133	0.927***	A
Co×Zn	Root	Zn = 0.751(Co)^2−6.279(Co) + 27.679	0.886**	A	Zn = 1.662(Co)^2−11.616(Co) + 32.384	0.831**	A
	Leaf	Zn = 0.094(Co)^2−4.098(Co) + 27.72	0.892**	A	Zn = 0.546(Co)^2−5.349(Co) + 28.287	0.940***	A
Cd×Cu	Root	Cu = 8.458(Cd)^2−14.443(Cd) + 9.273	0.864**	A	Cu = 7.502(Cd)^2−12.58(Cd) + 8.967	0.861**	A
	Leaf	Cu = 6.158(Cd)^2−10.419(Cd) + 6.997	0.916***	A	Cu = 1.868(Cd)^2−5.815(Cd) + 7.409	0.808**	A
Co×Cu	Root	Cu = 0.723(Co)^2−4.325(Co) + 9.353	0.863**	A	Cu = 0.652(Co)^2−3.832(Co) + 8.838	0.815**	A
	Leaf	Cu = 0.456(Co)^2−2.767(Co) + 7.012	0.904	A	Cu = 0.417(Co)^2−2.79(Co) + 7.456	0.786*	A
Co×Ni	Root	Ni = 0.114(Co)^2+0.353(Co) + 4.613	0.793*	S	Ni = 0.111(Co)^2+0.141(Co) + 4.872	0.405ns	S
	Leaf	Ni = − 0.455(Co)^2+2.683(Co) − 0.10	0.767*	S	Ni = − 0.308(Co)^2+2.316(Co) − 0.072	0.937**	S
S, synergistic; A, antagonistic; S-A, synergistic-antagonistic; A-S, antagonistic-synergistic, *, **, ***Significant at p 0.05, 0.01, and 0.001 probability level, respectively.

As far as the contribution in nutrients and heavy metals along the ‘root-leaf’ pathway, Table 7 reveals the following: the mean net contribution in Ni and Mn is higher under TMWW, while only N is contributed at higher levels under the effect of the control. On the other hand, the contribution in Co, Cd, Zn and Cu is negative under both the effect of TMWW and control, respectively, their concentration in the dry matter, being reduced due to antagonistic interactions between the above elements, as shown in Table 6. Further detailed examination of Table 7 shows that the interactions net effect on Co under either TMWW or control, is equally negative, suggesting equal reduction of Co concentration in the ‘root-leaf’ pathway, while in the case of Zn, the interactions net effect is less negative under TMWW, and in the case of Cu and Cd is more negative than that under the control. These results showed in general that the interactions play an important role in the positive or negative change of the level of various nutrients and heavy metals in the plant pathways.

Table 7. Contribution of interactions in nutrients and heavy metals, occurring concomitantly in the ‘root-leaf’ pathway of Brassica oleracea var. gemmifera (Brussels sprouts), under the effect of TMWW and control, respectively.

		TMWW			Control			Average contribution^b
Interactions	Contributed element^a	Roots	Leaves	Sprouts	Roots	Leaves	Sprouts	TMWW	Control
N×Co	Co	−4.070	−4.193	−0.0050	−3.878	−4.781	3.160
Zn×Co	Co	−5.056	−4.881	1.200	−3.729	−5.798	0.000
Cu×Co	Co	−3.699	−4.549	0.830	−4.503	−4.899	0.000
Mean	Co	−4.275	−4.541	0.675	−4.037	−5.159	1.053	−2.714	−2.714
Mn×Cd	Cd	0.155	−1.62	0.000	−0.475	−1.441	0.071
Co×Cd	Cd	0.741	1.012	0.000	0.941	1.081	0.000
Zn×Cd	Cd	−0.814	−1.697	1.310	0.000	−0.814	0.000
K×Cd	Cd	−1.157	−1.199	0.350	−1.230	−0.688	0.000
Mean	Cd	−0.269	−0.877	0.415	−0.191	−0.466	0.018	−0.244	−0.213
Cu×N	N	1.110	1.615	1.013	2.117	5.604	0.000
Cd×N	N	−1.003	−2.556	0.000	−1.641	−2.732	0.000
Mean	N	0.054	−0.471	0.507	0.238	1.436	0.000	0.030	0.558
Cu×Mn	Mn	13.249	37.400	5.630	−1.696	16.780	0.000
Cd×Mn	Mn	−14.120	−21.420	0.000	0.086	−13.787	0.000
Mean	Mn	−0.436	7.99	2.815	−0.805	1.497	0.000	3.456	0.231
Cu×Zn	Zn	12.023	15.583	9.170	20.382	13.363	0.000
Cd×Zn	Zn	−14.614	−10.872	0.000	−18.652	−10.242	0.000
Co×Zn	Zn	−12.864	−14.709	0.000	−17.919	−12.908	0.000
Mean	Zn	−5.152	−3.333	3.057	−5.396	−3.262	0.000	−1.809	−2.886
Cd×Cu	Cu	−5.554	−3.583	0.000	−4.215	−4.452	0.440
Co×Cu	Cu	−5.057	−3.678	0.000	−3.744	−3.618	0.140
Mean	Cu	−5306	−3.631	0.000	−3.980	−4.035	0.290	−2.979	−2.575
Co×Ni	Ni	3.612	3.467	0.000	0.000	3.264	−0.750	2.360	0.838
^aThe units of the nutrients and heavy metals are: N% dm, Zn, Cu, Co, Cd, Ni in mg/g dm; ^bIrrespective of the plant part.

Interactions occurring in the ‘leaf-sprout’ pathway

Six interactions were found to take place concomitantly in the leaves and sprouts under the effect of TMWW or the control, respectively (Table 8). It was further shown that all of these interactions were synergistic and they occurred exclusively between essential macro and micronutrients. These results suggested that they contributed positively only essential nutrients throughout the above pathway, thus securing for the plants a regular flow of nutrients, favoring its normal growth (Table 8).

Table 8. Regression equations and their coefficients of interactions between macro and micronutrients concomitantly occurring in the ‘leaf-sprout’ pathway of Brassica oleracea var. gemmifera (Brussels sprouts) under the TMWW and control, respectively.

		TMWW			Control
Interactions	Plant part	Regression equation	R	Type	Regression equation	R	Type
Mn×N	Leaf	N = 0.002(Mn)^2+0.264(Mn) − 6.02	0.808**	S	N = 0.001(Mn)^2+0.044(Mn) − 1.00	0.762**	S
	Sprout	N = 0.004(Mn)^2+0.308(Mn) − 1.498	0.834*	S	N = 0.010(Mn)^2+0.484(Mn) − 2.509	0.973***	S
N×Fe	Leaf	N = 0.065(Fe) − 1.179	0.777**	S	N = − 0.001(Fe)^2+0.196(Fe) − 5.478	0.720**	S
	Sprout	N = 0.001(Fe)^2+0.232(Fe) − 6.328	0.843**	S	N = − 0.001(Fe)^2+0.076(Fe) − 0.931	0.959	S
Mn×K	Leaf	K = 0.003(Mn)^2+0.458(Mn) − 10.856	0.834**	S	K = 0.001(Mn)^2+0.064(Mn) − 1.805	0.812**	S
	Sprout	K = 0.008(Mn)^2+0.447(Mn) − 2.744	0.849*	S	K = − 0.001(Mn)^2+0.056(Mn) + 2.189	0.644ns	S
Fe×K	Leaf	K = − 0.001(Fe)^2+0.131Fe − 3.01	0.780**	S	K = − 0.001(Fe)^2+0.247(Fe) − 7.243	0.760**	S
	Sprout	K = − 0.001(Fe) + 0.178(Fe) − 4.355	0.909*	S − A	K = ….(Fe)^2+0.005(Fe) + 2.642	0.588ns	S
K×Mn	Leaf	Mn = 3.213(K)^2−13.212(K) + 49.644	0.697*	S	Mn = 1.402(K)^2−5.232(K) + 40.4170	0.860**	S
	Sprout	Mn = − 5.715(K)^2+39.524(K) − 45.189	0.835*	S	Mn = − 193.75(K)^2+1200.51(K) − 1833.450	0.808*	S
Fe×Zn	Leaf	Zn = 0.24(Fe) + 5.394	0.738*	S	Zn = 0.005(Fe)^2+0.881(Fe) − 16.201	0.809*	S
	Sprout	Zn = − 0.008(Fe)^2+1.506(Fe) − 29.431	0.891*	S	Zn = − 0.007(Fe)^2+1.258(Fe) − 17.577	0.873*	S
A, antagonistic; S, synergistic; S-A, synergistic-antagonistic; *, **, ***Significant at p 0.05, 0.01 and 0.001 probability level, respectively.

Interestingly enough, the data of Table 9 disclosed that on average, the net N contribution of interactions under the effect of TMWW, was much higher than that under the control, being 3.163% and 1.279%, respectively. Nevertheless, this high N contribution offsets the lower N, contributed under the TMWW in the ‘root-leaf-sprout’ (Table 5) and in the ‘root-leaf’ (Table 7), pathways, respectively, and at the same time the sprouts were being supplied with high N levels, which are required for their growth and maturation. It is thus shown that the elemental interactions contribution, and more specifically in relation to N, starts at lower levels in the ‘root-leaf’ pathway, and increases significantly along the ‘leaf-sprout’ pathway, thus satisfying the higher needs of the sprouts, for N.

Table 9. Elemental contribution in macro and micronutrients of the concomitantly occurring interactions between the above elements in the ‘leaf-sprouts’ pathway of Brassica oleracea var. gemmifera (Brussels sprouts), under the effect of TMWW and control, respectively.

		TMWW		Control		Mean contribution^b
Interactions	Contributed elements^a	Leaf	Sprout	Leaf	Sprout	TMWW	Control
Mn×N	N	1.344	2.904	3.824	0.543
Fe×N	N	5.350	3.53	3.807	−3.060
Mean	N	3.347	2.979	3.816	−1.259	3.163	1.279
Mn×K	K	5.492	0.713	4.391	0.000
Fe×K	K	−1.710	0.713	7.699	0.000
Mean	K	1.891	0.722	6.045	0.000	1.307	3.023
K×Mn	Mn	23.050	2.903	21.969	5.591	12.980	13.78
Fe×Zn	Zn	21.600	11.511	11.483	7.773	16.556	9.628
^aUnits N and K% dm, and Mn and Zn in g/g dm; ^bIrrespective of the plant part.

Relationship between the level of an element in the soil, calculated by means of the regression equation of a given interaction, and its corresponding measured soil level

Correlation of elemental values of either the soil or the plant dry matter content obtained by calculations using the regression equations of interactions, with the corresponding elemental values of soil or plants chemical analysis, showed that they are closely and statistically significantly correlated. This is evident from the soil data of Table 10 and from leaf data of Table 11. The regression equations used for obtaining the data of Table 11 are given in Table 4, while the equations used to obtain the data of Table 10, are given in Table 12.

Table 10. Correlation between elemental values, calculated by means of regression equations of interactions, and their corresponding values measured by chemical analysis of soil, cultivated with Brussels sprouts, under the effect of TMWW and control, respectively.

		TMWW		Control
Interactions	Correlated elements	r	significance	r	significance
Fe×Mn	Mn(Fe) vs. Mn(S)	0.992	0.000	0.977	0.001
Fe×Pb	Pb(Fe) vs. Pb(S)	0.991	0.000	0.986	0.000
Fe×Ni	Ni(Fe) vs. Ni(S)	0.985	0.000	0.928	0.007
B×K	K(B) vs. K(S)	0.938	0.006	0.936	0.006
Cu×Ca	Ca(Cu) vs. Ca(S)	0.986	0.000	0.935	0.006
Co×Cd	Cd(Co) vs. Cd(S)	0.959	0.000	0.962	0.002
The S in parentheses refers to soil, Also, the letters in parentheses, i.e., Fe,B,Cu, and Co refer to iron, boron, copper and cobalt, respectively. The notation, for example Mn(Fe), means that Mn has been calculated as function of Fe by means of the corresponding interaction Fe×Mn etc.

Table 11. Correlation between elemental values, calculated by means of regression equations of interactions, and their corresponding values, measured by chemical analysis of Brussels sprouts leaves, under the effect of TMWW and Control, respectively.

		TMWW		Control
Interactions	Correlated elements	r	significance	r	significance
N×K	K(N) vs. K(l)	0.958	0.000	0.983	0.000
Cu×K	K(cu) vs. K(l)	0.929	0.000	0.802	0.000
Zn×N	N(Zn) vs. N(l)	0.933	0.000	0.900	0.000
K×Cu	Cu(K) vs. Cu(l )	0.910	0.000	0.744	0.006
N×Zn	Zn(N) vs. Zn(l)	0.948	0.000	0.954	0.000
The l in parentheses refers to leaf dry matter content. Also, the letters in parentheses, i.e. K, N, Cu and Zn refer to potassium, nitrogen, copper, and zinc, respectively. The notation, for example Mn(Fe), means that Mn has been calculated as function of Fe by means of the corresponding regression equation of the interaction Fe×Mn etc.

Table 12. Regression equations of the interactions occurring in soil (second sampling) used to calculate the data of Table 10.

Regression equations
TMWW
Interaction	Regression equation	R	Significance of F
Fe×Mn	Mn = 0.015×(Fe)^2+0.22×(Fe) +8.363	0.995	0.001
Fe×Pb	Pb = 0.011×(Fe)^2−0.242×(Fe) +3.033	0.995	0.001
Fe×Ni	Ni = 0.001×(Fe)^2+0.017(Fe) +0.327	0.994	0.006
B×K	K = 38.275×(B)^2+49.275(B) +108.169	0.943	0.037
Co×Cd	Cd = 3.356×(Co)^2−0.469×(Co) +0.037	0.960	0.022
Cu×Ca	Ca = 6.143×(Cu)^2 −20.05×(Cu) +17.06	0.985	0.005
Control
Fe×Mn	Mn = − 0.04×(Fe)^2 +1.783 (Fe) =1.947	0.987	0.004
Fe×Pb	Pb = − 0.093 (Fe)^2+2.704 (Fe) − 16.686	0.986	0.004
Fe×Ni	Ni= −0.015 (Fe) 2 + 0.476 (Fe) − 2.736	0.928	0.052
B×K	K = 318.867×(B)^2−39.537 (B) + 106.695	0.936	0.044
Cu×Ca	Ca = 12.162×(Cu)^2−36.013 (Cu) + 27.542	0.995	0.001
Co×Cd	Cd = 20.271×(Co)^2−0.684 (Co) + 0.028	0.964	0.019

These results suggested that the regression equations of the interactions could be used for the prediction of the elemental levels in either soil or in the plants. Furthermore, they emphasize the trustworthiness of the interaction regression equations.

Efforts to correlate the calculated tissue dry matter elemental values with the corresponding soil elemental content proved unsuccessful, as the correlation was non-significant. This was most probably due to the non-systematic and stepwise increasing application of the studied variable, i.e. of the TMWW, which was applied only at a constant level. Nevertheless, more work is necessary to show that the occurrences of the interactions are related to the corresponding elemental levels in the soil. This relation could help towards the establishment of critical heavy metal levels in the soil that would be useful in managing soil pollution problems due the above toxic heavy metals.

Conclusions

Based on the above discussion the following are concluded:

• Concomitantly occurring interactions were found in the following pathways: (a) ‘Root-leaf-sprout’, (b) ‘root-leaf’, and (c) ‘leaf-sprout’.

• The interactions which occurred along the ‘Root-leaf-sprout’, and ‘Leaf-sprout’ pathways, respectively, were all of them synergistic type, including exclusively essential plant macro and micronutrients. While, the interactions which occurred in the ‘root-leaf’ pathway were mostly antagonistic and very few of them synergistic, and more so, they included, apart from essential macronutrients, micronutrients and heavy metals as well.

• The interaction net effect was basically a contribution to the plants of essential elements primarily and heavy metals, secondarily. Quantification of this contribution showed that: (a) In the ‘root-leaf-sprout’ pathway the highest quantify of Mn was contributed under the TMWW being 16.46 g/g in comparison, to 11.69 g/g under the control. Also, the highest level of N was contributed under the effect of the control (2.13% dry matter compared to 1.85% under TMWW). Similarly, the contribution in N was higher under the control, i.e. 0.558% in comparison to 0.03% under the TMWW in the ‘root-leaf’ pathway.

• On the other hand, in the ‘leaf-sprout’ pathway, the interactions net effect in N was much higher under the TMWW, being 3.16% compared to 1.28% under the control.

• The antagonistic interactions which were found in the ‘root-leaf’ pathway, and which were absent from the ‘leaf-sprout’ pathway, suggested that they may possibly act as a mechanism against intensive accumulation of heavy metals in the edible plant part (sprouts).

• The calculated elemental levels by means of the regression equations of the interactions were significantly correlated with the corresponding measured elemental concentrations in the soil or in the leaves, suggesting the trustworthiness of the interactions, which could probably be used in modeling heavy metals and nutrient interrelationships studies in plants under TMWW.

• More research work is needed for the detailed study of the above aspect of plant elemental interactions