Heavy metal concentrations in the root zone soils of BFBF and CF alone practices
Concentrations of all the heavy metals analyzed (Table 2) were within the previously observed ranges of them in rice soils of Sri Lanka [54]. Differences in their concentrations were not significant between the BFBF and CF practices (P > 0.05). This indicated that the two practices had similar heavy metal concentrations in the root zone soil.
Table 2. The different heavy metals in the root zone soils of BFBF and CF alone practices.
Element
|
HM concentration in practice (µg.kg-1)
|
difference
|
|
CF
|
BFBF
|
(BFBF-CF)
|
As
|
1443.6 ± 49.23
|
1607 ± 101.46
|
163.4 (0.157)
|
Cd
|
ND
|
ND
|
-
|
Pb
|
5314 ± 129.64
|
5323 ± 179.12
|
9 (0.968)
|
Co
|
6584 ± 1061.86
|
5697 ± 839.95
|
-887 (0.517)
|
Cr
|
22340 ± 2172.95
|
21093 ± 1663.94
|
-1247 (0.652)
|
Ni
|
7078 ± 738.85
|
69 ± 606.95
|
-136 (0.887)
|
Mean ± standard errors are mentioned, and P-values in parentheses indicate the probability levels at which the differences in the factors between the BFBF and CF alone practices are significant. CF: 100% Chemical fertilizer recommended by the Agriculture Department (340 NPK/ha), BFBF: biofilm biofertilizer practice (225 NPK/ha+2.5L BFBF). ND not detected.
Bioaccumulation factor and translocation factor
Both BaF and TF are important parameters for assessing the potential risks of contaminants in the environment and are used in regulatory frameworks to set limits on the concentration of contaminants in the environment. By understanding the BaF and TF of different THM in the paddy plant, we would be able to better realize their potential impacts on human and environmental health and to take steps to minimize those impacts.
Table 3. Bioaccumulation and translocation factors of the different heavy metals in the BFBF and CF alone practices.
Factor
|
Treatment
|
As
|
Cd
|
Pb
|
Co
|
Cr
|
Ni
|
BaFs-r
|
BFBF
|
1.414 ± 0.10
|
-
|
0.344 ± 0.02
|
2.275 ± 0.26
|
0.302 ± 0.03
|
0.147 ± 0.01
|
|
CF
|
1.166 ± 0.05
|
-
|
0.225 ± 0.01
|
2.584 ± 0.40
|
0.190 ± 0.03
|
0.130 ± 0.02
|
|
P- value
|
0.032
|
|
0.000
|
0.519
|
0.004
|
0.369
|
TFr-s
|
BFBF
|
-
|
-
|
0.720 ± 0.05
|
0.186 ± 0.04
|
0.666 ± 0.05
|
2.257 ± 0.17
|
|
CF
|
-
|
-
|
1.350 ± 0.87
|
0.077 ± 0.00
|
1.534 ± 0.07
|
2.531 ± 0.48
|
|
P- value
|
|
|
0.000
|
0.004
|
0.000
|
0.598
|
TFs-l
|
BFBF
|
-
|
-
|
2.117 ± 0.15
|
0.600 ± 0.10
|
1.752 ± 0.28
|
1.752 ± 0.28
|
|
CF
|
-
|
-
|
2.410 ± 0.21
|
0.882 ± 0.08
|
0.981 ± 0.08
|
1.499 ± 0.13
|
|
P- value
|
|
|
0.026
|
0.035
|
0.468
|
0.412
|
TFl-p
|
BFBF
|
-
|
-
|
0.434 ± 0.07
|
1.009 ± 0.21
|
0.430 ± 0.06
|
0.511 ± 0.13
|
|
CF
|
-
|
-
|
0.739 ± 0.13
|
0.664 ± 0.04
|
0.508 ± 0.02
|
0.650 ± 0.07
|
|
P- value
|
|
|
0.049
|
0.188
|
0.229
|
0.359
|
TFp-g
|
BFBF
|
0.050 ± 0.01
|
0.173 ± 0.02
|
-
|
0.083 ± 0.02
|
0.166 ± 0.01
|
1.540 ± 0.43
|
|
CF
|
0.093 ± 0.01
|
0.218 ± 0.03
|
-
|
0.117 ± 0.02
|
0.125 ± 0.00
|
0.734 ± 0.18
|
|
P- value
|
0.003
|
0.176
|
|
0.165
|
0.000
|
0.090
|
Mean ± standard errors are mentioned, and P-values indicate the probability levels at which the differences in the factors between the BFBF and CF alone practices are significant. BaFs-r is the bioaccumulation factor of a given heavy metal from paddy soil to root. TFr–s, TFs–l, TFl–p, and TFp−g are the translocation factors of a given heavy metal from root to stem, stem to leaf, leaf to panicle, and panicle to seed, respectively.
The BaF of As, Pb, and Cr, except Co and Ni from soil to plant roots were higher in the BFBF practice than in the CF alone practice (Table 3). This could be attributed to the triggering of binding HM by HM-complexation [20, 55], as revealed by the strong correlations among As, Pb, and Cr for their enhanced bioaccumulation [56]. Generally, negatively charged soil EPS synthesized by the applied BFBF induces the chelation/binding of these heavy metals in the soil [57]. However, the BFBF practice caused increased bioaccumulation of the three heavy metals in the roots against their soil chelation. This shows that ecosystem intelligence has played a role in selectively remove As and Pb, in particular, from the soil, and to store them in the roots in the BFBF practice, because the two heavy metals are activated by the microbes, and in turn adversely affect them [58–60]. The selective removal of the two heavy metals has taken place under similar concentrations in the soil of the two practices (Table 2), reiterating the role of intelligence [60].
The application of BFBF enhanced the translocation of Co, whereas the CF increased the translocation of Pb and Cr at significant paces from root to stem (P < 0.01). In the CF alone practice, Co and Pb showed greater TF from stem to leaf, whereas Pb showed greater TF from leaf to panicle, leaving Co in leaves, which might tend to concentrate it in the leaves causing chlorosis and/or necrosis [61]. Low chlorophyll content in rice leaves in the CF practice in comparison to the BFBF practice is a frequent observation that is reported in the field (Ekanayake et al. in manuscript). In the CF practice, the TF of As from panicle to seed was significantly increased, while that of Cr was significantly decreased (P < 0.01) in comparison to the BFBF practice. The increased translocation of As from panicle to seed might have been caused by the increased translocation of Pb from leaf to panicle, because As and Pb are positively correlated in plants [56]. In rice consumed in Sri Lanka, As is frequently reported it exceeds the maximum permissible level in some cases, whereas Cr does not show toxicity [62]. Further, As accumulation in rice has been reported to reduce the levels of essential micronutrients Mn, Ni, and Se [63]. At its safety levels, Cr is beneficial for human brain health and insulin regulation [64]. In this manner, reduced translocation of As and increased translocation of Cr to rice grains with the BFBF application imply a sign of intelligence in the soil-plant system [60].
Human risk assessment
Non-carcinogenic risk assessment
Table 4. Estimated Daily Intake (EDI) of the different heavy metals in the BFBF and CF alone practices.
Heavy metal
|
EDI (µg.kg-1day-1)
|
BFBF
|
CF alone
|
As
|
0.12 ± 0.016
|
0.32 ± 0.014
|
|
(0.000)
|
Cd
|
0.08 ± 0.0085
|
0.16 ± 0.023
|
|
(0.004)
|
Pb
|
-
|
-
|
|
-
|
Co
|
0.12 ± 0.026
|
0.20 ± 0.024
|
|
(0.027)
|
Cr
|
0.99 ± 0.038
|
1.40 ± 0.058
|
|
(0.000)
|
Ni
|
3.79 ± 1.0
|
4.40 ± 1.1
|
|
(0.688)
|
Mean ± standard errors in each column. Values within parenthesis are Probability levels at which the differences of the factors between the BFBF and CF alone practices are significant.
The highest and lowest EDI values were observed in Ni and Cd, respectively, in both practices (Table 4). Application of BFBF pointed out that the daily intake of As, Co, Cd, and Cr could be reduced significantly compared to the CF alone practice (P < 0.05). It is reported that reducing the daily intake of toxic heavy metals such as Cd and As can lessen serious diseases such as lung cancer, bone defects, and also bronchitis [65]. The reduced EDI of the toxic heavy metals in the BFBF practice seems to have played a role in ecosystem intelligence [60].
All the HQ values were less than one, except As in CF alone practice (Fig. 1), which has reached the non-carcinogenic health risk level. The HQ is a measure of the potential risk associated with exposure to a single toxic heavy metal. In the BFBF practice, As, Cd, Co, and Cr showed significantly lower HQ values, possibly due to the binding of the HM to fungal cell walls [48] with the increased microbial diversity and abundance under the BFBF application [66, 67]. As such, the HQ values were significantly reduced by the BFBF intervention, except for the micronutrient Ni (Fig. 1). Even if it is non-toxic as a single HM, we consume the HM collectively. Thus, HI value which depicts the potential health risk associated with exposure to multiple toxic heavy metals is a better parameter [68].
Interestingly, the HI of the BFBF practice had been kept below the threshold value (Fig. 2) by significantly reducing the HQ values of the single HM though the values were well below the threshold of the HQ (Fig. 1). This is a clear evidence for the action of ecosystem intelligence with the BFBF practice in comparison to that of the CF practice [60].
Ecosystem intelligence is an outcome of the complex signaling among microbes, plants, and animals in the system for sustainability [60, 69]. Microbes are the focal point of ecosystem intelligence. When the microbial cells commune in great numbers, their startling collective talents for solving problems and controlling their environment have been observed via awareness, understanding, or other capacities implicit in real intellect [70–72]. As such, increasing microbial diversity and abundance contributes immensely to reinstating the intelligence in degraded ecosystems, in particular, for beneficial outcomes, as was seen with the BFBF application [60].