Food’s Waste Water Biosolid Assessment against Toxic Element Absorbability of Food’s Cropping Soil Plant by Dominance Theory
The blending of the Food’s Waste Water Biosolid (FWWB) fertilizer with Food’s Cropping Soil (FsCS) results the absorption of the toxic macromicroorganisms from FsCS (is known as absorbability index). It is observed that such as blending not only increase the fertility and productivity of FsCS by neu...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Hindawi - SAGE Publishing
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/a85ac3b2a92d43afb3414de2dbc6c6bf |
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| Sumario: | The blending of the Food’s Waste Water Biosolid (FWWB) fertilizer with Food’s Cropping Soil (FsCS) results the absorption of the toxic macromicroorganisms from FsCS (is known as absorbability index). It is observed that such as blending not only increase the fertility and productivity of FsCS by neutralizing or absorbing the macromicroorganisms but also catering the necessary nutrition to plants. The authors sensed that a few research works are conducted recently in the dimension of evaluating the best FWWB among available FWWBs under O-(objective) FWWB’s parameter models. On potential analysis of published research works, the authors claimed that there is yet no research document, which can evaluate the best FWWB among available FWWBs or assess the best absorbability index of O-(objective) as well as S-(subjective) FWWB’s model corresponding to evaluated FWWBs or alternative points. It is accepted as a first research challenge. On extensive review, the authors determined that published FWWB’s parameter models are simulated by only single or nondynamic multivariable optimization techniques, which is accepted as a second research challenge. To address both research challenges, preliminary, the authors developed and proposed FWWB’s parameter model, consisted of physical, chemical, and biological parameters corresponding to O and S in nature via auditing a real case of FWWB alternative points such as Narendr Rice Mill-P1, Liese Mahamaya Rice Mill-P2, Vijay Rice Mill-P3, Mahim Rice Mill-P4, and Dhansingh Rice Mill-P5 and their characteristics vs. parameters. Next, the authors framed the FWWB parameter model by acquiring O and S information against O-physical, chemical, and S-biological parameters corresponding to FWWB alternative points. To evaluate the results, the authors applied the robust multiparameter optimization “RMPO” (crisp VIKOR “VIseKriterijumska Optimizacija I Kompromisno Resenje” and FMF “Full Multiplicative Form technique with dominance theory”) approach on defuzzified S-data and O-data to evaluate the best FWWB point among available based on absorbability index assessment. The results are described in summary part. |
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