Rethinking food loss and waste to promote sustainable resource use and climate change mitigation in agri-food systems: A review.

The sustainable agri-food system is an important sector recognized for promoting the United Nations' Sustainable Development Goals on food security, resource conservation and climate change mitigation. However, the increasing food loss and waste (FLW) along the supply chains has continued to hinder these goals. This study evaluates the trend of FLW research from 1975 to 2022 and how it promotes the achievement of resource and environmental sustainability in agri-food systems. The salient research themes and hotspots that are of interest to researchers were identified. Bibliometric and network analyses were carried out on scholarly research articles from the Scopus database using bibliometrix and VOSviewer. Furthermore, the content analysis was conducted on the selected highly influential articles containing relevant data to understand the role of FLW in promoting sustainable agri-food systems. The results showed disaggregate and unbalanced research distribution on the impacts of FLW among the countries, with China and the United States having the highest contributions. The identified major research themes relating to sustainable agri-food systems are food waste and sustainable systems, food waste management and food waste impact assessment. Moreover, the circular economy was found to be a relatively new approach being explored in agri-food systems to promote FLW reduction and ensure sustainability of resource use. This study highlights the critical role of the impact of FLW in addressing the grand challenge of food security, resource use efficiency and environmental sustainability.

Prediction Models Based on Soil Characteristics for Evaluation of the Accumulation Capacity of Nine Metals by Forage Sorghum Grown in Agricultural Soils Treated with Varying Amounts of Poultry Manure.

Predictive models were generated to evaluate the degree to which nine metals (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) were absorbed by the leaves, stems and roots of forage sorghum in growing media comprising soil admixed with poultry manure concentrations of 0, 10, 20, 30 and 40 g/kg. The data revealed that the greatest contents of the majority of the metals were evident in the roots rather than in the stems and leaves. A bioaccumulation factor (BAF) < 1 was calculated for Cr, Fe, Ni, Pb and Zn; BAF values for Co, Cu, Mn and Cd were 3.99, 2.33, 1.44 and 1.40, respectively, i.e., > 1. Translocation factor values were < 1 for all metals with the exception of Co, Cr and Ni, which displayed values of 1.20, 1.67 and 1.35 for the leaves, and 1.12, 1.23 and 1.24, respectively, for the stems. The soil pH had a negative association with metal tissues in plant parts. A positive relationship was observed with respect to plant metal contents, electrical conductivity and organic matter quantity. The designed models exhibited a high standard of data precision; any variations between the predicted and experimentally observed contents for the nine metals in the three plant tissue components were nonsignificant. Thus, it was concluded that the presented predictive models constitute a pragmatic tool to establish the safety from risk to human well-being with respect to growing forage sorghum when cultivating media fortified with poultry manure.

Prediction models based on soil properties for evaluating the heavy metal uptake into Hordeum vulgare L. grown in agricultural soils amended with different rates of sewage sludge.

The current study aims at forming new prediction models to be employed in the approximating the possible uptake of a range of 10 heavy metals (HMs) (Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb and Zn) by Hordeum vulgare tissues including roots, shoots and grains following its growth in soil amended with sewage sludge (SS) using conditions employed in greenhouses. The present study determined an insignificant difference between the actual and predicted quantities of the HMs in the three tissues using t values. The majority of the predicted quantities of the HMs were acceptable with the exception of Cd in the shoots, Cu in grains and Pb in roots. Consequently, it is possible to use these models in assessing the cultivation of barley plants in soil amended with SS in a safe way, while simultaneously monitoring any potential risks to the health of humans.

Integration of Radiometric Ground-Based Data and High-Resolution QuickBird Imagery with Multivariate Modeling to Estimate Maize Traits in the Nile Delta of Egypt.

In site-specific management, rapid and accurate identification of crop stress at a large scale is critical. Radiometric ground-based data and satellite imaging with advanced spatial and spectral resolution allow for a deeper understanding of crop stress and the level of stress in a given area. This research aimed to assess the potential of radiometric ground-based data and high-resolution QuickBird satellite imagery to determine the leaf area index (LAI), biomass fresh weight (BFW) and chlorophyll meter (Chlm) of maize across well-irrigated, water stress and salinity stress areas in the Nile Delta of Egypt. Partial least squares regression (PLSR) and multiple linear regression (MLR) were evaluated to estimate the three measured traits based on vegetation spectral indices (vegetation-SRIs) derived from these methods and their combination. Maize field visits were conducted during the summer seasons from 28 to 30 July 2007 to collect ground reference data concurrent with the acquisition of radiometric ground-based measurements and QuickBird satellite imagery. The results showed that the majority of vegetation-SRIs extracted from radiometric ground-based data and high-resolution satellite images were more effective in estimating LAI, BFW, and Chlm. In general, the vegetation-SRIs of radiometric ground-based data showed higher R2 with measured traits compared to the vegetation-SRIs extracted from high-resolution satellite imagery. The coefficient of determination (R2) of the significant relationships between vegetation-SRIs of both methods and three measured traits varied from 0.64 to 0.89. For example, with QuickBird high-resolution satellite images, the relationships of the green normalized difference vegetation index (GNDVI) with LAI and BFW showed the highest R2 of 0.80 and 0.84, respectively. Overall, the ground-based vegetation-SRIs and the satellite-based indices were found to be in good agreement to assess the measured traits of maize. Both the calibration (Cal.) and validation (Val.) models of PLSR and MLR showed the highest performance in predicting the three measured traits based on the combination of vegetation-SRIs from radiometric ground-based data and high-resolution QuickBird satellite imagery. For example, validation (Val.) models of PLSR and MLR showed the highest performance in predicting the measured traits based on the combination of vegetation-SRIs from radiometric ground-based data and high-resolution QuickBird satellite imagery with R2 (0.91) of both methods for LAI, R2 (0.91-0.93) for BFW respectively, and R2 (0.82) of both methods for Chlm. The models of PLSR and MLR showed approximately the same performance in predicting the three measured traits and no clear difference was found between them and their combinations. In conclusion, the results obtained from this study showed that radiometric ground-based measurements and high spectral resolution remote-sensing imagery have the potential to offer necessary crop monitoring information across well-irrigated, water stress and salinity stress in regions suffering lack of freshwater resources.

Modeling of mineral elements uptake and localization in cabbage inflorescence (Brassica oleracea var. capitata) grown on sugar mill pressmud-amended soils.

Sugar mill pressmud is highly considered and used as a supplement to improve soil fertility and crop yield, especially in India. This study investigated the growth and yield performance of cultivated cabbage (Brassica oleracea var. capitata) on sugar mill pressmud amended soil. Pot experiments were performed using various pressmud amendment rates (0, 50, 100, and 150 g/kg soil) to study the fertilization impact on cabbage inflorescence yield (g) and size (diameter: cm). Moreover, mineral element (Cd, Cr, Cu, Fe, Mn, and Zn) accumulation in the cabbage inflorescence was also studied using a modified polynomial non-linear model. Results showed that the sugar mill pressmud had significantly (p < 0.05) higher nutrient elements which induced their concentration in the soil after mixing. Also, the highest yield (849.25 ± 7.47 g), size (15.10 ± 1.50 cm diameter), and dry weight (42.13 g) of cabbage inflorescence were attained using 100 g/kg pressmud treatment with a maximum significant (p < 0.05) accumulation of mineral elements. However, the highest accumulation of mineral elements was observed in the outer zones (Z1 and Z2) of leafy inflorescence as compared to inner zones (Z3 and Z4), respectively. The mineral elements in both outer and inner zones of cabbage followed an order of Fe > Mn > Zn > Cu > Cr > Zn. Furthermore, the developed modified polynomial quadratic model precisely predicted the total mineral element uptake (mg dwt.) by cabbage inflorescence. The models had good fitness as described by the coefficient of determination (R2 > 0.992) values. This study suggested that sugar mill pressmud was a promising resource for cabbage cultivation, and the developed models were helpful in the precise prediction of mineral elements accumulated by its inflorescence.

Evaluation of uptake of eight metals by Sorghum bicolor grown in arable soil combined with sewage sludge based on prediction models.

Prediction models were developed to estimate the extent to which aluminium, chromium, copper, iron, manganese, nickel, lead, and zinc were absorbed in the grains, leaves, stems, and roots of Sorghum bicolor cultivated in soil with various amendment rate of sewage sludge (0, 10, 20, 30, 40, and 50 g/kg) under greenhouse conditions. It was found that, aside from lead, all the examined metals occurred in significantly higher content in the roots compared to aerial tissues. Furthermore, the r-values were significantly negative between the bioconcentration factors of all metals, apart from aluminium and lead, and soil pH, whereas they were significantly positive between the bioconcentration factors, apart from lead, and soil organic matter content (OM). The r-values were typically significantly positive between the levels of all eight metals in the investigated tissues and in the soil. Moreover, the content of all the eight metals in the tissues exhibited a significant negative r-value with soil pH but a significant positive r-value with soil OM. The eight metal contents in the tissues given by the prediction models were quite similar to the real values, suggesting that the created models performed well, as shown by t-tests. It was thus concluded that prediction models were a viable option for evaluating how safe it was to grow S. bicolor in soils with sewage sludge content and at the same time for keeping track of possible human health hazards.

Temporal Potential of Phragmites australis as a Phytoremediator to Remove Ni and Pb from Water and Sediment in Lake Burullus, Egypt.

In the current work, we investigated the concentration of Ni and Pb in different organs of Phragmites australis to evaluate its potential application as a phytoremediator to remove these two metals from contaminated water and sediment in Lake Burullus (a Ramsar site in Egypt). Above- and below-ground biomass of P. australis, water and sediment were sampled monthly for 1 year at six sites of Lake Burullus (three sites represent each of the northern and southern parts of the lake) using six randomly distributed quadrats (each of 0.5 × 0.5 m) at each sampling site. Significant variation was detected for Ni and Pb concentrations in the sediments and waters between the northern and southern sites of the lake. The biomass of P. australis in the southern sites was greater than that in the northern sites; in addition, the above-ground biomass was higher than the below-ground biomass. The above-ground organs accumulated higher concentrations of Ni and Pb than the below-ground organs. The Ni and Pb standing stocks data indicated that the organs of P. australis extracted higher amounts of Ni and Pb per its area from the southern rather than the northern sites. In the current study, the Ni and Pb above-ground standing stocks increased from the early growing season (February) and reached its peak during August and then decreased. The highest monthly Ni and Pb standing stock (18.2 and 18.4 g m- 2, respectively) was recorded in the above-ground organs of plants in the southern sites in August. The bioaccumulation factor of Ni was 157.6 and 153.4 in the northern and southern sites, respectively, whereas that of Pb was 175.3 and 158.3. The translocation factor of Ni and Pb from the below- to above-ground organs was generally > 1. Thus, this reed species is a potential candidate for Ni and Pb phytoextraction. Based on our results, P. australis could be used for the extraction of Ni and Pb to reduce the pollution in Lake Burullus, if the above-ground biomass is harvested at its maximum value in August, as was the case regarding the maximum standing stock of Ni and Pb.

Insights into hazardous solid waste generation during COVID-19 pandemic and sustainable management approaches for developing countries.

The recent emergence of the COVID-19 pandemic has contributed to the drastic production and use of healthcare and personal protective equipment, leading to the release of a huge quantity of hazardous medical and solid wastes in the environment. Meanwhile, these solid wastes may contribute to the spread of the SARS-CoV-2 viral particles when disposed of without proper treatment and care. Since SARS-CoV-2 could persist on different material surfaces including plastic, steel, paper, cardboard, cloth, and wood, proper management of these hazardous solid wastes has become a challenging task during the COVID-19 pandemic. In this paper, an overview of the consumption of COVID-19-related healthcare and personal protective equipment along with the production of hazardous solid waste is presented. The efficient management of these wastes is necessary to prevent the entering of SARS-CoV-2 in various environmental compartments. Therefore, some preventive measures including the use of biodegradable materials for manufacturing personal protective equipment, minimizing the use of non-biodegradable materials, efficient pre- and-post planning, careful segregation, and disposal are, therefore, proposed for their sustainable management. The findings reported in this paper contribute to tackling the problems associated with hazardous solid waste management, particularly for low- and middle-income countries.

Prediction models for monitoring heavy-metal accumulation by wheat (Triticum aestivum L.) plants grown in sewage sludge amended soil.

Prediction of heavy-metal concentration in the edible parts of economic crops, based on their concentration in soil and other environmental factors, is urgently required for human risk assessment. The present investigation aimed to develop regression models for predicting heavy-metal concentration in wheat plants via their contents in sewage sludge amended soil, organic matter (OM) content and soil pH. The concentration of heavy metals in the plant tissues reflected its concentration in the soil with high Fe followed by Al, Mn, Cr, Zn, Ni, Co, Cu, and Pb. Soil OM content had a significant positive correlation with all investigated heavy-metal concentrations in the different tissues of wheat plants, while soil pH was negatively significant with most heavy metals except spike Pb and grain Cr. The bio-concentration factor of Al, Cu, and Zn from soil to wheat root was >1, while that of shoot, spikes, and grains was <1 for all heavy metals. Significantly valid regression models were developed with fluctuated coefficient of determination (R2), high model efficiency (ME) values and low mean normalized average error (MNAE). The significant positive correlations between the concentration of some heavy metals in the soil and the same in wheat tissues indicate the potential of this plant as a biomonitor for these metals in contaminated soils. The significant correlations between heavy-metal concentrations in soil and its properties (pH and OM) with metal concentrations in wheat plants support the prediction model as an appropriate option. This study recommends the use of models with R2 greater than 50% and recommend other researchers to use our models according to their own specific conditions.

Prediction models for evaluating heavy metal uptake by Pisum sativum L. in soil amended with sewage sludge.

The present study aims to develop prediction models for estimating the potential uptake of 10 heavy metals (HMs) (cadmium, Cd; cobalt, Co; chromium, Cr; copper, Cu; iron, Fe; manganese, Mn; molybdenum, Mo; nickel, Ni; lead, Pb; zinc, Zn) by the tissues of Pisum sativum (root, shoot and pod) grown in soil amended with sewage sludge (SS) under greenhouse conditions. Soil organic matter (OM) was estimated by loss-on-ignition at 550 °C for 2 h. The pH was determined by shaking the soil and pure water at a 1:5 ratio. For HM quantifications, 0.5-1.0 g of each soil or plant sample was digested using a tri-acid mixture digestion method. The quantities of selected HMs were estimated by means of inductively coupled plasma optical emission spectrometry. Bio-concentration (BCF) and translocation (TF) factors were <1 for most of the HMs. In addition, simple linear correlations were significantly negative between the BCF of all studied HMs and soil pH, except for Pb, Mn and Ni, whereas significant positive correlations were observed between BCFs and soil OM, except for Mn, Ni and Zn. The accumulation of the 10 HMs in P. sativum tissues was predicted using regression models based on the values of the same HM in the soil as well as its pH and OM. The calculated prediction models performed well for most HMs in P. sativum tissues (except Ni in the pod, Cd in the shoot and Mn in the root). All measured soil factors (HM, pH and OM) consistently contributed to HM concentrations in the three tissues of the studied plants. These models may help to evaluate the safe cultivation of this species in soil amended with SS.

Mangrove health along the hyper-arid southern Red Sea coast of Saudi Arabia.

Changes in land use and land cover have severely influenced the sustainability of mangrove vegetation, especially in the hyper-arid, hyper-saline Red Sea coastal waters of Saudi Arabia. The present study investigates the effect of effluents released from an adjoining shrimp farm on the sustainability of a nearby mangrove woodland during operation and after closure of the farm. In addition, the consequences of dredging activities to fill coastal waters for land reclamation to develop a mega seaport at Jazan Economic City are explored. A band image-difference algorithm was applied to Landsat 5 Thematic Mapper and Landsat 08 Operational Land Imager satellite images obtained on different dates, which revealed a prominent vigour boom in the mangrove forest while the shrimp farm operated but a gradual decrease in vigour after its closure. During the investigation time frame of 2016 and 2017, spectral vegetation analysis of Sentinel-2A satellite images highlighted a strong negative correlation between dredging operations for seaport construction and the adjacent fragile mangrove forest. Dredging operations were responsible for a reduction of 19.30% in the Normalized Difference Vegetation Index, 27.5% in the Leaf Area Index, and 19.0% in the Optimized Soil Adjusted Vegetation Index. The results clearly show the potential application of spectral vegetation indices in the monitoring and analysis of anthropogenic impacts on coastal vegetation. We suggest strong management efforts for monitoring, assessing, and regulating measures to offset the negative trends in the sustainability of mangroves in Red Sea coastal regions.

Uptake Prediction of Ten Heavy Metals by Eruca sativa Mill. Cultivated in Soils Amended with Sewage Sludge.

This study was carried out to develop mathematical regression equations for predicting the uptake of ten heavy metals (HMs) (cadmium, Cd; cobalt, Co; chromium, Cr; copper, Cu; iron, Fe; manganese, Mn; molybdenum, Mo; nickel, Ni; lead, Pb; zinc, Zn) by a vegetable species (Eruca sativa Mill.) in the Abha region (Saudi Arabia) based on the concentration of these HMs in soils amended with sewage sludge, organic matter (OM) content and soil pH. The resultant regression equations indicated that the three soil factors were significant predictors for the uptake of the ten HMs in the plant tissues. By applying a t test, we found that there are no significant differences between the actual and predicted values of the ten HMs in the E. sativa roots and leaves (P > 0.05), which reflects the goodness of fit of these equations for predicting the uptake of these HMs. Such types of equations may be helpful for evaluating the risk of cultivation of E. sativa plants in soils amended with sewage sludge.

Effect of the conversion of mangroves into shrimp farms on carbon stock in the sediment along the southern Red Sea coast, Saudi Arabia.

The conservation of coastal ecosystems and specially mangroves ''blue carbon'' is receiving more attention as consequence of their recognition as high ecosystem carbon stocks and for the fact that these areas are undergoing land conversion. The aim of the present study is to evaluate the impact of land use changes due to conversion of mangroves to shrimp farms on the bulk density (SBD), organic carbon (SOC) concentration, and SOC stock in the sediments along the southern Saudi Arabian Red Sea coast. Shrimp farms and mangrove locations showed significant (P < 0.001) differences in SBD with high mean values in the sediments of shrimp farms. Shrimp farms and mangrove locations showed significant (P < 0.001) SOC concentration differences with high mean values in the sediments of mangroves. Considering the whole depth of sediment interval (0-100 cm), the highest value of SOC stock was recorded at mangroves (29.2 kg C m-2) and the lowest was identified at the locations of shrimp farms (19.9 kg C m-2). The results show that SOC stock of mangroves is 147% higher than that of shrimp farms confirming the fact that anthropogenic factors contributed significantly to SOC stock decrease. The mean cumulative potential carbon dioxide (CO2) emission due to loss soil carbon stock from mangrove conversion to the shrimp ponds was 34.9 kg CO2 m-2. In conclusion, the conversion of mangroves into shrimp farms contributed to the loss of SOC stock, therefore, the preservation of mangrove areas has an important value especially in arid areas such as Saudi Arabia.

Bioaccumulation and translocation of nine heavy metals by Eichhornia crassipes in Nile Delta, Egypt: perspectives for phytoremediation.

The current research was carried out to estimate the potential of water hyacinth (WH) for removal of nine heavy metals (HMs) from three irrigation canals in Nile Delta. Sampling was achieved in monospecific and homogeneous WH stands at three irrigation canals in the study area, and WH biomass was sampled at monthly intervals from April 2014 to November 2014 using five randomly distributed quadrats (each 0.5 × 0.5 m) at each canal. All HM concentrations were significantly higher in the roots compared with the other WH organs. The WH was recognized by a bioaccumulation factor >1.0 for all HMs. The WH was recognized by translocation factor <1.0 for all HMs (except Pb). In many cases, the concentrations of the HMs in the different organs of WH were correlated with the same HMs in the water. Such correlations indicate that WH reflects the cumulative influences of environmental pollution from the water, and thereby suggesting its potential use in the bio-monitoring of most examined HMs. In conclusion, WH is a promising macrophyte for remediation of irrigation canals polluted with Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn.

Prediction models for evaluating the heavy metal uptake by spinach (Spinacia oleracea L.) from soil amended with sewage sludge.

The risk evaluation of polluted soil requires the application of precise models to predict the heavy metal uptake by plants so possible human risks can be identified. Therefore, the present work was conducted to develop regression models for predicting the concentrations of heavy metals in spinach plants from their concentration in the soil by using the organic matter content and soil pH as co-factors. The soil improved with sewage sludge was slightly alkaline and had a relatively high organic matter content. Similar to the soil analysis, Fe had the highest median concentration, while Cd had the lowest concentration in the roots and leaves. Heavy metals accumulated in the roots and leaves in the order Fe > Mn > Zn > Cu > Cr > Ni > Co > Pb > Cd. The bio-concentration factor of the investigated heavy metals, from soil to roots, did not exceed one. The spinach was recognized by a translocation factor <1.0 for all of the heavy metals except Zn. Plant heavy metal concentrations were positively correlated with the soil organic matter content and negatively correlated with soil pH. The leaf Cr, Fe and Zn and the root Cr, Fe, Pb and Zn concentrations were positively correlated with the respective soil heavy metals. In addition, a linear correlation was found between the bio-concentration factor of heavy metals and soil pH and organic matter content. Regression models with high model efficiency and coefficients of determination and low mean normalized average errors, which indicate the efficiency of the models, were produced for predicting the plant heavy metal contents by using the soil pH and organic matter content as co-factors.

Bioaccumulation and rhizofiltration potential of Pistia stratiotes L. for mitigating water pollution in the Egyptian wetlands.

The bioaccumulation and rhizofiltration potential of P. stratiotes for heavy metals were investigated to mitigate water pollution in the Egyptian wetlands. Plant and water samples were collected monthly through nine quadrats equally distributed along three sites at Al-Sero drain in Giza Province. The annual mean of the shoot biomass was 10 times that of the root. The concentrations of shoot heavy metals fell in the order: Fe < Mn < Cr < Pb < Cu < Zn < Ni < Co < Cd, while that of the roots were: Fe < Mn < Cr < Pb < Zn < Ni < Co < Cu < Cd. The bio-concentration factor (BCF) of most investigated heavy metals, except Cr and Pb, was greater than 1000, while the translocation factor (TF) of most investigated metals, except Pb and Cu, did not exceed one. The rhizofiltration potential (RP) of heavy metals was higher than 1000 for Fe, and 100 for Cr, Pb and Cu. Significant positive correlations between Fe and Cu in water with those in plant roots and leaves, respectively were recorded, which, in addition to the high BCF and RP, indicate the potential use of P. stratiotes in mitigating these toxic metals.

Prediction models for evaluating the uptake of heavy metals by cucumbers (Cucumis sativus L.) grown in agricultural soils amended with sewage sludge.

Heavy metal (HM) concentrations in edible plants can develop many serious health risks to humans. The precise prediction of plant uptake of HMs is highly important. Thus, the present investigation was carried out to develop regression models for predicting the concentrations of HMs in cucumbers (Cucumis sativus L.) from their concentration in the soil and using the organic matter (OM) content and soil pH as co-factors. The results showed that cucumber roots had the highest significant concentrations of all HMs at P < 0.001, except Cd, Cu, and Zn were in fruits. The lowest concentrations of Cd, Co, Cr, Mn, Ni, and Pb were recorded in stems. HM concentrations in cucumbers were strongly correlated with soil HM, pH, and OM content. Soil pH and OM content had negative and positive correlations with all HMs in cucumber tissues, respectively. Regression analysis indicated that soil HM, pH, and OM contents were good predictors for HM concentrations in cucumbers. The regression models for root Co, Cr, Fe, and Zn were described by high model efficiency values that explain 48-58% variability. The best regression models for cucumber stem were for Cu, Mn, Ni, and Zn that are characterized by high R2 and model efficiency values. For cucumber fruits, R2 values were ranged from 54 to 82%, with best models for Cr, Pb, Cd, Cu, Ni, and Co in the fruit. We expect that these models will be beneficial for risk assessment studies on sewage sludge utilization in agriculture.

Effects of different sewage sludge applications on heavy metal accumulation, growth and yield of spinach (Spinacia oleracea L.).

In this study, we present the response of spinach to different amendment rates of sewage sludge (0, 10, 20, 30, 40 and 50 g kg-1) in a greenhouse pot experiment, where plant growth, biomass and heavy metal uptake were measured. The results showed that sewage sludge application increased soil electric conductivity (EC), organic matter, chromium and zinc concentrations and decreased soil pH. All heavy metal concentrations of the sewage sludge were below the permissible limits for land application of sewage sludge recommended by the Council of the European Communities. Biomass and all growth parameters (except the shoot/root ratio) of spinach showed a positive response to sewage sludge applications up to 40 g kg-1 compared to the control soil. Increasing the sewage sludge amendment rate caused an increase in all heavy metal concentrations (except lead) in spinach root and shoot. However, all heavy metal concentrations (except chromium and iron) were in the normal range and did not reach the phytotoxic levels. The spinach was characterized by a bioaccumulation factor <1.0 for all heavy metals. The translocation factor (TF) varied among the heavy metals as well as among the sewage sludge amendment rates. Spinach translocation mechanisms clearly restricted heavy metal transport to the edible parts (shoot) because the TFs for all heavy metals (except zinc) were <1.0. In conclusion, sewage sludge used in the present study can be considered for use as a fertilizer in spinach production systems in Saudi Arabia, and the results can serve as a management method for sewage sludge.

Bioaccumulation and translocation of heavy metals by nine native plant species grown at a sewage sludge dump site.

In the present study, nine native plant species were collected to determine their potential to clean up nine heavy metals from soil of a sewage sludge dump site. Almost all nine plant species grown at sewage sludge dump site showed multifold higher concentrations of heavy metals as compared to plants grown at the reference site. All the investigated species were characterized by a bioaccumulation factor (BF) > 1.0 for some heavy metals. BF was generally higher for Cd, followed by Pb, Co, Cr, Cu, Ni, Mn, Zn, and Fe. The translocation factor (TF) varied among plant species, and among heavy metals. For most studied heavy metals, TFs were <1.0. The present study proved that the concentrations of all heavy metals (except Cd, Co, and Pb) in most studied species were positively correlated with those in soil. Such correlations indicate that these species reflect the cumulative effects of environmental pollution from soil, and thereby suggesting their potential use in the biomonitoring of most heavy metals examined. In conclusion, all tissues of nine plant species could act as bioindicators, biomonitors, and remediates of most examined heavy metals. Moreover, Bassia indica, Solanum nigrum, and Pluchea dioscoridis are considered hyperaccumulators of Fe; Amaranthus viridis and Bassia indica are considered hyperaccumulators of Pb; and Portulaca oleracea is considered hyperaccumulator of Mn.

An experimental and prediction modeling study on water lettuce (Pistia stratiotes L.) assisted heavy metals removal from glass industry effluent.

The glass manufacturing industry produces hazardous effluent that is difficult to manage and causes numerous environmental problems when disposed of in the open. In this study, an attempt was made to study the phytoremediation feasibility of water lettuce (Pistia stratiotes L.), a free-floating aquatic macrophyte, for the removal of six heavy metals from glass industry effluent (GIE) at varying concentrations (0, 25, 50, 75, and 100%). After a 40-day experiment, the results showed that 25% GIE dilution showed maximum removal of heavy metals i.e., Cu (91.74%), Cr (95.29%), Fe (86.47%), Mn (92.95%), Pb (87.10%), and Zn (91.34%), respectively. The bioaccumulation, translocation, and Pearson correlation studies showed that the amount of heavy metals absorbed by vegetative parts of P. stratiotes was significantly correlated with concentrations. The highest biomass production, chlorophyll content, relative growth rate, and biomass productivity were also noted in the 25% GIE treatment. Moreover, the multiple linear regression models developed for the prediction of heavy metal uptake by P. stratiotes also showed good performance in determining the impact of GIE properties. The models showed a high coefficient of determination (R2 > 0.99), low mean average normalizing error (MANE = 0.01), and high model efficiency (ME > 0.99) supporting the robustness of the developed equations. This study outlined an efficient method for the biological treatment of GIE using P. stratiotes to reduce risks associated with its unsafe disposal.