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.

Productivity and Post-Harvest Fungal Resistance of Hot Pepper as Affected by Potassium Silicate, Clove Extract Foliar Spray and Nitrogen Application.

In the present study, growth and productivity of hot pepper planted in the two successive summer seasons of 2017 and 2018 were evaluated under the effect of foliar spray of variable doses of potassium silicate (PS), and clove water extract (CWE) with different rates of nitrogen (N) fertilization application. The post-harvest resistance of hot pepper fruits to Alternaria alternata fungal infection, was also evaluated. Maximum plant height was achieved with the application of the highest rates of N, PS and CWE, while the intermediate rates were sufficient to reach the maximum number of branches, the highest leaf dry matter and chlorophyll accumulation. Fruit yield progressively increased with increasing the applied N rate. The foliar application of PS and CWE exerted a limited, yet positive effect on fruit yield. Generally, the least amount of fruit yield, amounting to 18.84 and 18.00 t ha-1, resulted from the application of the lowest N rate (144 kg ha-1) in the absence of PS and CWE. The highest significant fruit yield, amounting to 31.71 and 31.22 t ha-1, for 2017 and 2018, respectively, accompanied the application of the maximum levels of the three factors. The application of high N rates increased the post-harvest Alternaria fruit rot severity. The positive effect of CWE application in counterbalancing the negative effects associated with the high rates of N and PS may be related to the presence of phenolic and flavonoid compounds ellagic acid, benzoic acid, catechol gallic acid, rutin, myricetin, quercetin, apigenin and kaempferol as identified by High Performance Liquid Chromatography (HPLC).

Heavy Metal Bioaccumulation, Growth Characteristics, and Yield of Pisum sativum L. Grown in Agricultural Soil-Sewage Sludge Mixtures.

The application of sewage sludge (SS) in agriculture is an alternative disposal method for wastewater recycling and soil fertilization. This study evaluated heavy metal bioaccumulation, growth, and yield of Pisum sativum (pea) grown in agricultural soil amended with SS at rates of 0, 10, 20, 30, and 40 g/kg. The results show that root, shoot, pod length, biomass, and number of leaves and pods increased with SS amendments of 10 and 20 g/kg, while rates declined at 30 and 40 g/kg. SS had greater salinity and organic content than the soil. Heavy metals in the postharvest soil samples increased for all SS application rates except Fe and Mo. The significant increase in Cd content started at the lowest amendment rate 10 g/kg; for Co, Mn, and Pb, the significant increase was detected at the highest amendment rate (40 g/kg). Generally, all heavy metals increased significantly in portions of P. sativum except Cd in the shoot. At an amendment rate of 10 g/kg, Co in the shoot and root, Cr in the fruit, Cu in the root, Fe in the fruit, Mn in the shoot and fruit, Mo in the fruit, Pb in the shoot, and Zn in the fruit were elevated significantly. In contrast, the concentrations of Cd in the fruit, Cr in the root, Cu in the shoot, Fe in the shoot and root, Ni in the fruit and root, Pb in the fruit and root, and Zn in the root significantly increased only at the highest rate of 40 g/kg. The highest regression R2 was 0.927 for Mn in pods and the lowest was 0.154 for Cd in shoots. Bioaccumulation and translocation factors were > 1 for Mo and the bioaccumulation of Pb was >1. SS could be used for pea fertilization but only at rates below 20 g/kg to avoid environmental and health hazards.

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.

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.

Regression models for monitoring trace metal accumulations by Faba sativa Bernh. plants grown in soils amended with different rates of sewage sludge.

The present study was conducted using a pot experiment to develop regression models for the prediction of trace metal concentrations in faba bean (Faba sativa Bernh.) plants cultivated in soils amended with different rates of sewage sludge to monitor possible human health risks. The trace metal concentrations in the different tissues of faba bean showed that most of the investigated trace metals were accumulated in the plant roots rather than in the other tissues. Meanwhile, the fruits accumulated the lowest concentration of most trace metals. The trace metal concentrations of the faba bean plants had a significant positive correlation with the organic matter content and a significant negative correlation with the soil pH. Transfer of trace metals from the soil to faba bean roots indicated that Al, Cu, Pb and Zn had a transfer factor that exceeded one, whereas the TF of the investigated trace metals from the roots to the fruits did not exceed one. The daily intake rate of the investigated trace metals did not exceed one in both adults and children. On the other side, the hazard quotient of trace metals from consuming faba bean fruits had values <1 for most investigated trace metals except Al and Mn in adults and in children. It is worth mentioning that the predicted trace metal concentrations via the established regression models and measured values from the validation data set were not significantly different (P > 0.05). Therefore, these developed models will be useful for prediction of trace metals uptake by faba bean grown in soil amended with sewage sludge so possible human risks can be identified.

Evaluation of the potential of sewage sludge as a valuable fertilizer for wheat (Triticum aestivum L.) crops.

A greenhouse experiment was performed to assess the soil heavy metal pools, growth, yield, and heavy metal uptake of wheat plants (Triticum aestivum L.) that are grown at different rates in soils supplemented with sewage sludge (SS). The experimental design was completely randomized, with six replicates per treatment. The application of SS significantly increased the soil organic matter content. Generally, most growth parameters, as well as the biomass of treated wheat, were significantly increased with the amendment of SS, up to the addition rate of 40 g kg-1. The content of all heavy metals (except Cr in grains and Pb in spikes) significantly increased in different tissues of treated wheat with the increasing rate of SS application. However, all heavy metal concentrations (except for Al, Cr, Fe, and Mn in the roots) were normal and did not overcome the phytotoxic levels. The wheat was recognized by a bioaccumulation factor < 1.0 for most of the heavy metals. The translocation factor for all of the heavy metals was < 1.0. Therefore, the SS utilized in the present study could be used as a valuable organic fertilizer in wheat cultivation areas in Saudi Arabia and could also act as an eco-friendly method for the recycling of SS.

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.

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.

The effects of different sewage sludge amendment rates on the heavy metal bioaccumulation, growth and biomass of cucumbers (Cucumis sativus L.).

When sewage sludge is incorrectly applied, it may adversely impact agro-system productivity. Thus, this study addresses the reaction of Cucumis sativus L. (cucumber) to different amendment rates (0, 10, 20, 30, 40 and 50 g kg-1) of sewage sludge in a greenhouse pot experiment, in which the plant growth, heavy metal uptake and biomass were evaluated. A randomized complete block design with six treatments and six replications was used as the experimental design. The soil electrical conductivity, organic matter and Cr, Fe, Zn and Ni concentrations increased, but the soil pH decreased in response to the sewage sludge applications. As approved by the Council of European Communities, all of the heavy metal concentrations in the sewage sludge were less than the permitted limit for applying sewage sludge to land. Generally, applications of sewage sludge of up to 40 g kg-1 resulted in a considerable increase in all of the morphometric parameters and biomass of cucumbers in contrast to plants grown on the control soil. Nevertheless, the cucumber shoot height; root length; number of leaves, internodes and fruits; leaf area; absolute growth rate and biomass decreased in response to 50 g kg-1 of sewage sludge. All of the heavy metal concentrations (except the Cu, Zn and Ni in the roots, Mn in the fruits and Pb in the stems) in different cucumber tissues increased with increasing sewage sludge application rates. However, all of the heavy metal concentrations (except the Cr and Fe in the roots, Fe in the leaves and Cu in the fruits) were within the normal range and did not reach phytotoxic levels. A characteristic of these cucumbers was that all of the heavy metals had a bioaccumulation factor <1.0. All of the heavy metals (except Cd, Cu and Zn) had translocation factors that were <1.0. As a result, the sewage sludge used in this study could be considered for use as a fertilizer in cucumber production systems in Saudi Arabia and can also serve as a substitute method of sewage sludge disposal. Graphical Abstract The effects of different sewage sludge amendment rates on the heavy metal bioaccumulation, growth and biomass of cucumbers.

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.

Plants versus fungi and oomycetes: pathogenesis, defense and counter-defense in the proteomics era.

Plant-fungi and plant-oomycete interactions have been studied at the proteomic level for many decades. However, it is only in the last few years, with the development of new approaches, combined with bioinformatics data mining tools, gel staining, and analytical instruments, such as 2D-PAGE/nanoflow-LC-MS/MS, that proteomic approaches thrived. They allow screening and analysis, at the sub-cellular level, of peptides and proteins resulting from plants, pathogens, and their interactions. They also highlight post-translational modifications to proteins, e.g., glycosylation, phosphorylation or cleavage. However, many challenges are encountered during in planta studies aimed at stressing details of host defenses and fungal and oomycete pathogenicity determinants during interactions. Dissecting the mechanisms of such host-pathogen systems, including pathogen counter-defenses, will ensure a step ahead towards understanding current outcomes of interactions from a co-evolutionary point of view, and eventually move a step forward in building more durable strategies for management of diseases caused by fungi and oomycetes. Unraveling intricacies of more complex proteomic interactions that involve additional microbes, i.e., PGPRs and symbiotic fungi, which strengthen plant defenses will generate valuable information on how pathosystems actually function in nature, and thereby provide clues to solving disease problems that engender major losses in crops every year.

Proteomic analysis of the phytopathogenic soilborne fungus Verticillium dahliae reveals differential protein expression in isolates that differ in aggressiveness.

Verticillium dahliae is a soilborne fungus that causes a vascular wilt disease of plants and losses in a broad range of economically important crops worldwide. In this study, we compared the proteomes of highly (Vd1396-9) and weakly (Vs06-14) aggressive isolates of V. dahliae to identify protein factors that may contribute to pathogenicity. Twenty-five protein spots were consistently observed as differential in the proteome profiles of the two isolates. The protein sequences in the spots were identified by LC-ESI-MS/MS and MASCOT database searches. Some of the identified sequences shared homology with fungal proteins that have roles in stress response, colonization, melanin biosynthesis, microsclerotia formation, antibiotic resistance, and fungal penetration. These are important functions for infection of the host and survival of the pathogen in soil. One protein found only in the highly aggressive isolate was identified as isochorismatase hydrolase, a potential plant-defense suppressor. This enzyme may inhibit the production of salicylic acid, which is important for plant defense response signaling. Other sequences corresponding to potential pathogenicity factors were identified in the highly aggressive isolate. This work indicates that, in combination with functional genomics, proteomics-based analyses can provide additional insights into pathogenesis and potential management strategies for this disease.