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. 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.The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number IFP-KKU-2020/3.Peer reviewe

Plants &lt;em&gt;versus&lt;/em&gt; 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, &lt;em&gt;e.g.&lt;/em&gt;, glycosylation, phosphorylation or cleavage. However, many challenges are encountered during &lt;em&gt;in planta &lt;/em&gt;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, &lt;em&gt;i.e.&lt;/em&gt;, 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

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 &gt; 1 for Mo and the bioaccumulation of Pb was &gt;1. SS could be used for pea fertilization but only at rates below 20 g/kg to avoid environmental and health hazards

Prediction models based on soil properties for evaluating the uptake of eight heavy metals by tomato plant (Lycopersicon esculentum Mill.) grown in agricultural soils amended with sewage sludge

The aim of this study is to design de novo prediction models in order to gauge the likely uptake of eight heavy metals (Al, Cr, Cu, Fe, Mn, Ni, Pb and Zn) by Lycopersicon esculentum, the tomato plant. Uptake was assessed within the plant’s root, stem, leaf and fruit tissues, respectively. The plant was cultivated in soil amended by different application rates of sewage sludge, i.e. 0, 10, 20, 30 and 40 g/kg. The roots exhibited markedly elevated heavy metal concentrations compared to the above-ground plant components, with the exception of the quantity of Ni in the leaves. Apart from Al, Fe and Mn, a bioconcentration factor >1 was identified for all heavy metals. Excluding Ni in the leaves, all tested heavy metals exhibited a translocation factor < 1. The regression models were deployed to predict the accretion of the heavy metals under investigation within the various parts of L. esculentum. These were founded on the parameters of the equivalent eight heavy metals within the soil, pH and organic matter content. Student’s unpaired t-tests revealed no differences between the actual and predicted heavy metal concentrations in the roots, stems, leaves or fruits of the tomato plant. These data suggest an excellent model goodness of fit in terms of its accuracy to forecast the degree of heavy metal uptake. The constructed models may therefore facilitate the safe propagation of L. esculentum in growing media amended with sewage sludge, and concurrently provide a risk assessment with respect to human well-being.The authors extend their appreciation to the Scientific Research Deanship at King Khalid University and the Ministry of Education in Saudi Arabia for funding this research work through the project number IFP-KKU-2020/3.Peer reviewe