Jatropha curcas is an oilseed crop with biorefinery applications. Whilst cake generated following oil extraction offers potential as a protein source for animal feed, inactivation of toxic phorbol esters present in the material is necessary. Pleurotus pulmonarius is a detoxifying agent for jatropha cake with additional potential as animal feed, edible mushroom and for enzyme production. For the characterization of fungal genes involved in phorbol ester degradation, together with other industrial applications, reverse transcription-quantitative PCR (RT-qPCR) is a tool that enables accurate quantification of gene expression. For this, reliable analysis requires reference genes for normalization of mRNA levels validated under conditions employed for target genes. The stability of potential reference genes β-TUB, ACTIN, GAPDH, PHOS, EF1α, TRPHO, LAC, MNP3, MYP and VP were evaluated following growth of P. pulmonarius on toxic, non-toxic jatropha cake and a combined treatment, respectively. NormFinder and geNorm algorithms for expression stability analysis identified PHOS, EF1α and MNP3 as appropriate for normalizing gene expression. Reference gene combinations contrasting in ranking were compared following normalization of relative expression of the CHU_2040 gene, encoding an esterase enzyme potentially involved in phorbol ester degradation. The reference genes for P. pulmonarius will facilitate the elucidation of mechanisms involved in detoxification of phorbol esters as well as analysis of target genes for application in biorefinery models. Jatropha curcas L., an oilseed crop with potential industrial and agricultural applications, is recognized primarily as a potential sustainable biofuel crop3. Difficulties exist, however, in adding value to the by-product of jatropha cake, which is a lignocellulosic residue rich in proteins, nitrogen, phosphorus, potassium, and carbon. Application of this residue in animal feed is currently limited due to the presence of toxic and thermostable antinutritional factors such as phorbol ester diterpenes6.The current global drive to reduce the negative impacts of industry on the environment has led to the development of the bioeconomy concept, where economic sectors are adapted towards sustainability utilizing renewable biological resources for food, materials and energy production. Agro-industries are undergoing a transformation regarding renewable raw materials, low-carbon production, and land-use optimisation within integrative models such as biorefineries. In this context, 8. These chemical compounds, whilst widely used in industrial processes such as in the production of cosmetics, pharmaceuticals, medicinal products, and insecticides10, are also among the main pollutants accumulating from industrial pulp and paper production11. Given this, the bioprospecting of microorganisms capable of degrading such substances and their derivatives is of fundamental importance in bioremediation. The bio-detoxification of diterpene phorbol esters in jatropha cake offers potential for downstream application of the residue as a fertilizer or animal feed supplement. Appropriate micro-organisms may enable not only the degradation of toxic compounds present, but potentially also concomitantly increase nutritional value, or generate other value-added by-products such as enzymes, bioactive compounds and/or edible mushrooms. The genes and metabolic pathways underlying the biodegradation mechanism of phorbol ester in the cake generated after J. curcas oil extraction are currently poorly explored. However, it has been demonstrated that specific microbial growth can lead to the secretion of extracellular enzymes such as esterases, lipases, and proteases, which play roles in the degradation of the toxic diterpene12.Terpenes are chemical compounds derived from secondary plant metabolism that play a fundamental role in plant development, ecological interactions and defense responses against pests and pathogensPleurotus are today employed in the bioeconomy, in green chemistry and in the production of edible protein substitutes. These cultivated mushrooms, known as oyster mushrooms, are among the most cultivated globally13. Success in production is mainly due to the efficiency of fruiting and cultivation on various substrates14. Biotechnological products are numerous, with applications in bioremediation, mycoremediation, biotreatment and enrichment of lignocellulosic waste, biological control, development of catalytic products and in production of polysaccharides such as ergosterol18. Among the oyster mushrooms, Pleurotus pulmonarius is efficient in the degradation of phorbol esters in jatropha cake, with additional potential for application in biorefinery models3. The identification of genes in this basidiomycete fungus that are involved in the degradation of phorbol esters has yet to be conducted and represents an important step towards efficient enzymatic degradation and solving bottlenecks related to biodegradation. In this context, high-throughput sequencing approaches for analysis of the fungal transcriptome will be appropriate for the identification of expressed genes and metabolic pathways activated during the degradation of this toxic compound, as well as additional genes encoding and regulating the expression of enzymes with diverse industrial application12.Fungal species of the genus 24. Robust analysis, however, requires the employment of a suitable set of reference genes for transcript expression normalization, correcting data for variation across samples. In accordance with the Minimum Information for Publication of Real-Time Quantitative PCR Experiments (MIQE) guidelines25, normalization of expression of each target gene in relation to a reference gene is required to correct data for potential variations across sample replicates that often occur during cDNA preparation. For such normalization, specific reference genes are necessary for each organism that consider microbial growth conditions, tissue type and expression time points27. A suitable reference gene for gene expression normalization should exhibit constant expression, independent of the sample, condition, treatment, cell, and tissue type29. To determine the most stable normalizing genes, different algorithms with distinct statistical methods are generally applied, which will determine the best sets of stable genes32.For accurate quantification and validation of gene expression data originating from high-throughput transcriptome sequence data, reverse transcription-quantitative PCR (RT-qPCR) is a benchmark analytical tool for application across different experimental conditionsPleurotus, including Pleurotus ostreatus35; Pleurotus eryngii36, and Pleurotus tuber-regium37. Given the potential in P. pulmonarius for both the degradation of phorbol esters and concomitant application in biorefinery models using jatropha cake as carbon source, analysis of fungal gene expression is warranted. For accurate future analysis of target gene expression, reference genes for RT-qPCR are therefore required for this species. This study investigates the reliability of potential reference genes for P. pulmonarius during growth on jatropha cake, in the presence and absence of toxic phorbol esters.The genetic stability of reference genes has previously been investigated in different species of the genus P. pulmonarius cultivated on jatropha cake in the presence and absence of phorbol esters. Primer information for each evaluated gene is described in Supplementary Table PEP, ACTIN2, LAC2, CHS, and α-TUB did not display specific amplification via RT-PCR and were therefore not subsequently tested via RT-qPCR. For the remaining 10 genes, the specificity of primer amplification for single gene loci was confirmed by analysing melting curves, as shown in Supplementary Fig. Fifteen candidate genes were tested for specificity and stability as potential reference genes for P. pulmonarius grown on jatropha cake with the presence of toxic phorbol ester (treatment T)  , representing a dataset of combined T and NT data)  gene presented the highest Cq value, indicating lowest gene expression. Greatest variation of Cq was observed for the gene VP, with GAPDH presenting the lowest variation of Cq, with a mean value and median similar to the EF1α gene. The LAC gene was the only candidate to present outliers for this condition. For the NT condition of P. pulmonarius cultivation on jatropha cake without toxic phorbol esters, Cq values ranged from 15.6 to 30.8. For this condition, the MYP gene displayed the highest Cq value, whilst the lowest Cq value was observed for the ACTIN gene, where the highest variation of Cq was also observed. The gene VP was the only candidate in this condition to present outliers, with the lowest variation of Cq observed for the GAPH gene. For the combined condition, ACTIN and VP genes showed the lowest and highest Cq values, respectively. Both genes, however, showed a large variation in Cq, as also observed for the MYP gene. The lowest variation of Cq for this condition was observed for GAPDH and EF1α genes.Variation in Cq (cycle quantification) values for the 10 candidate genes was analysed and presented using a Box-plot representation, where it is possible to observe expression intervals, average Cq values (mean and median) and discrepant outlier values. Analysis of each gene was carried out under distinct conditions, namely P. pulmonarius cultivated on jatropha cake representing T, NT and combined data for treatments was assessed using the algorithms BestKeeper, geNorm, and NormFinder. Ranking of expression stability according to each biological treatment is summarized in Table Stability of candidate reference gene expression stability for P. pulmonarius candidate genes β-TUB, PHOS, EF-1 and MNP3 across all treatment conditions, with stability values below the default limit of 0.5, representing stability  was conducted using geNorm to determine the minimum number of genes necessary for normalizing gene expression in P. pulmonarius on J. curcas cake. Data presented in Fig. Analysis with the geNorm algorithm revealed stability for the ity Fig. . In contPHOS and EF1α genes displayed greatest stability across all treatment conditions. In the case of the MNP3 gene, analysis with NormFinder indicated high stability in expression in P. pulmonarius during cultivation conditions on toxic jatropha cake and when considering data for the combined conditions. Also in agreement with geNorm data, the genes TRPHO and MYP, displayed greater stability during growth under only the toxic condition, whilst β-TUB, ACTIN and LAC genes, which also displayed stability only during the toxic condition, showed a NormFinder stability profile diverging from geNorm ranking data.Gene stability ranking data following analysis with the algorithm NormFinder is presented in Fig. GAPDH gene displaying a standard deviation value lower than 1 for P. pulmonarius under the three distinct conditions, and the EF1α gene displaying a value of 0.94 in P. pulmonarius during treatment NT , has revealed that the CHU_2040 gene exhibits differential expression across 3, 7, and 11 days of cultivation on toxic jatropha cake when compared to cultivation on non-toxic cake. For normalization tests using the CHU_2040 gene, various combinations of genes ranked as most stable  and as least stable (LAC and VP) were compared. Figure CHU_2040 gene using the two most stable gene pair combinations revealed a similar positive expression profile of the gene over the time course investigated, albeit with variations in expression levels, and with RT-qPCR data supporting in silico data. Normalization with the two least stable gene candidates, in contrast, resulted in distinct gene expression profiles of the CHU_2040 gene over the time course, with greater standard deviation.To validate reference gene rankings, relative expression of the P. pulmonarius in the degradation of phorbol esters and concomitant enrichment of lignocellulosic residues3, the objective of this study was to identify reference genes for normalizing gene expression data for P. pulmonarius cultivated on jatropha cake in the presence and absence of the toxic diterpene phorbol ester.Given the potential application of P. pulmonarius during growth on toxic and non-toxic jatropha cake. These encoded proteins involved in constitutive fungal activities, such as β-tubulin and Actin 1, which are both involved in structural activity, GAPDH, which is involved in glycolysis, PHOS, that plays an important role in the synthesis of amino acids and nitrogenous bases, EF1α, involved in translation processes, and TRPHO, involved in membrane protection40.Several potential reference genes were selected for screening in 28, NormFinder29 and BestKeeper41 have been widely employed for reference gene development across different kingdoms, with combined data generally enabling accurate identification of stable normalizing genes. Here, data obtained using NormFinder and geNorm showed an overlap for the most stable and the least stable genes, in contrast to the results obtained using BestKeeper. Discrepancies in results obtained with the different software are common19. BestKeeper is an algorithm that may be inadequate for in vivo samples, since the calculation model applied (geometric mean of reference genes with a standard deviation > 1) does not fit biological system variations and is limited to controlled conditions42.The mathematical algorithms of geNormPHOS and EF1α. According to Castanera and coworkers19, the PHOS gene also showed high stability and is suitable for normalizing gene expression in P. ostreatus using the same algorithms. The EF1α gene was recently introduced as the secondary barcode region for molecular identification of fungi at the species level43, including basidiomycetes of the genus Pleurotus45. As such, this gene also adheres to the guidelines for ideal reference genes, with conservation in the target DNA sequence, species specificity, constant copy number, and without allelic variation36. Previously, the GAPDH gene was reported to be unsuitable for normalizing expression in the basidiomycete P. tuber-regium, according to data generated using the geNorm algorithm37. Here, the GAPDH gene was also shown to be unsuitable for normalizing gene expression in P. pulmonarius cultivated on jatropha cake, as was the ACTIN gene. Castanera and colleagues19 reported that the constitutive genes ACTIN, GAPDH1, and β-TUB, according to results generated using Genorm and NormFinder, were the least stable for normalizing gene expression in P. ostreatus cultivated on lignocellulosic residue. Clearly, the use of constitutive genes as reference genes without validation of their stability can lead to errors in gene expression analyses46. Given the previous reports across the three Pleurotus species, the constitutive gene GAPDH does not appear to be adequate for normalizing the expression of genes in basidiomycetes of the genus Pleurotus.Based on the results obtained using geNorm and NormFinder, highest stability among the housekeeping genes evaluated was observed with the genes Pleurotus pulmonarius belongs to the class of saprotrophic basidiomycetes, fungi that have evolved the ability to degrade the complex polymers that make up plant cell walls48. Within the basidiomycetes, P. pulmonarius is classified as a White-rot fungus, capable of completely degrading lignin through the action of oxidative enzymes51. Laccase (LAC), manganese peroxidase (MnP), lignin peroxidase (LiP), and versatile peroxidase (VP) are important enzymes in lignin degradation and are assumed to be the first in the line of proteins expressed during fungal catabolism of lignin49. Members of the genus Pleurotus have been reported to possess genes encoding MNP and VP, but not LiP-encoding genes52. Given the importance of oxidative enzymes for saprotrophic basidiomycetes, genes encoding LAC, MnP, and VP proteins were also tested for here for gene stability. The literature is scarce regarding the selection of reference genes for P. pulmonarius, although the MYP gene has been described for QPCR quantification of P. pulmonarius mycelia53. In our results, the MYP gene showed stability only under toxic culture conditions. In addition, this gene showed the highest Cq value in both toxic and non-toxic conditions, suggesting that it may be less expressed in these conditions. The LAC and VP genes did not show stability during any of the tested conditions, with box-plot data indicating outliers within the analyses. In contrast to the other genes encoding oxidative enzymes, the MNP3 gene, encoding a distinct manganese peroxidase to that of the MYP gene, displayed high stability under the experimental conditions, as did the PHOS and EF1α genes.54 and Nakao et al.55, esterases are the primary enzymes involved in the degradation of phorbol esters by bacteria of the genus Bacillus. Based on in-house RNA-seq data for P. pulmonarius on toxic and non-toxic jatropha cake (unpublished), the CHU_2040 gene encodes an esterase potentially involved in the complete degradation of phorbol esters. Through comparison with RNA-seq data, relative expression of this gene was used to validate the stability of the reference genes. When the most highly ranked stable gene combinations (PHOS-EF1α and EF1α-MNP3) were applied for normalizing relative expression of the CHU_2040 gene, differential expression results aligned with the in silico data. In contrast, when the least stable reference genes for normalization were employed, namely LAC and VP, the expression pattern of CHU_2040 exhibited a distinct profile that significantly diverged from the in silico expression data, revealing their unsuitability as normalization genes under the specific growth conditions employed for P. pulmonarius. These results clearly showed that different reference genes can influence the relative expression of target genes under specific growth conditions.According to Phengnuam and SuntornsukP. pulmonarius identified three stable genes suitable for normalizing gene expression during culture on jatropha cake with or without the toxic compound phorbol ester. In addition, paired variation analyses showed that gene normalization can be performed with two reference genes. Whilst P. pulmonarius offers considerable importance in biotechnology, data related to molecular investigation of this fungus is still relatively limited. Together with the recent reference genome for P. pulmonarius16, the set of reference genes developed here for gene expression normalization is appropriate for future transcriptomic analysis and validation of gene expression of this fungus on this lignocellulosic residue.In summary, this first investigation into the development of reference genes for J. curcas (accession 123), all provided by the germplasm bank at Embrapa Agroenergia. Prior to pressing, seeds were individually heated at 60 °C for two hours using a rotary mixer dryer . The pressed seeds were then processed using an oil and grease extractor  to obtain both crude oil and the cakes that were employed in this study. Methanolic extraction of phorbol esters and quantification by HPLC was conducted following the method described by Gomes et al.3. The concentration of phorbol esters in the toxic cake was measured at 2.17 mg/g, while the non-toxic cake did not contain detectable levels of phorbol esters using the employed technique.Cakes were obtained by mechanically pressing seeds for genetic accessions of non-toxic (accession 169) and toxic Pleurotus pulmonarius strain BRM 055674, originating from the basidiomycete collection at Embrapa Agroenergia, was preserved according to the Castellani method56. Subsequently, mycelial disks were transferred to Jatropha agar culture medium3 and incubated at 28 °C for 7 days. As described above, available naturally non-toxic varieties of J. curcas57 that do not synthesize or have minimal amounts of phorbol esters were employed in bioassays as controls for analysis of gene expression modulation after fungal growth on toxic jatropha cake. For solid-state cultivation, 100 g of each substrate of toxic and non-toxic jatropha cake were moistened to 70% humidity and transferred to 150 mm × 20 mm Petri dishes. Following sterilization, 7-day old P. pulmonarius mycelial plugs were inoculated onto either toxic jatropha cake (treatment T) or non-toxic jatropha cake (treatment NT), then incubated at 28 °C. Fungal mycelia colonizing the substrates were collected at three time points over a 3-, 7- and 11-day incubation period. All bioassays were performed in triplicate. As described above, the third condition analysed corresponded to a combination of T and NT treatment data sets and is referred to as the combined condition throughout (treatment C).P. pulmonarius were collected from the surface of colonized jatropha cake for both treatments at 3, 7 and 11 days after inoculation (DAI). Mycelia was immediately flash frozen in liquid nitrogen then stored at – 80 °C. Extraction and purification of total RNA for each treatment was performed using an INVITRAP® SPIN PLANT RNA kit , following the manufacturer’s instructions. Total RNA was treated with DNase I  for removal of residual genomic DNA. Total RNA concentration and integrity were analysed via 1% agarose gel electrophoresis and Nanodrop ND-1000 spectrophotometry . For synthesis of cDNA, from biological triplicates for each experimental condition , a total of 1 μg of total RNA was reverse transcribed to cDNA using Super Script II RT and Oligo(dT) primers .Mycelial samples of P. pulmonarius grown on jatropha cake waste, candidate genes were selected for screening that encode proteins likely involved in basal cell activities across diverse species of the genus Pleurotus .A Platinum SYBR Green qPCR Super Mix-UDG w/ROX kit  was employed for RT-qPCR analysis of expression of potential reference genes. PCR amplifications were performed using an ABI StepOne® Real-Time PCR thermocycler . PCR amplification was conducted on three experimental replicates and three technical replicates per treatment. Each PCR reaction comprised 2 μL of a 1:20 dilution of template cDNA, 0.2 μM of each primer and 5 μL Platinum® SYBR® Green qPCR Super Mix-UDG w/ROX kit , to a final volume of 10 μL. PCR thermocycling comprised 52 °C for 2 min, 95 °C for 10 min, followed by 40 cycles of denaturation at 95 °C for 15 s, followed by primer annealing and extension at 62 °C for 60 s. Analysis of the Tm (dissociation) of amplicons was performed using the software SDS 2.2.2  to verify specificity of primers. Raw ΔRn data was applied to determine RT-qPCR efficiency for each gene by using the program LinRegPCR, version 2017.1  between each potential reference gene, for determination of the optimal number of reference genes for employment in gene expression normalization. Subsequently, the software qbase +  was used to calculate the average quantification cycles (Cqs) per gene and the software GraphPad Prism v7  for statistical analysis.Stability analysis and validation of expression for each candidate reference gene were based on quantification cycle (Cq) values for each cDNA sample. This value indicates the total number of amplification cycles during the PCR exponential amplification phase that are needed to reach a default threshold value for amplification detection. The expression stability of each gene was determined using the analytical algorithms geNormPHOS and EF1α; MNP3 and EF1α) and the least stable reference genes (LAC and VP) were compared for normalization of the relative expression of the CHU_2040 gene, which encodes an esterase enzyme, potentially involved in phorbol ester degradation. RNA extraction, cDNA synthesis and qPCR were all conducted as previously described. The software qbase + (Biogazelle) was employed to calculate the average quantification cycles (Cqs) per gene, with the software GraphPad Prism v7 employed for statistical analysis of the combined condition.Combinations of the most stable genes (Supplementary Figure S1.Supplementary Table S1.


Understanding germplasm’s genetic diversity is essential for developing new and improved cultivars with stable yields under diverse environments. The objective of this study was to determine the genetic diversity and population structure of 128 maize inbred lines sourced from the International Institute of Tropical Agriculture (IITA), the International Maize and Wheat Improvement Centre (CIMMYT), and the University of KwaZulu-Natal (UKZN) using 11,450 informative single nucleotide polymorphism (SNP) markers. The inbred lines revealed highly significant (p < 0.001) levels of variability for the key phenotypic traits. The SNP markers had a mean gene diversity (GD) and polymorphic information content (PIC) of 0.40 and 0.31, respectively, indicating the existence of substantial genetic variation across the germplasm panel. The model-based population structure analysis identified three subpopulations (K = 3) among the inbred lines. This corroborated the phylogenetic analysis using phenotypic traits and molecular markers which classified the inbred lines into three groups. The findings of this study identified considerable genetic diversity for the selection of inbred lines with favourable alleles for multiple traits and could be useful to initiate marker-assisted selection (MAS) to identify significant loci associated with agronomic performance and multiple-stress tolerance. Zea mays L.) crop is a significant employer and source of foreign currency due to its multiplier effects. The crop has strong linkages throughout the economy, upstream to the input industries and downstream into the milling, animal feed, and food processing industries2. The hectarage planted with maize in South Africa varies depending on weather and market conditions, but on average, 2.5 to 2.75 million hectares of hybrid maize are planted each year, yielding 12 million tons of grain3. This translates to surplus maize exported to Zimbabwe, Botswana, Lesotho, Namibia, Eswatini, and Mozambique. South Africa is the only country in Africa that is in the top 10 of maize producers in the world4. However, climate change-induced biotic and abiotic stresses threaten maize productivity in tropical areas. Maize is severely affected by extreme weather events such as high temperatures, and unpredictable rainfall patterns, resulting in heat and drought stress or flooding5. Approximately 90% of maize in South Africa is produced on dry land under rain-fed conditions6.In South Africa, the maize  Rane, Payak & Renfro) and northern leaf blight  with previously resistant cultivars being affected. Thus, the selection of germplasm with improved resistance or tolerance to biotic and abiotic stresses is critical in developing resilient maize production systems adapted to climate change-induced stresses. The sub-Saharan Africa is a centre of diversity for tropical and subtropical maize which has evolved stress adaptation genes for wide adaptation in the harsh savannah climates. Hence, this germplasm can expand the genetic diversity required for the development of climate-resilient maize cultivars in South Africa.Rainfall has decreased drastically over the past few years causing a dramatic decline in maize volumes due to the El Nino induced droughts. The variations in the frequency and amount of rainfall received have deleterious effects on maize grain yields mainly when water deficits occur during flowering (anthesis and silking)12. The CIMMYT program in Africa is divided into the East and Southern Africa regional hubs. Yield, drought, heat, low N, Low P, Striga, grey leafspot, maize streak virus, rusts, and ear rots have been the primary targets for selection at the two hubs13.The Consultative Group of International Agricultural Research (CGIAR) centers comprising the International Maize and Wheat Improvement Centre (CIMMYT) and International Institute of Tropical Agriculture (IITA) have contributed immensely to the genetic improvement of tropical maize in Africa. Several inbred lines with tolerance to a diverse range of biotic and abiotic stresses have been developed by CIMMYT and IITA14. The MLN Screening facility in East Africa, Kenya identified notable resistance to the virus, and integrated the resistance genes into African-adapted germplasm. Currently, maize is a principal cereal in West Africa because of the Central Africa Maize Collaborative Research Network (WECAMAN) established by IITA and all the national programs in that region. The IITA’s breeding strategy of combining Striga resistance, earliness, drought- and low-N tolerance enhanced maize yield production in multiple stress environments. Maize grown in West and Central Africa should mature early before the onset of terminal drought which triggers Striga parasitic infections. It is noteworthy that both programs integrate elite exotic germplasm to expand the genetic and phenotypic elasticity of tropical and subtropical maize in the region. For instance, some of CIMMYT’s inbred lines developed in Africa are derived from Tuxpeño Sequía, and La Posta Sequía populations14, with the CIMMYT heterotic group A coming from populations and lines including the Tuxpeno, Kitale, BSSS , B73 and Salisbury white (N), in contrast the CIMMYT group B contains populations and lines from ETO, Ecuador 573, Lancaster, Mo17 and Southern cross (SC)15. Elite exotic germplasm introduces valuable new alleles that broaden the genetic divergence required to exploit heterosis for hybrid breeding16.However, the recent fall armyworm outbreaks in Southern Africa and the maize lethal necrosis virus (MLN) in East Africa presented new challenges warranting immediate action. To date, several multiple-stress tolerant CIMMYT maize lines (CMLs), including CMLs 536–544 and 571–572, and 587–592, bred in Southern Africa are available for public and private maize breeding programs in Africa17, containing GM traits such as glyphosate and insect resistance, thus improving grain yield. While these traits have resulted in considerable yield gains compared to conventional maize production, introgression of these traits will potentially result in deleterious genetic ‘bottlenecks’. In addition, most commercial breeding programs developed new inbred lines by recycling elite lines via pedigree which also narrows genetic divergence. Furthermore, most maize hybrid breeding programs, particularly in southern and eastern Africa, have utilized elite maize inbred lines from nine heterotic groups15 and derived from the “P” heterotic group  maize21. Trait phenotyping can be used in conjunction with molecular makers in the designation of entries into heterotic groups, particularly for highly heritable traits22. While morphological and agronomic polymorphisms are highly amenable to the environment and developmental stage of the plant, molecular markers, on the other hand, are very stable. Single nucleotide polymorphisms (SNPs) are the predominant form of naturally occurring genetic variation and offer adequate variation to distinguish closely related individuals. As a result, they have become the preferred DNA marker of choice for diversity studies. Additionally, SNPs are useful for studying genetic variation due to their low cost per data point, lower genotyping error rates, locus-specificity, high genomic abundance, potential for high throughput analysis, and codominance25.Knowledge of genetic relationships between local maize germplasm, and tropical and sub-tropical maize inbred lines will guide parental selection and the devising of appropriate breeding designs. Genetic diversity analysis differentiates breeding populations and assists in classifying inbred lines into definite heterotic groups26. Gaining insight into how locally bred lines are related to lines developed by the CGIAR, suffices in the exploitation of heterosis in local breeding programs. Therefore, the objectives of this study were to assess genetic diversity and interrelationships present among locally bred maize inbred lines and the CGIAR tropical and sub-tropical maize lines adapted to SSA conditions, to determine heterotic groups and select unique genotypes for biotic and abiotic stress tolerance breeding. The set of local South African germplasm used in the study represents important genetic resources for use in public and private maize breeding programs in the country.Thus, SNPs provide an opportunity for the assessment of genetic diversity among local South African inbred lines and exotic tropical and subtropical maize germplasm developed for national maize breeding programs in SSAStriga and MSV, as well as tolerance to drought, including TZE-W Pop DT STR C0, TZE-Y Pop DT STR C0, and TZE Comp 5-Y C6. The description of the germplasm used in the study is summarised in Table One hundred and twenty-eight (128) diverse maize inbred lines obtained from the International Maize and Wheat Improvement Centre (42), the International Institute of Tropical Agriculture (50), and the University of KwaZulu-Natal (36) were used in this study. The CIMMYT and IITA inbred lines were selected for their nutritional content and resistance/tolerance to biotic and/or abiotic stresses. The UKZN inbred lines were chosen to represent a sample of locally developed inbred lines to be used in commercial hybrid maize breeding. The CIMMYT lines were developed in Kenya and Zimbabwe  and were derived from the Tuxpeño Sequía, La Posta Sequía, and the Drought-Tolerant Population (DTP) yellow and white gene pools. The IITA germplasm was bred in Nigeria from several broad-based germplasm sources with resistance to −1. Field management followed the recommended maize agricultural practices.The test genotypes were evaluated under field conditions to complement molecular maker data. Two field trials were established at Ukulinga Research farm  of UKZN and Cedara Research Station  during the 2020/2021 cropping seasons. The experiments were arranged in 8 × 16 alpha lattice design with 2 replicates. Each plot consisted of 1 row, 5 m long, with inter and intra-row spacing of 0.8 and 0.3 m, respectively. The plant population density was 41,666.6 plants ha−1 was obtained from grain weight per plot adjusted to 12.5% grain moisture following CIMMYT (1999).Plant count (PC) was recorded as the total number of plants per plot counted after thinning. Days-to-anthesis (DA) and days-to-silking (DS) were recorded as the number of days from emergence to the date when 50% of the plants in a plot had produced pollen and silks, respectively. Anthesis-silking interval (ASI) was calculated as days to silking minus days to anthesis. Plant height (PH) expressed in centimetres (cm) was measured from base to tassel branching to the soil surface to the top of the tassel of 10 representative plants selected from each plot. Scoring the severity of rust (RST) disease of maize was done using a scale of 1–9, where 1 = 0% of leaf surface diseased (no rust) and 9 = 81–100% of leaf surface diseased. Field weight (FW) was measured as the total weight of unshelled cobs in kilograms (kg). Cob count (CC) was counted as number of cobs per plot at harvest. The number of kernel rows per ear (KR) and kernels per row per ear (KRE) were determined as counts. Ear length (EL) was recorded (cm) as the length of a cob from the tip to the base using the ruler, while the diameter of the cob (ED) was measured using a vernier calliper (mm). Grain moisture (MOI) content was measured using a moisture tester during shelling. Shelling percentage (SHP) was calculated as field weight minus grain weight and the difference was expressed as a percentage. A sample of 100 kernels, grain weight per ear (GWE) from each plot was weighed. Grain yield (GY) expressed in t hahttps://www.deltagen.agr.nz). Furthermore, the association among traits was deduced using Pearson correlation coefficients on the corrplot package in R software27.Data generated were subjected to analysis of variance after testing for normality and homogeneity of variance using R software. Trait BLUPs were computed using DeltaGen (https://www.seqart.net) in Nairobi, Kenya for DNA extraction and genotyping by sequencing. The DArTseq protocol was used to genotype samples using a SNP chip covering the ten maize chromosomes. The initial 50,941 SNPs from the genotyping-by-sequencing (GBS) pipeline were filtered by imputation to remove SNPs with 20% missing data and 5% minor allele frequency (MAF) using the snpReady package on R28. A total of 11,450 informative SNP markers were used after data imputation. Individual genotypes with > 20% missing data were removed.Fresh leaf samples were collected from 3 weeks old seedlings within each genotype and was shipped to SEQART AFRICA  and genetic diversity was performed using GenAlex30 after grouping the inbred lines based on the source of collection. Population structure was determined using the STRUCTURE v2.3.4 software31. The burn-in period and Markov Chain Monte Carlo (MCMC) length were set at 10,000 iterations, and the model was run by varying the number of clusters (K) from 1 to 10 with 10 alterations for each K. The appropriate K value was estimated by implementing the Evanno method using the STRUCTURE Harvester program32. A joint analysis of phenotypic and genotypic data was conducted. A phenotypic distance matrix was generated based on Gower’s distance, while the genotypic distance matrix was generated using Jaccard’s coefficient on the R software27. The phenotypic, and genotypic matrices were used to generate hierarchical clusters using the package “cluster” in R software27.The polymorphic information content (PIC), major allele frequency, the number of alleles, heterozygosity, and gene diversity were estimated using the R package “adegenet”The combined analysis of variance for the 15 quantitative traits studied is shown in Table −1 with a mean performance of 2.8 t ha−1. The top performing genotypes in terms of grain yield comprised TZISTR1190, TZISTR1261, CML540, CML571, and TZISTR1119, recording 5.9, 5.8, 5.6, 5.6, and 5.5 t ha−1, respectively. The least performing genotypes were CML545, 18 UK1-54 and TZISTR1162 recording 1.3, 0.9 and 0.9 t ha−1 respectively. The mean performances for all the phenotypic traits of the genotypes are summarized in Table The mean performance of the genotypes showed that days to 50% anthesis and silking (DA and DS) ranged from approximately 83 to 91 days. Anthesis and silking interval range from − 0.4 to 1.8 with a mean of 0.3. Plant height ranged from 99 to 274 cm with a mean of 179 cm. Cob count exhibited a mean of 15 and ranged between 3 and 27 per plot. Grain weight per cob ranged from 0 to 0.2 g with a mean of 0.1 g. Considerable variation was observed for grain yield ranging from 0.9 to 5.9 t haThe association among the 16 measured phenotypic traits is depicted by the heat map of Pearson correlation coefficients. The blue and red squares are negative and positive correlations, respectively  ranged between 0.03 and 0.50, with a mean of 0.40. While the polymorphic information content (PIC) range was between 0.03 and 0.38, with a mean of 0.31. The minor allele frequency (MAF) ranged from 0.01 to 0.50, with an average value of 0.34. The observed heterozygosity had the mean average of 0.67 varied between 0.59 and 0.83. Fixation index (F) ranged from − 1.1 to − 0.5 with a mean of − 0.69 Table . The resThe population structure analysis identified three subpopulations among the inbred lines based on the optimal K = 3 determined according to Evanno’s method Figs. , 3. The −1.The dendrogram based on phenotypic data showed three clusters: I, II, and III, each consisting of 81%, 9%, and 10% membership, respectively Fig. . ClusterBased on the genetic data, the dendrogram showed that Clusters I, II, and III consisted of 23%, 26%, and 51% membership, respectively Fig. . The firGenetic diversity studies are critical in identifying the individual genotypes among closely and distantly related groups for the start of new breeding initiatives. To breed novel hybrids with outstanding agronomic performance, multiple stress tolerance and high-quality yield, there is a need to understand the genetic interrelationships among the inbred lines. Hence, the rational of this study was to gain genetic relationships among South African-bred maize inbred lines, tropical and subtropical inbred lines developed across the African continent.33. The significant differences observed in days to 50% anthesis and silking (DA and DS) among genotypes are essential for crop development in drought-prone environments. Early flowering and maturity are desired characteristics because they contribute to drought escape. This is particularly important in the SSA context, adversely affected by climate change resulting in poor rainfall35.The study revealed significant genetic variation among the inbred lines using phenotypic traits and SNP markers. Analysis of variance showed highly significant differences among genotypes for grain yield and its associated component traits, indicating substantial genetic variation among the genotypes. Grain yield and its associated yield components are quantitatively inherited and are of polygenic inheritance which can enable selection between genotypes within a population36. The high number of SNP markers utilized in this study enabled a more precise estimate of the population structure. Gene diversity ranged between 0.03 and 0.5, with a mean of 0.4. Reference37 reported similar findings with the genetic diversity varying from 0.01 to 0.5. The polymorphism information content (PIC) predicts the relevance of a genetic marker for linkage analysis39. In this current study, the PIC average value was 0.31, indicating that the SNP markers employed could effectively discriminate between the genotypes. These results are in support of those reported by Refs.40. Single nucleotide polymorphisms are bi-allelic; therefore, their PIC values are often lower than SSRs; however, they offer higher genetic resolution42. The mean observed heterozygosity (Ho) of 0.67 reported in this study was considerably higher than those reported for inbred lines by Refs.44. This suggest(s) that some of the inbred lines were not homozygous. Further selfing and substantial selection is strongly advised to fix these inbred lines45. The inbreeding coefficient (F) quantifies the likelihood that two alleles at every locus within an organism are identical by descent from the two parents’ shared ancestor(s)46. In this study, the F value ranged from − 1.1 to − 0.5, with an average of − 0.69. Reference47 similarly observed a negative F mean value of − 0.29. A negative F value in a population sample indicates the presence of excess heterozygotes48.The phenotypic diversity observed in the test population was supported by the analysis of molecular variance. Genomic data is utilized in determining phylogenetic relationships in germplasm collections49. Likewise, CIMMYT has been the major source of white maize germplasm for most SSA commercial seed companies because of the prominence of white maize in the region, particularly in Southern Africa15. This presents genetic bottlenecks that limit breeding gains. Reference50 reported a wide divergence between Southern Africa sub-tropical germplasm and temperate maize lines suggesting the potential utility of temperate germplasm in expanding the genetic base of African germplasm. The combination of stress tolerance and high-yield performance can produce broad adaptation in hybrids for South Africa. The Water Efficient Maize for Africa (WEMA) program is a good example of the efficacy of synergy between the private and public sector germplasm. Under the project, Monsanto, and CIMMYT developed germplasm combining drought tolerance and optimum yield performance. The resultant hybrids have a 20% yield advantage under drought conditions and outperform most commercial hybrids in optimum environments51.The panel of selected SNPs used in this study effectively revealed the polymorphisms existing among and within the inbred line populations. The within inbred line variation accounted for the most significant proportion of the variation observed compared to among population differences. A constant germplasm exchange between IITA and CIMMYT which may explain the lack of high genetic identity and low distance genetic divergence observed between the two centres. For example, parental germplasm used to initiate the CIMMYT program for drought and low soil N stress tolerance in Kenya was sourced from the CIMMYT Southern Africa regional centre in Zimbabwe and early maturing populations from the International Institute of Tropical Agriculture (IITA)37 who reported the existence of 3 subpopulation among 94 early maturing tropical maize inbred lines using SNP markers. Similarly, the dendrogram grouped the genotypes into three primary clusters showing partial existence of origin as a source of diversity. In genetic diversity studies, reports of the grouping of genotypes according to their geographic origins are common47. However, the clustering of most inbred lines was not based on ancestry suggesting that maize inbred lines derived from the same populations do not always have the same selection. This also indicates that the study panel consisted of unique inbred lines. The UKZN inbred lines were bred for performance in high-potential environments while the CGIAR material was developed for adaptation in stress environments.The SNP analysis revealed the existence of three subpopulations (K = 3). These results are in agreement with those reported by Ref.The results of this study revealed that the maize inbred lines displayed phenotypic variation supported by genetic diversity, which will enable the selection and breeding of stress-tolerant maize hybrids. The genotypes exhibited highly significant variation in key agronomic traits such as DA, DS, PC, PH, and GY. High genetic distances between paired inbred lines demonstrated the distinctiveness of the evaluated genotypes and the availability of substantial genetic variation that could be utilized in the maize breeding program. The inbred lines were partially classified into three heterotic groups based on source background. Superior hybrids can be developed from inbred lines exhibiting the most comprehensive genetic distance within populations identified. Combining ability studies are recommended to confirm the agronomic performance and breeding values of the most divergent parental lines.Supplementary Tables.


Biochar is increasingly being used for soil improvement, but the effects on microbial diversity in soil are still ambiguous due to contrasting results reported in the literature. We conducted a meta-analysis to clarify the effect of biochar addition on soil bacterial and fungal diversity with an increase in Shannon or Chao1 index as the outcome. Different experimental setups, quantitative levels of biochar addition, various biochar source materials and preparation temperatures, and the effect of natural precipitation in field experiments were the investigated variables. From a total of 95 publications identified for analysis, 384 datasets for Shannon index and 277 datasets for Chao1 index were extracted that described the bacterial diversity in the soils, of which field experiments and locations in China dominated. The application of biochar in soil significantly increased the diversity of soil bacteria but it had no significant effect on the diversity of fungi. Of the different experimental setups, the largest increase in bacterial diversity was seen for field experiments, followed by pot experiments, but laboratory and greenhouse settings did not report a significant increase. In field experiments, natural precipitation had a strong effect, and biochar increased bacterial diversity most in humid conditions , followed by semi-arid conditions (MAP 200–400 mm). Biochar prepared from herbaceous materials was more effective to increase bacterial diversity than other raw materials and the optimal pyrolysis temperature was 350–550 °C. Addition of biochar at various levels produced inconclusive data for Chao1 and Shannon indices, and its effect was less strong than that of the other assessed variables. Biochar is a mixture of organic materials that is typically obtained via pyrolysis of waste biomass under low-oxygen conditions ,2,3. ItsMicroorganisms in the soil can directly or indirectly participate in soil activities ,20,21,22Soil microorganisms are the main decomposers in terrestrial ecosystems and are very active members of the soil, with a wide variety of species , of whic2 flux is still under debate [The potential of biochar application on COr debate , as the r debate ,55,56,57r debate ,59. ThisTo address this, we performed a meta-analysis, based on the concept that was first proposed by Glass in 1976 . A meta-http://scholar.google.com/), Web of Sciences (WoS) (http://apps.webofknowledge.com/) and China National Knowledge Infrastructure . The search terms were “biochar” combined with “soil microorganism”, “soil microbial diversity”, “Shannon index” or “Chao1 index”, and the data collection was completed in June 2022.In order to systematically clarify the effect of biochar addition on soil microbial diversity, we conducted a meta-analysis of the published literature on this subject. The data for the meta-analysis were obtained from three literature databases: Google Scholar (The following inclusion criteria were used to screen the search hits: (i) studies had to include replicated biochar treatments (of at least one biochar addition) and controls (no biochar); (ii) each treatment must include three or more repetitions; (iii) at least one microbial diversity metric (Shannon index or Chao1 index) had to be reported. Publications in languages other than English or Chinese were excluded Since this study focused on the effect of biochar addition on soil microbial diversity, we collected target and explanatory variables from the included literature. For soil microbial diversity as a target variable, we collected the reported Shannon index and Chao1 index of bacteria and fungi. The sample size (n) for the biochar addition and the value of mean, standard deviation (SD) of the reported diversity index and the control treatment were extracted. If the SD was not indicated, it was calculated from the SE as SD = SE√N. In cases where neither SD nor SE was reported, the SD was calculated from the mean . When thA total of 95 papers were identified from WOS, Google Scholar and CNKI database that met the criteria. From those that represented field studies, we collated the location of the sampling sites and plotted their latitude and longitude data on a map .−2 = 1% and 81 t·hm−2 = 3%) [We grouped the various explanatory variables as follows. The experiments were grouped into field, greenhouse, pot, and laboratory experiments. Data from field studies were grouped for MAP with arid (<200 mm), semi-arid (200–400 mm MAP), semi-humid (400–800 mm) and humid conditions (≥800 mm). After standardizing the units of biochar addition (with 27 t·hm−2 = 3%) , the bio−2 = 3%) , with maLRR) was used to measure the effect size and was calculated from the mean treatment value Xt and the mean value in the control Xc as follows:The method for calculating the effect size and variance was taken from the literature . The natv) of each individual effect size was calculated as follows: tn represents the number of the treatment samples, cn the number of the control samples, St is the standard deviation (SD) of the treatment and Sc that of the control groups. We filled in any missing SD values in the collated data by using the “impute_SD” function in the “metagear” package of R4.1.3 software [The variance (software . LRR++), its standard error S(LRR++) and the 95% confidence interval (95%Cl) were calculated as follows:The weighted response ratio  reached 0, the biochar applications was considered to have no significant effect on the assessed variables. A Cl95% above 0 (upper and lower bound) indicated the biochar applications significantly increased the soil microbial diversity (p < 0.05) whereas a Cl95% below zero indicated a biochar application significantly decreased the soil microbial diversity (p < 0.05).Positive and negative values of tau2, the inter-case variance  [ijW):For each observation, we calculated the effect size as described in the literature  using tht cases) . This, aQt-test to determine whether the models could explain a significant amount of variation. For this, Qm . The overall weighted mean effect size estimate was slightly above zero, but the overall heterogeneity was large, with Qt = 34,801.5 (not shown in the figure), requiring the introduction of explanatory variables.The application of biochar significantly increased the bacterial Shannon index compared to the control group (p < 0.0001) and pot experiments (p < 0.05) but it decreased significantly the bacterial Shannon index in laboratory setups (p < 0.01). There was no significant effect on soil bacterial Shannon index in greenhouse studies (p > 0.05).Considering subgroups for the type of experimental setup in p < 0.001 and p < 0.0001, respectively) whereas MAP below 200 mm or between 400 and 800 mm did not have a significant effect. The addition of biochar prepared at temperatures between 350–550 °C significantly (p < 0.0001) increased the bacterial Shannon index, while the addition of biochar prepared below 350 °C significantly (p < 0.05) decreased the bacterial Shannon index. Only biochar prepared from herbaceous raw materials significantly increased the bacterial Shannon index (p < 0.0001), while others biochar types did not show a significant effect on bacterial Shannon index (p < 0.05), but medium level additions did not show a significant effect . However, similar as seen for the Shannon index, the overall heterogeneity was large, with Qt = 136,583 in the heterogeneity test, again requiring an analysis of explanatory variables.Based on 277 datasets that listed bacterial Chao1 indices, the application of biochar significantly increased this diversity index compared to the respective control groups  and now p < 0.05 and p < 0.0001, respectively), similar to the observations based on the Shannon index. The reported effects on Chao1 bacterial diversity were not significant for laboratory or greenhouse experiments (p > 0.05).The Orchard plot for Chao1 diversity  shows thp < 0.0001) observed for MAP > 800 mm. At a biochar preparation temperature between 350–550 °C, the used biochar significantly (p < 0.0001) increased the bacterial Chao1 diversity, similar to the Shannon findings. Biochar prepared from herbaceous material or wood significantly increased the Chao1 index , while biochar prepared from other sources or prepared with modifications did not significantly affect the bacterial Chao1 index (p < 0.005), medium (p < 0.001) and low (p < 0.0001) amounts significantly increased the bacterial Chao1 index. The observed effects produced similar values for high (0.0643) and medium ratios of biochar (0.0688), which were both larger than the effect value for low ratios of biochar addition (0.0486). A similar trend is noted for the Shannon index shown in The degree of influence of the various explanatory variables by subgroup analysis on bacterial Chao1 diversity is shown in o1 index . All thrp > 0.05, Fewer datasets were available on the effect of biochar application on fungal diversity. From the 95 papers that were analyzed, 85 datasets for fungal Shannon index and 69 datasets for fungal Chao1 index were identified. The effect of biochar addition on the fungal diversity (either Shannon or Chao1) was not significant compared to the control groups  on calculating soil microbial diversity may also affect the result of this study. The reason is that the numbers and community compositions of soil microorganism in different taxonomic level are different, and the α diversity indices are inextricably linked to the numbers and community compositions of soil microorganism. For example, the Chao1 index is sensitive to rare species, and the value of Chao1 index will be affected in the phylum level compared to other taxonomic levels. Similarity, the other α diversity (Shannon and Simpson index) of soil microorganism varies at different taxonomic levels. In our study, the data we collected did not consider above reason and this may cause some error on our result. So, it is necessary to consider the same taxonomic level in the future calculation and collation of soil microbial diversity. In our meta-analysis, only a small number of papers were located outside of China. These regions have different climates from China, where four major climates are distributed, including temperate continental, highland alpine, temperate monsoon, and subtropical monsoon climates. The climates of the study sites outside of China include semi-arid Mediterranean climate, tropical rainforest climate, etc. . We beliThe total effect value reported here through the random effects model showed that biochar could significantly improve soil bacterial diversity, however, the Q-test identified a high overall heterogeneity, necessitating the use of a mixed effect model to evaluate the degree of influence of different experimental types and subgroup variants.The reported diversity indices for soil bacterial communities were generally higher for greenhouse, pot and laboratory experiments than for field experiments. However, in our meta-analysis, the effect of biochar on enhancing soil bacterial diversity was higher in the field experiments than in other experimental setups. We believe that there are two reasons for this: i. The field experiments produced the largest dataset of all experimental types, and the larger the dataset, the more reliable the outcome is. ii. In most laboratory, greenhouse and pot experiments the soil bacterial habitat would be more stable, without dramatic fluctuation in diurnal or daily temperature changes, and with an adequate and constant nutrients supply there would be fewer harsh environmental conditions, thus leading to an insignificant biochar response. In contrast, in the field experiments, the habitat conditions of soil bacteria would be more strongly fluctuating, and when biochar is present this amendment can obviously enhance soil quality, with soil bacteria responding more to it, as shown by an increase in diversity.The meta-analysis identified that the response of soil bacterial diversity depended on the addition level of biochar. At a high level of addition (>3%) biochar significantly increased the Shannon index of soil bacteria  and bothBiochar is a carbon-rich material, and carbon is one of the nutrients necessary for biological growth and reproduction. We consider an increased metabolic capacity and activity of soil bacteria is likely after the addition of biochar, and the large surface area and porous structure of biochar can provide space for bacteria to live, thus leading to an increase in bacterial diversity in the soil after the addition of biochar. When the amount of biochar added to the soil increases, the soil bacteria have more habitats and are less likely to be preyed on, thus increasing the diversity of soil bacteria . Of courp < 0.0001). Precipitation levels affect the soil water content, which as an important indicator of soil quality and is the main influencing factor of soil microbial diversity [Precipitation levels in the locations of field experiments was selected as one of the explanatory variables in an attempt to explain the large heterogeneity of the overall effect value, for which the data were grouped in arid (<200 mm), semi-arid (200–400 mm), semi-humid (400–800 mm) and humid conditions (>800 mm). The subsequent subgroup analysis  showed tiversity . We assuiversity ; Bickel iversity . WhetherQm value represents the heterogeneity caused by the explanatory variables, with a higher value indicating a greater effect of the explanatory variables on the reported diversity. Based on the Shannon index, the different raw materials for biochar preparation produced a Qm value of 18.3591 (p < 0.05) and the different preparation temperatures resulted in a Qm of 21.0141 (p < 0.05). This illustrated that both the biochar type and the preparation temperature had a significant modulating effect on soil bacterial diversity by Shannon (p < 0.01) (Qm = 50.3364) and temperatures (Qm = 36.8704) also has a significant regulatory effect on the Chao1 index of soil bacteria (p < 0.0001). (p < 0.0001 for both Shannon and Chao1). The properties of biochar prepared from different raw materials will vary considerably. For example, Lu et al. found that biochar produced from herbal materials had larger pore sizes and larger transmissive pore volumes [Since biochar can support growth of soil microorganisms by the release of nutrients in the soil, we analyzed what role of raw materials and preparation temperatures of the applied biochar had. For this, we used the Q-test. The  < 0.01) . Biochar0.0001). . Among t volumes . Brendov volumes . Soria e volumes .p < 0.0001 for both indices). That the pyrolysis temperature affects biochar properties was demonstrated in several studies, for example, Das et al. found that the cation exchange capacity of biochar increased with increasing pyrolysis temperature, but the organic carbon content decreased [p adsorption [As for the different biochar preparation temperatures, pyrolysis of raw materials at 350–550 °C most strongly increased soil bacterial diversity  the addition of biochar to soil can have a significant effect on soil bacterial diversity, though not on soil fungal diversity; (ii) the effect of biochar on soil bacterial diversity was significantly influenced by the type of raw material used for biochar preparation, by the temperatures of biochar pyrolysis and by the addition ratios of biochar to soil; (iii) field experiments were most often recorded in the set of the analyzed data, and these may be the most suitable to assess the effect of biochar on soil bacterial diversity under natural conditions. In our meta-analysis, the field experiments resulted in a greater overall regulatory effect compared to other experiment types; (iv) for field experiments, the increase of biochar-dependent soil bacterial diversity was greater under medium precipitation conditions; (v) medium level biochar addition is more effective in enhancing soil bacterial diversity than low or high level addition; (vi) biochar prepared from herbaceous materials can better enhance soil bacterial diversity than biochar produced from other sources; (vii) biochar prepared at moderate pyrolysis temperatures best promotes soil bacterial diversity. Therefore, we believe that it is crucial to optimize the quality of biochar before application in future research on the application of biochar in soil. This includes the selection of suitable raw materials for preparation, the appropriate preparation temperature and the amount of biochar to be applied. Finally, by optimizing biochar addition measures and adapting biochar addition programs in different regions, and promote the advantages of soil microorganisms, to improve the soil quality and sustainable in soil utilization in the further.


The resulting deactivated cement asbestos powder (DCAP), a mixture of Ca-Mg-Al silicates and glass, was compounded with Pavatekno Gold 200 (PT) and Pavafloor H200/E (PF), two different epoxy resins (bisphenol A epichlorohydrin) for flooring applications. The addition of the DCAP filler to the PF samples causes a slight but acceptable decrease in the relevant mechanical properties  upon increasing DCAP content. The addition of the DCAP filler to pure epoxy (PT resin) causes a slight decrease in the tensile and flexural strengths with increasing DCAP content, while the compressive strength is almost unaffected, and the Shore hardness increases. The main mechanical properties of the PT samples are significantly better than those of the filler-bearing sample of normal production. Overall, these results suggest that DCAP can be advantageously used as filler in addition to, or in substitution for, commercial barite. In particular, the sample with 20 wt% of DCAP is the best performing in terms of compressive, tensile, and flexural strengths, whereas the sample with 30 wt% of DCAP shows the highest Shore hardness, which is an important property to be considered in flooring applications.Cement asbestos slates, commonly known as Eternit The massive increase in harmful by-products of industrial activities in recent decades has triggered an equally massive impulse for their treatment. The minimum goal of removing risks for the environment and health has been later complemented by the aim of reinserting the treated materials within the economic cycle.The goal of this work is to use the powder obtained by the deactivation of cement asbestos slates (CAS) through thermal treatments ,2 as a nIn recent years, a number of recycling routes of thermally treated CAS have been investigated, providing satisfactory results . Among Recycling or upcycling of an inorganic powder can often be achieved by its application as a filler in polymers. In this case, a much larger amount of recycled material can be employed  is regarded as an inexpensive mineral filler that can be utilized at high filler loadings and improve the flexural modulus. It also exhibits an excellent surface finish, as well as viscosity control [Commonly used mineral fillers in the polymeric industry are talc, limestone, silica, clay, mica, wollastonite, and barite. Sheet-like platy fillers, such as talc, mica, and kaolin, have been reported to enhance rigidity . In addi control .In terms of production volume and consumption, epoxy resins occupy an important place in the polymer industry. A variety of filler–epoxy composites have been tested so far, with the aim of either reducing the cost of finished products by reducing the cost of expensive binders or to give to the composite various functional properties. Among the low-cost, micron-sized mineral fillers so far investigated, there are fly ash ,26, bricIn the present paper, we employed thermally deactivated cement asbestos powder (DCAP) as a filler in the epoxy resin used for flooring applications, without further surface treatment. These applications were selected because they require good mechanical properties and are usually fulfilled by long-lasting thermoset materials. The results show that, for some formulations, the mechanical properties of DCAP-bearing composites are superior compared to those of normal production, suggesting a promising recycling route for the DCAP that matches the rising demand for more efficient materials in terms of low costs, sustainability, and improved mechanical behaviour and processing.DCAP was mixed as inorganic filler with two different bisphenol A (BPA) epichlorohydrin (ECH)-based epoxy resins. The resins are commercially known as Pavafloor H200/E (henceforth Pavafloor or PF) and Pavatekno Gold 200 (henceforth Pavatekno or PT), both produced by Pava Resine Srl and typically used for flooring in civil and industrial buildings. The PT is a filler-free BPA ECH resin, while PF is a solvent-free pigmented epoxy formulation with a pre-existing inorganic filler of barite included in the resin. PF is also a BPA ECH resin, but according to datasheet, it also contains 10 wt% polypropylene glycol (PPG)-epichlorhydrin copolymer and 4 wt% di(propylene glycol) dibenzoate. Both resins were combined with the hardener, composed of a mixture of benzyl alcohol, isophorone diamine (IPDA), and an oligomer of IPDA with epichlorohydrin and bisphenol.The samples were prepared by adding 10%, 20%, and 30% wt% of DCAP to the PT resin, and 2%, 5%, and 10 wt% to the PF resin, according to Due to the lower viscosity of the hardener compared to the resins, we first mixed the DCAP with the hardener using a laboratory dissolver mixer for 5 min. We then added the resin and repeated the mixing with the dissolver mixer for another 5 min. The mixture was then left in a vacuum chamber for about 5 min to remove the entrapped air, filled into silicon moulds , equipped with a 5 kN load cell and several appropriate tools. Each test was carried out with at least 4 measurements and the results were averaged, as reported in Compression test was performed on a ~5 × 12.5 mm resin cylinder at a rate of 1.3 mm/min. Tensile test was obtained by stretching a dumbbell-shaped specimen of resin with dimension according to ISO 527 type 1, and a rate of 1 mm/min. Flexural test was obtained by bending a rectangular prism of resin 2 × 2 × 30 mm at a rate of 1 mm/min.Hardness test was carried out using a Vulcanoline digital Shore durometer, model VLDSD6610D, with a conical R0.1 indenter, DIN 53505 and ASTM D2240 type D scale, and a resulting force of 44.48 N. All data, 10 measurements for each sample, are reported in g) was determined by differential scanning calorimetry (DSC) with a Mettler-Toledo DSC1 Star System under a nitrogen atmosphere. The instrument was calibrated using Indium melting temperature and enthalpy, and corrected for empty cell baseline. About 10–15 mg in mass was extracted from a thin film of each sample by cutting a disk of ~3 mm in diameter and encapsulated into 40 μL Al pan. The experiments were conducted by performing two heating and one cooling ramp, between −20 °C and 160 °C, at 20 °C/min. The Tg values calculated with the midpoint method for each sample are reported in Glass transition temperature (TSecondary electron (SE) images and energy dispersive X-ray (EDX) analyses were acquired at the Platform of Microscopy of the University of Milano-Bicocca with a Tescan VEGA TS 5136XM and a Zeiss Gemini 500 scanning electron microscopes (SEMs). SE images were acquired on the breaking surfaces after performing tensile and flexural tests to gain insights into the fracture mechanism. To avoid electrostatic charging, the samples were coated with a thin (~20 nm) graphite film.The influence of fillers on the mechanical properties of a composite is determined by their size, shape, and nature of the interaction with the matrix . The deaThe DCAP-bearing PF samples show quite similar compressive stress–strain curves compared to the PF0, apart from sample PF2, which shows higher strain values under same stress conditions A, i.e., The anomalous behaviour of the PF2 sample can also be tracked on the tensile and flexural tests, where the PF2 sample shows a completely different stress/force–strain curve C,E. In cTherefore, the increase in DCAP in the PF samples tends to slightly worsen the mechanical properties. However, their decrease can be considered acceptable especially considering the large amount of inorganic filler (DCAP + barite) mixed with the resin. A decrease in the properties of polymers are also not surprising when they are mixed with particles with low specific surface area, as is the case of DCAP − being composed by particles/aggregates up to 80 µm . GeneralThe anomalous behaviour of PF2 was initially considered to be due to a problem during the sample preparation. Then, we reconsidered this hypothesis after the preparation of a new sample that showed similar results. It seems that the addition of 2 wt% of DCAP to a resin already containing 38 wt% of barite builds up a critical filler concentration that dramatically affects the mechanical properties of the resin. A similar phenomenon was observed by  on talc-The mechanical tests on PT samples generally show more consistent stress–strain curves as function of increasing DCAP fraction , albeit In the tensile test, PT samples retain the same stress–strain trends regarding the DCAP content D, but shIn the flexural test, we observe a progressive decrease in the flexural strength with increasing DCAP content (from 74.6 to ~50 MPa), in contrast with the Young modulus that shows a sawtooth pattern, with the maximum value recorded for the sample PT20 .PT samples display a general decrease in the tensile and flexural strength with increasing DCAP content, whereas the compressive strength remains constant or slightly increases. This behaviour could be explained by the weak cohesive forces between the inorganic filler and the polymer, since the particles–resin boundaries can act as cracking sites. The frequency of this phenomenon is proportional to the filler content. Although the direct comparison between the PF and PT samples is complicated by the different natures of the host polymer matrix, the marginal decrease in the main mechanical properties and, especially, the superior mechanical properties of sample PT30 over sample PF0 with similar inorganic load , suggestg. In fact, the first heating irreversibly resets this stress, representing the thermal history of the sample. So, much more reliable results can be inferred from the second heating ramp , PT samples consistently show a typical glass transition represented by the change in the slope for heat. Instead, PF samples show an endothermal “bathtub” path that, in addition to the Tg, indicates the formation of a mesophase. The presence of such mesophase is an indicator of microscale separation, usually found in thermoplastic elastomers, such as styrene-ethylene-butylene-styrene (SEBS) . This ing of the composite significantly, resulting in both an increase [g of the composites to the filler size, in which an increase in the interfacial area between the filler and the resin leads to a reduction in the polymer chain mobility with a subsequent increase in Tg.The addition of inorganic filler may vary the Tincrease  or a decincrease  dependinincrease . For insincrease  relates g significantly, which is ~55 °C for the PF samples and ~59 °C for PT samples. Interestingly, sample PF2 also exhibits values in line with the series. An exception is sample PT10 showing a slight increase in Tg at ~61.5 °C. The low dependence of Tg on the filler load may indicate a weak interfacial strength between the micron-sized fillers and the resin. Indeed, only a small aliquot of the DCAP (~10% by volume) has a sub-micrometric (<1 µm) size  size . This suace area . Similarace area  studyingSEM images of the filler dispersion in resin, the typical grain morphology, and their average particle size distribution are reported in At the SEM, the grain size distribution of the DCAP appears heterogeneous, consisting either of individual particles generally down to 1 µm in size A, or of Barite shows a slightly more homogeneous grain size distribution compared to DCAP, as is also shown by DLS . In factRegarding the fracture mechanisms, we studied the morphology of the fracture surfaces after tensile and flexural tests. Therefore, DCAP seems to have a greater adhesion strength with resin than barite. The comparison between the gran size distributions of barite and DCAP as determined by DLS  shows th(1)Cement–asbestos slates, a building material that still poses serious environmental and health hazards, can be detoxified by a sustainable thermal treatment, powdered and successfully mixed, potentially in large amounts, to commercial resin formulations of different compositions without any further surface treatment.(2)The addition of DCAP filler to an epoxy resin for flooring applications that already contained barite filler (PF resin) causes a slight (but still acceptable) worsening of the main mechanical properties  with increasing DCAP content. An exception is sample PF2, showing lower elasticity and higher plasticity. Repeated tests on this formulation confirmed previous results, suggesting that 2 wt% of DCAP added to the PF resin is a critical value worthy of further investigation. The other samples instead describe a trend in mechanical properties that encourages realistic applications where loading is 10% or more.(3)The addition of DCAP filler to the neat epoxy for flooring applications (PT resin) causes a slight decrease in the tensile and flexural strengths, with increasing DCAP content, while the compressive strength is almost unaffected, and the Shore hardness increases. Overall, the PT20 sample (20 wt% of DCAP added) shows the best technical properties.(4)g of ~59 °C, which is higher than the average Tg (~55 °C) of the PF samples, indicating that PT is a better product for flooring applications.The thermal behaviour of both PF and PT samples are only marginally affected by the addition of DCAP. However, the PT samples  show an average T(5)The comparison between PF and PT composites reveals that the main mechanical properties of the PT samples are significantly better than those of the PF0 sample, i.e., the filler-bearing sample of normal production, suggesting that DCAP can be advantageously used as a filler in substitution for commercial barite. In particular, the PT20 sample (20 wt% of DCAP filler) seems very promising for flooring applications.The mechanical and thermal properties and fracture morphology of epoxy resins filled with deactivated cement asbestos have been investigated, coming to the following conclusions: