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In this work, the nanocomposites of chitosan containing carbon nanotubes (CNT) and maghemite nanoparticles have been prepared by solution casting method. Techniques such as Raman spectroscopy, SEM, TEM, dielectric relaxation spectroscopy, and VSM studies were made. The incorporation of CNT in to the chitosan matrix and also the interaction between the CNT and the maghemite nanoparticles were studied using Raman spectroscopy. The dielectric constant of Chitosan-CNT composites turned from positive to negative at low frequency when CNT concentration increased from 10 to 20wt%. Interestingly, addition of 20wt% of maghemite nanoparticles into the Cs-CNT nanocomposites affected both the dielectric property and the conductivity of the composite. VSM measurement shows that the prepared maghemite nanoparticles and the Cs-CNT-maghemite nanocomposites are superparamagnetic materials. Observed dielectric characteristics and the electrical conductivity of the samples have been explained by using a model. Tuning of negative permittivity in the chitosan-CNT nanocomposites by using maghemite nanoparticles could be useful as metamaterials.

In this work, an eco-friendly “green” nanocomposite of chitosan containing graphite and maghemite (g-Fe2O3) nanoparticles were prepared by solution casting method. The effect of g-Fe2O3 nanoparticles on structural, electric and dielectric properties of Chitosan-graphite (Cs-graphite) composites was investigated. The dielectric constant of Cs-graphite composites increased with incorporation of g-Fe2O3 nanoparticles. Among the composites Cs-20% graphite - 20% g-Fe2O3 has dielectric constant of ~16.5 at 1 MHz at room temperature. With increase in temperature the dielectric constant varied significantly. The conductivity of Cs-graphite is enhanced by one order of magnitude with addition of g-Fe2O3 nanoparticles, and the value is found to be 5.7x10-6 S/cm. Various parameters such as dielectric constant, dielectric loss, electric modulus, conductivity, activation energy were analyzed. Magnetic measurement of g-Fe2O3 nanoparticles and the PNCs showed superparamagnetic behaviour. A model is proposed to explain the observed dielectric behavior of polymer nanocomposites (PNCs). The formation of microcapacitors by incorporation of maghemite nanoparticles between graphite is proposed.

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a climate‐resilient cereal crop widely grown in arid and semiarid environments and an important crop for food, fodder, and nutritional security. This study was aimed at evaluating genetic variation(s) for drought tolerance‐related traits in a set of 29 seed (B) and 27 restorer (R) lines and identifying pearl millet inbreds for hybrid development. Field experiments were conducted in a split‐plot in randomized complete block design with three replications for 2 years. Moisture regimes (irrigated and rainfed) were kept as main plot treatments, and the genotypes were used as subplot treatments. Principal component analysis and neighbor joining clustering revealed the presence of greater genetic diversity between B and R lines. Combined analysis of variance showed significant difference(s) between the lines, treatments, and years. Genotype + genotype × environment interaction biplot indicated the significant environment and treatment effect(s) on grain yield per plant, number of seeds per plant, and 1000‐grain weight. Rank summation index based on percentage reduction and multi‐trait stability index analyses for the above three traits identified the best adapted genotypes for rainfed conditions. Based on these analyses, seven seed parents (ARCH41B, ARCH01B, ARCH13B, ARCH44B, ARCH09B, ARCH24B, and ARCH30B) and six pollinators (ARCH36R, ARCH68R, ARCH22R, ARCH63R, ARCH50R, and ARCH60R) were identified as potential parents to develop high‐yielding and drought‐tolerant pearl millet hybrids for the semiarid tropics. Core Ideas: The objective of this study was to identify potential drought‐tolerant seed and pollinator lines for pearl millet hybrid development.The Presence of greater genetic diversity between the B and R lines of pearl millet was revealed.The Genotype plus genotype × environment interaction (GGE) biplot indicated the significant environment and treatment effect(s).Seven seed parents and six pollinators were identified as potential parents to develop high‐yielding hybrids for semiarid tropics. [ABSTRACT FROM AUTHOR]

Grain sorghum [Sorghum bicolor (L.) Moench] is an important crop native to Africa and grown in many subtropical and temperate regions worldwide. The variability in production environments underscores the plasticity of sorghum genotypes and provides an opportunity to predict sorghum hybrid performance in novel environments. Reaction norms informed by envirotype data can aid in modeling the differential responses of genotypes across multi‐environment trials and ultimately increase the prediction accuracies of hybrid performance. In this study, a combination of genomic and enviromic information was applied to predict grain sorghum hybrid performance across United States sorghum production environments. Seven models based on additive, dominance, environment, and envirotype effects in two forms, and their interactions were tested under three cross‐validation schemes that simulate genomic prediction scenarios encountered by breeding programs. Relationship matrices for hybrids and environments were created from molecular and envirotypic data, respectively, to predict hybrid performance under a hierarchal Bayesian framework. When predicting unobserved environments, the envirotypic reaction norm model based on typologies produced the highest prediction accuracies for every temperate environment, but results vary in the subtropical environments, which has not been demonstrated in prior enviromic research. This study also demonstrated for the first time that envirotype data can effectively define established United States sorghum production regions and may assist breeders in resource allocation. Results support using sparse hybrid trials when breeding programs apply genomic predictions. Therefore, envirotype‐assisted genomic prediction models can expand the information available to a sorghum breeding program and aid breeders in efficiently designing hybrid trials. Core Ideas: Envirotyping can increase the information available to a plant breeding program.Enviromic‐assisted genomic prediction can increase the prediction accuracy of unobserved environments.Genomic prediction can greatly support a breeding program when combined with sparse hybrid trials. [ABSTRACT FROM AUTHOR]

The United Nations declared 2023 as the International Year of Millets to highlight the value and importance of millets, which are cereals grown in arid and semi-arid regions with low inputs and high resilience to climate change. Millets contribute to the Sustainable Development Goals, particularly in terms of food security, healthy diets, economic growth, responsible consumption, and climate action. Pearl millet is one of the most widely grown millets and plays a crucial role in achieving self-sufficiency and food security in dryland areas. It is a climate-resilient crop that is gluten-free and rich in essential micronutrients. This special issue of Crop Science covers various aspects of millet research, including crop improvement, phenotyping, crop physiology, management, nutritional quality, and grain composition. The goal is to promote global awareness of millets and their potential for diversifying and intensifying agricultural systems. Future research should focus on integrating disciplines, improving pre-breeding and phenotyping efforts, and expanding the use of millets for different purposes. Funding for this special issue was provided by the Feed the Future Innovation Lab for Collaborative Research on Sustainable Intensification at Kansas State University. [Extracted from the article]

Abstract Genomic selection in maize (Zea mays L.) has been one factor that has increased the rate of genetic gain when compared with other cereals. However, the technological foundations in maize also exist in other cereal crops that would allow prediction of hybrid performance based on general (GCA) and specific (SCA) combining abilities applied through genomic‐enabled prediction models. Further, the incorporation of genotype × environment (G × E) interaction effects present an opportunity to deploy hybrids to targeted environments. To test these concepts, a factorial mating design of elite yet divergent grain sorghum lines generated hybrids for evaluation. Inbred parents were genotyped, and markers were used to assess population structure and develop the genomic relationship matrix (GRM). Grain yield, height, and days to anthesis were collected for hybrids in replicated trials, and best linear unbiased estimates were used to train classical GCA‐SCA–based and genomic (GB) models under a hierarchical Bayesian framework. To incorporate population structure, GB was fitted using the GRM of both parents and hybrids. For GB models, G × E interaction effects were included by the Hadamard product between GRM and environments. A leave‐one‐out cross‐validation scheme was used to study the prediction capacity of models. Classical and genomic models effectively predicted hybrid performance and prediction accuracy increased by including genomic data. Genomic models effectively partitioned the variation due to GCA, SCA, and their interaction with the environment. A strategy to implement genomic selection for hybrid sorghum [Sorghum bicolor (L.) Moench] breeding is presented herein.

Anthracnose, incited by Colletotrichum sublineola, is the most destructive foliar disease of sorghum and, under severe conditions, yield losses can exceed 80% on susceptible cultivars. The hyper-variable nature of the pathogen makes its management challenging despite the occurrence of several resistant sources. In this study, the genetic variability and pathogenicity of 140 isolates of C. sublineola, which were sequenced using restriction site-associated sequencing (RAD-Seq), resulted in 1244 quality SNPs. The genetic relationship based on the SNP data showed low to high genetic diversity based on isolates' origin. Isolates from Georgia and North Carolina were grouped into multiple clusters with some level of genetic relationships to each other. Even though some isolates from Texas formed a cluster, others clustered with isolates from Puerto Rico. The isolates from Puerto Rico showed scattered distribution, indicating the diverse nature of these isolates. A population structure and cluster analysis revealed that the genetic variation was stratified into eight populations and one admixture group. The virulence pattern of 30 sequenced isolates on 18 sorghum differential lines revealed 27 new pathotypes. SC748-5, SC112-14, and Brandes were resistant to all the tested isolates, while BTx623 was susceptible to all. Line TAM428 was susceptible to all the pathotypes, except for pathotype 26. Future use of the 18 differentials employed in this study, which contains cultivars/lines which have been used in the Americas, Asia, and Africa, could allow for better characterization of C. sublineola pathotypes at a global level, thus accelerating the development of sorghum lines with stable resistance to the anthracnose pathogen. [ABSTRACT FROM AUTHOR]

This study estimates the environmental efficiency of 150 economies during the period of 2010–2017 to understand the environmental efficiency trend worldwide. This research adopts the meta-Malmquist approach to compare and capture the dynamic change in environmental efficiency among different income groups. The empirical results indicate that among the four income groups, only the low-income group suffers from regression in terms of environmental efficiency, while the high-income group achieves the greatest progress. For the high-income group, the source of improvement originates from the frontier shift rather than from efficiency change. By contrast, the improvement of the lower-income groups results from the catching-up effect. With regard to the effect of the Paris Agreement, only the lower middle-income group exhibits a statistical difference between the two periods, and environmental efficiency increases after the adoption of the Paris Agreement. The fight against global warming cannot succeed by relying only on specific countries. The whole world must cooperate and improve together, and thus, additional help must be devoted to the low-income group. The statistical results support that differences exist in terms of environmental efficiency among the four income groups. In particular, the low-income group is deteriorating.

Sorghum is a unique natural food source of 3-deoxyanthocyanidins (3-DA) polyphenols. This work evaluated the effect of acidification on sorghum extracts post pressurized liquid extraction (PLE) and its ability to increase the identification and quantification of 3-DA. The sorghum genotypes included Sumac and PI570366 (bran only) and SC991 (leaf and leaf sheath tissue). The acidification of the PLE extracts was carried out with methanol–HCl solutions at various concentrations (0, 0.5, 1, 2, and 4%, v/v). Changes in color were determined using L*a*b*. The overall phenolic composition was estimated with the total phenolic content and the DPPH free radical scavenging assays. Quantitative and qualitative chromatographic methods determined the phenolic profile. Color analysis showed that the redness and color saturation increased after acidification. No statistical difference was found in the total phenolic content of the acidified extracts, except for SC991, which was increased. There were no differences in the antioxidant capacity following acidification in all samples. For chromatographic analysis, luteolinidin was predominant in the extracts and the 3-DA content increased after acid treatment. However, some flavonoid and phenolic acid concentrations decreased following acid treatment, including taxifolin, quercetin, and chlorogenic acid. Interestingly, 0.5% v/v HCl acidification was sufficient to increase the color, allow the detection of 5-methoxyluteolinidin, and to increase luteolinidin and 7-methoxyapigenidin by at least twofold. [ABSTRACT FROM AUTHOR]

The traditional use of Murraya koenigii as Asian folk medicine prompted us to investigate its wound healing ability. Three carbazole alkaloids (mahanine (1), mahanimbicine (2), mahanimbine (3)), essential oil and ethanol extract of Murraya koenigii were investigated for their efficacy in healing subcutaneous wounds. Topical application of the three alkaloids, essential oil and crude extract on 8 mm wounds created on the dorsal skin of rats was monitored for 18 days. Wound contraction rate and epithelialization duration were calculated, while wound granulation and collagen deposition were evaluated via histological method. Wound contraction rates were obvious by day 4 for the group treated with extract (19.25%) and the group treated with mahanimbicine (2) (12.60%), while complete epithelialization was achieved on day 18 for all treatment groups. Wounds treated with mahanimbicine (2) (88.54%) and extract of M. koenigii (91.78%) showed the highest rate of collagen deposition with well-organized collagen bands, formation of fibroblasts, hair follicle buds and with reduced inflammatory cells compared to wounds treated with mahanine (1), mahanimbine (3) and essential oil. The study revealed the potential of mahanimbicine (2) and crude extract of M. koenigii in facilitation and acceleration of wound healing.

A total of three carbazole alkaloids and essential oil from the leaves of Murraya koenigii (Rutaceae) were obtained and examined for their effects on the growth of five antibiotic resistant pathogenic bacteria and three tumor cell lines (MCF-7, P 388 and Hela). The structures of these carbazoles were elucidated based on spectroscopy data and compared with literature data, hence, were identified as mahanine (1), mahanimbicine (2) and mahanimbine (3). The chemical constituents of the essential oil were identified using Gas Chromatography-Mass Spectroscopy (GCMS). These compounds exhibited potent inhibition against antibiotic resistant bacteria such as Staphylococcus aureus (210P JTU), Psedomonas aeruginosa (ATCC 25619), Klebsiella pneumonia (SR1-TU), Escherchia coli (NI23 JTU) and Streptococcus pneumoniae (SR16677-PRSP) with significant minimum inhibition concentration (MIC) values (25.0–175.0 mg/mL) and minimum bacteriacidal concentrations (MBC) (100.0–500.0 mg/mL). The isolated compounds showed significant antitumor activity against MCF-7, Hela and P388 cell lines. Mahanimbine (3) and essential oil in particular showed potent antibacteria and cytotoxic effect with dose dependent trends (≤5.0 μg/mL). The findings from this investigation are the first report of carbazole alkaloids’ potential against antibiotic resistant clinical bacteria, MCF-7 and P388 cell lines.