Enhancing cold and drought tolerance in cotton: a protective role of SikCOR413PM1.

The present study explored the potential role of cold-regulated plasma membrane protein COR413PM1 isolated from Saussurea involucrata (Matsum. & Koidz)(SikCOR413PM1), in enhancing cotton (Gossypium hirsutum) tolerance to cold and drought stresses through transgenic methods. Under cold and drought stresses, the survival rate and the fresh and dry weights of the SikCOR413PM1-overexpressing lines were higher than those of the wild-type plants, and the degree of leaf withering was much lower. Besides, overexpressing SikCOR413PM1 overexpression increased the relative water content, reduced malondialdehyde content and relative conductivity, and elevated proline and soluble sugar levels in cotton seedlings. These findings suggest that SikCOR413PM1 minimizes cell membrane damage and boosts plant stability under challenging conditions. Additionally, overexpression of this gene upregulated antioxidant enzyme-related genes in cotton seedlings, resulting in enhanced antioxidant enzyme activity, lowered peroxide content, and reduced oxidative stress. SikCOR413PM1 overexpression also modulated the expression of stress-related genes (GhDREB1A, GhDREB1B, GhDREB1C, GhERF2, GhNAC3, and GhRD22). In field trials, the transgenic cotton plants overexpressing SikCOR413PM1 displayed high yields and increased environmental tolerance. Our study thus demonstrates the role of SikCOR413PM1 in regulating stress-related genes, osmotic adjustment factors, and peroxide content while preserving cell membrane stability and improving cold and drought tolerance in cotton.

Suppression of dry root rot disease caused by Rhizoctonia bataticola (Taub.) Butler in chickpea plants by application of thiamine loaded chitosan nanoparticles.

The present study evaluated the effect of thiamine loaded chitosan nanoparticle (TChNp) on chickpea plant growth under greenhouse condition. TChNp treated plants showed increased number of leaves, branches, shoot/root length, number of secondary roots and plant dry weight. Enhanced nodulation with larger nodules was observed in TChNp treated chickpea plants. A significant increase in the number of flowers, pods and grain yield was observed in the TChNp treated chickpea plants compared to the chitosan and untreated control. The TChNps showed direct antifungal activity towards Rhizoctonia bataticola as evidenced by in vitro and SEM analyses, which might be due to the solubility and size of the nanoparticle. TChNps treated chickpea plants challenged with R. bataticola showed significant reduction in plant mortality compared to infected untreated control under pot condition. These results indicate the potential of the TChNps in enhancing the yield and suppressing the dry root rot disease in chickpea.

Melatonin enhances plant growth and abiotic stress tolerance in soybean plants.

Melatonin is a well-known agent that plays multiple roles in animals. Its possible function in plants is less clear. In the present study, we tested the effect of melatonin (N-acetyl-5-methoxytryptamine) on soybean growth and development. Coating seeds with melatonin significantly promoted soybean growth as judged from leaf size and plant height. This enhancement was also observed in soybean production and their fatty acid content. Melatonin increased pod number and seed number, but not 100-seed weight. Melatonin also improved soybean tolerance to salt and drought stresses. Transcriptome analysis revealed that salt stress inhibited expressions of genes related to binding, oxidoreductase activity/process, and secondary metabolic processes. Melatonin up-regulated expressions of the genes inhibited by salt stress, and hence alleviated the inhibitory effects of salt stress on gene expressions. Further detailed analysis of the affected pathways documents that melatonin probably achieved its promotional roles in soybean through enhancement of genes involved in cell division, photosynthesis, carbohydrate metabolism, fatty acid biosynthesis, and ascorbate metabolism. Our results demonstrate that melatonin has significant potential for improvement of soybean growth and seed production. Further study should uncover more about the molecular mechanisms of melatonin's function in soybeans and other crops.

Contributions of Genome Editing Technologies Towards Improved Nutrition, Environmental Sustainability and Poverty Reduction.

The Sustainable Development Goals (SDGs) were launched in 2015, with the top three goals being poverty eradication, improved food security and increased human health. All 17 SDGs have a target achievement date of 2030. These are ambitious and inspirational goals that require substantial innovation and technology adoption for successful achievement. Innovations in plant breeding have substantially contributed to transforming the efficiency of food production since the mid 20th century, with innovations emerging in the current millennium demonstrating enhanced potential to improve crop yields, the nutritional values of food crops and environmental impacts. These outcomes underpin several SDGs, but in particular the first three. As climate change is expected to become increasingly variable, with greater impacts on agriculture, the ability to ensure increased food production is going to be increasingly important, as higher yields directly contribute to reducing poverty. This article reviews recent reports of potential contributions from genome editing technologies in terms of increased yield, enhanced nutrition and greater sustainability, highlighting their importance for achieving the leading three SDGs.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 4: ß-Lactams: amoxicillin and penicillin V.

The specific concentrations of amoxicillin and penicillin V in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for amoxicillin, whilst for penicillin V no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these two antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 7: Amphenicols: florfenicol and thiamphenicol.

The specific concentrations of florfenicol and thiamphenicol in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield, were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for florfenicol was estimated. However, due to the lack of data, the calculation of the FARSC for thiamphenicol was not possible until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for florfenicol, whilst for thiamphenicol no suitable data for the assessment were available. Uncertainties and data gaps associated to the levels reported were addressed. For florfenicol, it was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC, whereas for thiamphenicol, the recommendation was to generate the data required to fill the gaps which prevented the FARSC calculation.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 6: Macrolides: tilmicosin, tylosin and tylvalosin.

The specific concentrations of tilmicosin, tylosin and tylvalosin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield, were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for tilmicosin and tylosin, whilst for tylvalosin no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these three antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 8: Pleuromutilins: tiamulin and valnemulin.

The specific concentrations of tiamulin and valnemulin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for tiamulin, while for valnemulin no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these two antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 10: Quinolones: flumequine and oxolinic acid.

The specific concentrations of flumequine and oxolinic acid in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data are available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. No suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 11: Sulfonamides.

The specific concentrations of sulfonamides in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data are available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were identified for three sulfonamides: sulfamethazine, sulfathiazole and sulfamerazine. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 1: Methodology, general data gaps and uncertainties.

The European Commission requested EFSA to assess, in collaboration with EMA, the specific concentrations of antimicrobials resulting from cross-contamination in non-target feed for food-producing animals below which there would not be an effect on the emergence of, and/or selection for, resistance in microbial agents relevant for human and animal health, as well as the levels of the antimicrobials which could have a growth promotion/increase yield effect. The assessment was performed for 24 antimicrobial active substances, as specified in the mandate. This scientific opinion describes the methodology used, and the main associated data gaps and uncertainties. To estimate the antimicrobial levels in the non-target feed that would not result in emergence of, and/or selection for, resistance, a model was developed. This 'Feed Antimicrobial Resistance Selection Concentration' (FARSC) model is based on the minimal selective concentration (MSC), or the predicted MSC (PMSC) if MSC for the most susceptible bacterial species is unavailable, the fraction of antimicrobial dose available for exposure to microorganisms in the large intestine or rumen (considering pharmacokinetic parameters), the daily faecal output or rumen volume and the daily feed intake. Currently, lack of data prevents the establishment of PMSC and/or FARSC for several antimicrobials and animal species. To address growth promotion, data from an extensive literature search were used. Specific assessments of the different substances grouped by antimicrobial classes are addressed in separate scientific opinions. General conclusions and recommendations were made.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 3: Amprolium.

The specific concentrations of amprolium in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC for amprolium, it was not possible to conclude the assessment. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of amprolium in feed that showed to have an effect on growth promotion/increased yield were reported. The lack of antibacterial activity at clinically relevant concentrations for amprolium suggests that further studies relating to bacterial resistance are not a priority.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 5: Lincosamides: lincomycin.

The specific concentrations of lincomycin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of lincomycin in feed that showed to have an effect on growth promotion/increased yield were reported. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for lincomycin.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 9: Polymyxins: colistin.

The specific concentrations of colistin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of colistin in feed that showed to have an effect on growth promotion/increased yield were reported. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 13: Diaminopyrimidines: trimethoprim.

The specific concentrations of trimethoprim in non-target feed for food-producing animals below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for trimethoprim was estimated. Uncertainties and data gaps associated to the levels reported were addressed. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. No suitable data for the assessment were available. It was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC for trimethoprim.

K-Domain Technology: Constitutive Expression of a Blueberry Keratin-Like Domain Mimics Expression of Multiple MADS-Box Genes in Enhancing Maize Grain Yield.

MADS-box genes are considered as the foundation of all agronomic traits because they play essential roles in almost every aspect of plant reproductive development. Keratin-like (K) domain is a conserved protein domain of tens of MIKC-type MADS-box genes in plants. K-domain technology constitutively expresses a K-domain to mimic expression of the K-domains of other MADS-box genes simultaneously and thus to generate new opportunities for yield enhancement, because the increased K-domains can likely prevent MADS-domain proteins from binding to target DNA. In this study, we evaluated utilizing the K-domain technology to increase maize yield. The K-domain of a blueberry's SUPPRESSOR of CONSTITUTIVE EXPRESSION OF CONSTANS 1 (VcSOC1K) has similarities to five MADS-box genes in maize. Transgenic maize plants expressing the VcSOC1K showed 13-100% of more grain per plant than the nontransgenic plants in all five experiments conducted under different experimental conditions. Transcriptome comparisons revealed 982 differentially expressed genes (DEGs) in the leaves from 83-day old plants, supporting that the K-domain technology were powerful and multiple functional. The results demonstrated that constitutive expression of the VcSOC1K was very effective to enhance maize grain production. With the potential of mimicking the K-domains of multiple MADS-box genes, the K-domain technology opens a new approach to increase crop yield.

Ex-ante impact assessment of GM maize adoption in El Salvador.

Bacillus thuringiensis (Bt) white maize was field tested in El Salvador in 2009. Results showed sufficient pest abatement, eliminating the need for insecticide applications, and an average yield increase of 18% above that of the most widely cultivated conventional hybrid. This article presents an ex ante economic impact assessment of Bt maize adoption in El Salvador. Ten-year economic surplus projections show a considerable welfare gain for the overall economy, with consumers being the principal beneficiaries. Trade implications of adopting Bt maize are analyzed and appropriate alternatives to possible market shutdowns are explored. Results obtained in this study could compliment the agronomic evaluation of Bt maize and become part of the Salvadoran government decision process on Bt maize adoption.

[Characteristics of soil nitrogen cycle and mechanisms underlying the increase in rice yield with partial substitution of mineral fertilizers with organic manure in a paddy ecosystem: A review]. / 稻作系统有机肥替代部分化肥的土壤氮循环特征及增产机制.

Partial substitution of mineral fertilizers with organic manure is a key strategy for stable and increase crop yield accompanying with zero growth of mineral fertilizers. Based on recent stu-dies, we reviewed the effects of partial substitution of mineral fertilizers with organic manure on rice yield, nitrogen utilization efficiency, soil nitrogen fractions, and microbial nitrogen fixation, ammonification, nitrification, and denitrification in rice paddy ecosystems. We further compared the cha-racteristics of soil nitrogen cycle of mineral fertilizers alone and partial substitution of mineral fertili-zers with organic manure. The partial substitution altered key processes of nitrogen cycling, including enhancement of ammonification, mediation of nitrification and denitrification, reduction of ammonia volatilization and nitrogen loss, improved the status of nitrogen supplements (enriching the supplement of low-molecular-weight organic nitrogen, adjusting the distribution of inorganic nitrogen components, increasing the amount of microbial biomass nitrogen, and decreasing the loss of total nitrogen), improved soil nitrogen supply (increasing supply of small molecule organic nitrogen, coordinating inorganic nitrogen components and proportions, and increasing soil microbial biomass nitrogen and total nitrogen fixation), which promoted nitrogen uptake and regulated nitrogen allocation in rice plant to realize stability and enhancement of rice yield.

Virus epidemics, plant-controlled population bottlenecks and the durability of plant resistance.

Plant qualitative resistances to viruses are natural exhaustible resources that can be impaired by the emergence of resistance-breaking (RB) virus variants. Mathematical modelling can help determine optimal strategies for resistance durability by a rational deployment of resistance in agroecosystems. Here, we propose an innovative approach, built up from our previous empirical studies, based on plant cultivars combining qualitative resistance with quantitative resistance narrowing population bottlenecks exerted on viruses during host-to-host transmission and/or within-host infection. Narrow bottlenecks are expected to slow down virus adaptation to plant qualitative resistance. To study the effect of bottleneck size on yield, we developed a stochastic epidemic model with mixtures of susceptible and resistant plants, relying on continuous-time Markov chain processes. Overall, narrow bottlenecks are beneficial when the fitness cost of RB virus variants in susceptible plants is intermediate. In such cases, they could provide up to 95 additional percentage points of yield compared with deploying a qualitative resistance alone. As we have shown in previous works that virus population bottlenecks are at least partly heritable plant traits, our results suggest that breeding and deploying plant varieties exposing virus populations to narrowed bottlenecks will increase yield and delay the emergence of RB variants. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

A novel enzymatic approach to nanocrystalline cellulose preparation.

In this work, conditions for an enzymatic pretreatment prior to NCC isolation from cotton linter were assessed. Different cellulase doses and reaction times were studied within an experimental design and NCC were obtained. At optimal enzymatic conditions (20U, 2 h), a total yield greater than 80% was achieved and the necessary enzymatic treatment time was reduced 90%. Different intensities of enzymatic treatments led to proportional decreases in fiber length and viscosity and also were inversely proportional to the amount of released oligosaccharides. These differences within fibers lead to quantitative differences in NCC: increase in acid hydrolysis yield, reduction of NCC surface charge and crystallinity increase. Benefits produced by enzymatic treatments did not have influence over other NCC characteristics such as their sulfur content (≈1%), size (≈200 nm), zeta potential (≈-50 mV) or degree of polymerization (≈200). Evidence presented in this work would reduce the use of harsh sulfuric acid generating a cleaner stream of profitable oligosaccharides.