Mutation breeding is a promising technique used for improving crop plants' performance, including tolerance to aluminum in rice (Oryza sativa L.) cultivars. The presented research pursued developing aluminum-tolerant rice lines through mutation in two local rice cultivars, 'Mayas' and 'Adan'. Mutation induction using six doses of gamma irradiation included 50, 100, 150, 200, 250, and 300 Gy. The evaluation of root tolerance index proceeded for early selection of aluminum tolerant lines. In addition, root swelling, aluminum absorption, cross-sectional histology, and root lipid peroxidation incurred scrutiny. The results showed gamma irradiation (100 Gy) could produce aluminum stress tolerant lines from the cultivar Mayas. Aluminum-tolerant lines obtained totaled 91 through gamma irradiation in the local rice genotypes. The morphological traits of these aluminum-tolerant mutant lines underwent accumulation only at the root tip, cross-sectional histology with sclerenchyma thickening due to organic acids, and minimal cell wall damage. These lines need further evaluation to confirm their tolerance to aluminum stress, for rice cultivation on acid soils.

Heavy metal pollution is one of the most devastating abiotic factors, significantly damaging crops and human health. One of the serious problems it causes is a rise in cadmium (Cd) toxicity. Cd is a highly toxic metal with a negative biological role, and it enters plants via the soil-plant system. Cd stress induces a series of disorders in plants' morphological, physiological, and biochemical processes and initiates the inhibition of seed germination, ultimately resulting in reduced growth. Fiber crops such as kenaf, jute, hemp, cotton, and flax have high industrial importance and often face the issue of Cd toxicity. Various techniques have been introduced to counter the rising threats of Cd toxicity, including reducing Cd content in the soil, mitigating the effects of Cd stress, and genetic improvements in plant tolerance against this stress. For decades, plant breeders have been trying to develop Cd-tolerant fiber crops through the identification and transformation of novel genes. Still, the complex mechanism of Cd tolerance has hindered the progress of genetic breeding. These crops are ideal candidates for the phytoremediation of heavy metals in contaminated soils. Hence, increased Cd uptake, accumulation, and translocation in below-ground parts (roots) and above-ground parts (shoots, leaves, and stems) can help clean agricultural lands for safe use for food crops. Earlier studies indicated that reducing Cd uptake, detoxification, reducing the effects of Cd stress, and developing plant tolerance to these stresses through the identification of novel genes are fruitful approaches. This review aims to highlight the role of some conventional and molecular techniques in reducing the threats of Cd stress in some key fiber crops. Molecular techniques mainly involve QTL mapping and GWAS. However, more focus has been given to the use of transcriptome and TFs analysis to explore the potential genomic regions involved in Cd tolerance in these crops. This review will serve as a source of valuable genetic information on key fiber crops, allowing for further in-depth analyses of Cd tolerance to identify the critical genes for molecular breeding, like genetic engineering and CRISPR/Cas9.

In potato breeding, maturity class (MC) is a crucial selection criterion because this is a critical aspect of commercial potato production. Currently, the classification of potato genotypes into MCs is done visually, which is time- and labor-consuming. The objective of this research was to use vegetation indices (VIs) derived from unmanned aerial vehicle (UAV) imagery to remotely assign MCs to potato plants grown in trials, representing three different early stages within a multi-year breeding program. The relationships between VIs (GOSAVI - Green Optimized Soil Adjusted Vegetation Index, MCARI2 - Modified Chlorophyll Absorption Index-Improved, NDRE - Normalized Difference Red Edge, NDVI - Normalized Difference Vegetation Index, and OSAVI - Optimized Soil Adjusted Vegetation Index and WDVI - Weighted Difference Vegetation Index) and visual potato canopy status were determined. Further, this study aimed to identify factors that could improve the accuracy (decrease Mean Absolute Error - MAE) of potato MC estimation remotely. Results show that VIs derived from UAV imagery can be effectively used to remotely assign MCs to potato breeding lines, with higher accuracy for the potato B-clones (20 plants per plot) than the A-clones (6 plants per plot). Among the tested VIs, the NDRE allowed for potato MC evaluation with the lowest MAE. Applying NDRE for remote MC estimation using a validation dataset of potato B-clones (100 plants per plot), resulted in an MC estimate with a 0.81 MAE. However, the accuracy of potato MC estimation using UAV image-based methods should be improved by reducing the potato canopy's variability (increasing uniformity) within the plot. This could be achieved by minimizing 1) potato vines bending over the neighboring row, causing vine overlap between plots, and 2) plants damaged by tractor wheels during field operations. En el mejoramiento de la papa, la clase de madurez (CM) es un criterio de selecci & oacute;n crucial porque este es un aspecto cr & iacute;tico de la producci & oacute;n comercial de papa. Actualmente, la clasificaci & oacute;n de los genotipos de papa en MC se realiza visualmente, lo que requiere mucho tiempo y trabajo. El objetivo de esta investigaci & oacute;n fue utilizar & iacute;ndices de vegetaci & oacute;n (VIs) derivados de im & aacute;genes de veh & iacute;culos a & eacute;reos no tripulados (UAV) para asignar de forma remota MCs a plantas de papa cultivadas en ensayos, representando tres etapas tempranas diferentes dentro de un programa de mejoramiento de varios a & ntilde;os. Se determinaron las relaciones entre los VIs (GOSAVI - & Iacute;ndice de Vegetaci & oacute;n Ajustado al Suelo Optimizado Verde, MCARI2 - & Iacute;ndice de Absorci & oacute;n de Clorofila Modificado-Mejorado, NDRE - Borde Rojo de Diferencia Normalizada, NDVI - & Iacute;ndice de Vegetaci & oacute;n de Diferencia Normalizada, y OSAVI - & Iacute;ndice de Vegetaci & oacute;n Ajustado al Suelo Optimizado y WDVI - & Iacute;ndice de Vegetaci & oacute;n de Diferencia Ponderada) y la visualizaci & oacute;n del dosel de la papa. Adem & aacute;s, este estudio tuvo como objetivo identificar factores que podr & iacute;an mejorar la precisi & oacute;n (disminuir el Error Absoluto Medio - MAE) de la estimaci & oacute;n de MC de papa de forma remota. Los resultados muestran que los VI derivados de las im & aacute;genes de UAV se pueden utilizar de manera efectiva para asignar MC de forma remota a las l & iacute;neas de mejoramiento de papa, con mayor precisi & oacute;n para los clones B de papa (20 plantas por parcela) que para los clones A (6 plantas por parcela). Entre los VI probados, el NDRE permiti & oacute; la evaluaci & oacute;n de la MC de papa con el MAE m & aacute;s bajo. La aplicaci & oacute;n de NDRE para la estimaci & oacute;n remota de MC utilizando un conjunto de datos de validaci & oacute;n de clones B de papa (100 plantas por parcela), result & oacute; en una estimaci & oacute;n de MC con un MAE de 0.81. Sin embargo, la precisi & oacute;n de la estimaci & oacute;n de la MC de la papa utilizando m & eacute;todos basados en im & aacute;genes UAV debe mejorarse reduciendo la variabilidad del dosel de la papa (aumentando la uniformidad) dentro de la parcela. Esto podr & iacute;a lograrse minimizando 1) los tallos de papa que se doblan sobre el surco vecino, lo que causa la superposici & oacute;n de follaje entre las parcelas, y 2) las plantas da & ntilde;adas por las ruedas de los tractores durante las operaciones de campo.

Cadmium (Cd) has become an important heavy metal pollutant because of its strong migration and high toxicity. The industrial production process aggravated the Cd pollution in rice fields. Human exposure to Cd through rice can cause kidney damage, emphysema, and various cardiovascular and metabolic diseases, posing a grave threat to health. As modern technology develops, the Cd accumulation model in rice and in-situ remediation of Cd pollution in cornfields have been extensively studied and applied, so it is necessary to sort out and summarize them systematically. Therefore, this paper reviewed the primary in-situ methods for addressing heavy metal contamination in rice paddies, including chemical remediation (inorganic-organic fertilizer remediation, nanomaterials, and composite remediation), biological remediation (phytoremediation and microbial remediation), and crop management remediation technologies. The factors that affect Cd transformation in soil and Cd migration in crops, the advantages and disadvantages of remediation techniques, remediation mechanisms, and the long-term stability of remediation were discussed. The shortcomings and future research directions of in situ remediation strategies for heavily polluted paddy fields and genetic improvement strategies for low-cadmium rice varieties were critically proposed. To sum up, this review aims to enhance understanding and serve as a reference for the appropriate selection and advancement of remediation technologies for rice fields contaminated with heavy metals.

Introduction Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms. Methods We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables. Results Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

Microplastics (MPs), found in many places around the world, are thought to be more detrimental than other forms of plastics. At present, physical, chemical, and biological methods are being used to break down MPs. Compared with physical and chemical methods, biodegradation methods have been extensively studied by scholars because of their advantages of greenness and sustainability. There have been numerous reports in recent years summarizing the microorganisms capable of degrading MPs. However, there is a noticeable absence of a systematic summary on the technology for breeding strains that can degrade MPs. This paper summarizes the strain-breeding technology of MP-degrading strains for the first time in a systematic way, which provides a new idea for the breeding of efficient MP-degrading strains. Meanwhile, potential techniques for breeding bacteria that can degrade MPs are proposed, providing a new direction for selecting and breeding MP-degrading bacteria in the future. In addition, this paper reviews the sources and pollution status of soil MPs, discusses the current challenges related to the biodegradation of MPs, and emphasizes the safety of MP biodegradation.

The environmental invasion of plastic waste leads to, among other things, a reassessment of natural fibers. Environmental pollution has shown the importance of the degradability, among other properties, of the raw materials used by the textile industry or other industrial fields. Wool seems to be a better raw material than the polymers that generate large quantities of micro- and nano-plastics, polluting the soil, water, and air. However, the usual processing of raw wool involves a number of chemically very polluting treatments. Thus, sustainable procedures for making wool processing environmentally friendly have been considered, leading to the reappraisal of wool as a suitable raw material. Besides their applications for textile products (including smart textiles), new directions for the valorization of this natural material have been developed. According to the recent literature, wool may be successfully used as a thermal and phonic insulator, fertilizer, or component for industrial devices, or in medical applications, etc. In addition, the wool protein alpha-keratin may be extracted and used for new biomaterials with many practical applications in various fields. This review makes a survey of the recent data in the literature concerning wool production, processing, and applications, emphasizing the environmental aspects and pointing to solutions generating sustainable development.

Bacterial wilt (BW) is a soil-borne disease that leads to severe damage in tomato. Host resistance against BW is considered polygenic and effective in controlling this destructive disease. In this study, genomic selection (GS), which is a promising breeding strategy to improve quantitative traits, was investigated for BW resistance. Two tomato collections, TGC1 (n = 162) and TGC2 (n = 191), were used as training populations. Disease severity was assessed using three seedling assays in each population, and the best linear unbiased prediction (BLUP) values were obtained. The 31,142 SNP data were generated using the 51K Axiom array (TM) in the training populations. With these data, six GS models were trained to predict genomic estimated breeding values (GEBVs) in three populations (TGC1, TGC2, and combined). The parametric models Bayesian LASSO and RR-BLUP resulted in higher levels of prediction accuracy compared with all the non-parametric models (RKHS, SVM, and random forest) in two training populations. To identify low-density markers, two subsets of 1,557 SNPs were filtered based on marker effects (Bayesian LASSO) and variable importance values (random forest) in the combined population. An additional subset was generated using 1,357 SNPs from a genome-wide association study. These subsets showed prediction accuracies of 0.699 to 0.756 in Bayesian LASSO and 0.670 to 0.682 in random forest, which were higher relative to the 31,142 SNPs (0.625 and 0.614). Moreover, high prediction accuracies (0.743 and 0.702) were found with a common set of 135 SNPs derived from the three subsets. The resulting low-density SNPs will be useful to develop a cost-effective GS strategy for BW resistance in tomato breeding programs.

Introduction: Soil salinity poses a severe threat to rice production, resulting in stunted growth, leaf damage, and substantial yield losses. This study focuses on developing an early maturing seedling stage salinity tolerant rice variety by integrating conventional breeding methods with marker assisted breeding (MAB) approaches.Methods: Seedling-stage salinity tolerance Quantitative Trait Locus (QTL) Saltol from the salt-tolerant parent FL478 was introduced into the high-yielding but salt-sensitive rice variety ADT 45. This was achieved through a combination of conventional breeding and MAB. The breeding process involved rigorous selection, screening, and physiological parameter assessments.Results: KKL(R) 3 (KR 15066) identified as the top performing Recombinant Inbred Line (RIL), consistently demonstrating maximum mean grain yields under both salinity (3435.6 kg/ha) and normal (6421.8 kg/ha) conditions. In comparison to the early maturing, salt-tolerant national check variety CSR 10, KKL(R) 3 exhibited a substantial yield increase over 50%.Discussion: The notable improvement observed in KKL(R) 3 positions it as a promising variety for release, offering a reliable solution to maximize yields, ensure food security, and promote agricultural sustainability in both saline and non-saline environments. The study highlights the effectiveness of MAB in developing salt-tolerant rice varieties and emphasizes the significance of the Saltol QTL in enhancing seedling stage salinity tolerance. The potential release of KKL(R) 3 has the capacity to revolutionize rice production in salt affected regions, providing farmers with a reliable solution to maximize yields and contribute to food security while ensuring agricultural sustainability.