Agriculture Communications最新文献

Antimicrobial peptides (AMPs) show promise in enhancing resistance against pathogens. Previously, we integrated two AMP genes, cathelicidin (Cath) from alligator (Alligator mississippiensis or Alligator sinensis) and cecropin (Cec) from moth (Hyalophora cecropia), into the channel catfish (Ictalurus punctatus) genome. This study examines the efficacy of exogenous AMP gene integration in improving bacterial resistance in transgenic channel catfish and assesses the direct and pleiotropic effects of gene replacement/knockout on survival and growth based on insertion site. Transgenic Cath- and Cec-expressing fish exhibited similar or higher survival rates (P ​> ​0.05) compared to controls during the initial culture. Integration of the Cec transgene doubled the survival rate when challenged with Edwardsiella ictaluri, with knock-in (KI) of Cath further increasing bacterial resistance. Coupling Cec KI with mstn knockout (KO) increased survival 3-fold after E. ictaluri infection and growth by 50% at 4 months post-fertilization (mpf). However, random integration of Cec had a minimal effect on disease resistance and did not enhance growth. Random integration of Cath increased survival 2.5-fold and 4-fold against E. ictaluri and Flavobacterium covae, respectively, without affecting growth. Cath KI at the lh locus increased survival 4-fold when challenged with F. covae and reduced growth by 10% (P ​> ​0.05) at 24 mpf, whereas Cath KI coupled with mc4r KO resulted in a 2.5-fold increase in survival following F. covae infection compared with controls, and increased growth by 80% at 3 mpf. Simultaneous KI of Cath and Cec, along with KO of mc4r and mstn, increased survival 4-fold against E. ictaluri, while increasing growth by 50% at 3 mpf. Dual insertion of AMP genes yielded the greatest resistance to disease. These direct and pleiotropic effects may increase comprehension and societal acceptance of genetic engineering in aquaculture.

Glucosinolates (GSLs) are a prototypical group of bioactive compounds found in the Brassicaceae family that promote human health and plant defense. The GSL-myrosinase system can be induced to release multiple bioactive products when plants are subjected to mechanical damage, environmental stress, or pathogen infection. While many GSLs promote human health, some cause deleterious effects when ingested. To engineer Brassicaceae crops with lower levels of harmful GSLs without sacrificing health-promoting GSLs requires a complete understanding of the origin and advances in GSL modification. Extensive early domestication studies were conducted using classic breeding and plant nutrition. More recently, genetic modification of specific groups of GSLs or levels of GSLs in specific tissues has been partially successful. However, efforts have fallen short of delivering a reduction in potentially harmful GSLs without concomitant losses to health-promoting effects and plant defense. The latest work has been to synthetically express GSL biosynthesis pathways in non-host crops or microbial species. However, yields have been far from economically sustainable. This review discusses key advances made in GSL modification that are promising for the precise modification of GSL content and composition for optimal plant defense and human health.

A pangenome encompasses the complete genetic diversity of a species, by assembling a range of representative individuals from various populations. This review describes the advances in plant pangenomics, tracing its evolution since the initial plant genome sequencing in 2000, and provides comprehensive best-practice advice to build a linear or graphical pangenome, delineating the strengths and limitations of different pangenome construction methods. The review also examines the challenges in pangenome data visualisation, the challenges of graph-based pangenomes and their utility in investigating the potential function of genome variation. Furthermore, we examine the application of pangenomes in plant breeding, including the identification of genetic diversity for crop improvement, and the integration of multi-omics data into pangenome databases to advance plant breeding.

Accurately distinguishing the origin and variety of rice types is of paramount importance to conducting research on this staple crop. While various methods are currently employed for this purpose, few approaches can verify the identity of single grains rapidly and accurately. In this study, we present a method that integrates machine learning with infrared (IR) microspectroscopy for swift detection of the origin and variety of a single rice grain. To establish the validity of our approach, we assembled a diverse collection of rice samples, comprising 14 distinct types with different origins or varieties. Each rice sample yielded 100 microspectroscopy spectra, resulting in 1400 spectra. We applied two deep learning algorithms, deep neural network (DNN) and convolutional neural network (CNN), for spectral analysis. The 1400 spectra were randomly partitioned into calibration and validation sets at a ratio of 3:1. These datasets were subjected to both DNN and CNN analysis for classification of samples by origin and variety. Following 10,000 iterations, we selected optimal DNN and CNN models. The predication accuracies of the optimal DNN model for calibration and validation sets were 95.4% and 90.0%, respectively. In comparison, the optimal CNN model demonstrated superior accuracy, with 99.8% for the calibration set and 92.0% for the validation set. Based on these results, we selected the CNN model as the final model for field use in rice grain classification.

Understanding crop domestication provides a basis for ongoing genetic improvement of crops, especially in the utilization of wild crop relatives as a source of new variation and may guide the domestication of new crops. The Asia Pacific region is home to most of the world's human population and is a region in which many important crops were domesticated. Here we review the domestication of banana, citrus, coconut, macadamia, mango, millet, mungbean, rice, sugarcane and taro in the Asia Pacific region. These examples illustrate the importance of this region in the development of agriculture. The challenges of conservation of the genetic resources for these crops are exacerbated by the large human population and rapid economic development in the region. Advances in genetic technologies provide an opportunity for accelerated genetic improvement of these crops and the domestication of new crops.

Nitrogen is one of the most important nutrients for plants. However, the availability of nitrogen sources in the soil is often a limiting factor for growth. Some plants, such as legumes, can establish a nitrogen fixing nodule symbiosis with certain bacteria. This allows them to use nitrogen from the air to make ammonium that can be used for their growth. Since the discovery of the nitrogen fixing process at the end of the 19th century, there has been contemplation regarding the possibility of transferring the property of nitrogen fixing root nodule formation to crops that do not have this ability. Currently, our knowledge concerning its evolution and molecular mechanism that control nodulation has markedly increased. In this review, we summarized recent advances in these areas and discussed possibilities to engineer nodulation in crops.

The Food and Agriculture Organization (FAO) has indicated that digital technology is key for improving the resilience of food systems. Smart models have been developed for agricultural water, fertilizer, medicine, and environmental regulations, in which data-driven quantity and precision are crucial. However, data acquisition methods based on manual observation cannot meet the requirements of large amount of real-time data. The development of machine vision provides a new method for online non-destructive monitoring. We discuss algorithm types and evaluation methods for machine vision applications based on RGB images considering their low cost and easy access. This paper reviews progress in the application field, covering the entire process from planting to postharvest, and the application of sensing and control equipment in agricultural practice. Finally, aiming at the problems such as lack of agricultural data set, poor model portability, and large model size, a new algorithm framework based on “data layer - model layer - deployment layer,” multi-parameter “environmental data - image data” and multi-method fusion of “mechanism model - machine vision” was proposed to provide a basis for low-cost nondestructive online crop monitoring.

In an effort to develop novel, less toxic, and effective controls for plant diseases, we aimed to identify derivatives of the natural product isomagnolone with antimicrobial activity. We established a facile method for the synthesis of isomagnolone and its isomer Ⅱ, and prepared a series of novel isomagnolone analogues bearing N-(1,3-thiazol-2-yl)amides Ⅲ1–30. The structures of Ⅲ1–30 were determined by IR, ¹H NMR, ¹³C NMR, and ESI-MS. Among them, compounds Ⅲ24 and Ⅲ26 exhibited potent antifungal activity against four fungi with EC₅₀ values substantially lower than that of the positive control, hymexazol. Additionally, the antibacterial results showed that Ⅲ20 and Ⅲ22 displayed more potent antibacterial activity against Xanthomonas oryzae pv. oryzae (Xoo) with EC₅₀ values of 12.6 and 10.3 ​μg/mL, respectively, approximately 2-fold lower than that of the positive control, thiodiazole copper (EC₅₀: 24.0 ​μg/mL). Structure-activity relationships suggested that the antifungal activity of title isomagnolone analogues was favored when the substituent (R) was pyridyl or the 2-chloro-3-pyridyl group. Mechanism of action studies revealed that Ⅲ22 could disrupt bacterial membranes, thus resulting in cell death. Furthermore, the potent compounds Ⅲ20, Ⅲ22, Ⅲ24, and Ⅲ26 showed low toxicity against the human hepatocyte cell line (LO2). Given these results, these isomagnolone analogues bearing N-(1,3-thiazol-2-yl)amides are promising antimicrobials against phytopathogenic fungi and bacteria for controlling plant diseases.

To address the challenge of disposing vegetable waste in greenhouses while mitigating white pollution associated with the use of conventional polyethylene film, we compared polyethylene (PE) film with two types of fully biodegradable film in both straw-return and no-straw-return treatments. We systematically investigated the effects of mulching on soil properties, film degradation, and tomato quality and yield. The results showed that the humic acid biodegradable film with straw-return (FZS-SR) increased the contents of lycopene, vitamin C (Vc), and soluble sugars in tomato fruit by 20.77%, 16.68%, and 25.89%, respectively, and decreased the total acid content by 8.46% compared to polyethylene film with no-straw-return (PE-NR). Additionally, FZS-SR enhanced the relative abundance of soil bacteria and fungi in Chloroflexi and Basidiomycota, while reducing the relative abundance of pathogenic fungal groups. Moreover, the biodegradable film degraded 15 days earlier in the straw-return treatment, with significantly higher characteristic peaks in Fourier transform infrared spectral analysis compared to no straw-return treatment. In a greenhouse, the straw-return model accelerated the degradation rate of biodegradable film. In summary, our results indicate that using humic acid biodegradable film with straw-return is an effective and sustainable cultivation method, improving tomato quality and yield. This approach offers insights for addressing residual plant and film pollution in vegetable production.

The pervasive use of antibiotics in agriculture and animal husbandry has raised a significant concern—residual antibiotic contamination in food, which contributes to the natural evolution of antibiotic resistance in pathogenic microbial strains. The emergence of antibiotic resistance in microbial communities poses a global threat to food safety and security. Recently, the situation has been exacerbated by the discovery of novel strains of antibiotic resistant bacteria (ARB) in plant- and animal-derived foods. These microbes can enter the human body through direct contact with affected animals or through consumption of contaminated foods. In this review, we explore the prevalence of antibiotic contaminants in food at various locations around the world, delve into the molecular mechanisms behind acquisition of antimicrobial resistance, examine the current strategies employed to mitigate the evolution and spread of antibiotic resistant pathogens, and discuss emerging technologies aimed at halting the trend that projects 10 million annual deaths by 2050 as a result of ARB contamination in agriculture. Genetic processes, including mutations, efflux pump activity, and horizontal gene transfer, play crucial roles in the evolution and widespread distribution of ARB in the microbial community. Effectively addressing this global threat requires development of methodologies to rapidly detect ARB in the food supply chain. Therefore, we examine several established rapid diagnostic techniques such as the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) methodology, aptasensors, and fluorescence-based Metal Organic Frameworks. Additionally, we explore innovative strategies to fight ARB such as nano-antibiotics, natural antibiotics, synthetic biology, bacteriophages, and predator bacteria. Here, we propose emerging technologies such as omics technologies and biochar use as potential tools for combating ARB. We anticipate that this review article will serve as a valuable resource for future research, particularly in the development of strategies designed not only to suppress the activities of antibiotic resistance genes but also to potentially reverse resistance mechanisms that are already widespread in microbial communities.