Important Agricultural Products Research Articles

CPD-CCNN: classification of pepper disease using a concatenation of convolutional neural network models

Agricultural products are vital to the sustainability of the economies of developing countries. Most developing countries’ economies such as Ethiopia heavily rely on agriculture. On a global scale, the pepper crop is one of the most important agricultural products in terms of human food security. However, it is susceptible to a variety of diseases which include blight leaf disease, gray leaf spot, common rust, fruit rot disease, powdery mildew symptoms on pepper leaf, and other related diseases that are all common today. Currently, more than 34 different pepper diseases have been discovered, resulting in a 33% average yield loss in pepper cultivation. Conventionally, farmers detect the disease using visual observation but this has its own demerits as it is usually not accurate and usually time consuming. In the past, a number of researchers have presented various methods for classifying pepper plant disease, especially using image processing and deep learning techniques. However, earlier studies have shown that binary classification requires improvement as some classes were more challenging to identify than others. In this study, we propose a concatenated neural network of the extracted features of VGG16 and AlexNet networks to develop a pepper disease classification model using fully connected layers. The development of the proposed concatenated CNN model includes steps such as dataset collection, image preprocessing, noise removal, segmentation, feature extraction, and classification. Finally, the proposed concatenated CNN model was evaluated, providing a training classification accuracy of 100%, validation accuracy of 97.29%, and testing accuracy of 95.82%. In general, it can be concluded from the findings of the study that the proposed concatenated model is suitable for identifying pepper leaf and fruit diseases from digital images of pepper.

Synthesis and insecticide evaluation of some new oxopropylthiourea compounds as insect growth regulators against the cotton leafworm, Spodoptera littoralis

In this project we aim to share in increasing the production of the most important non-food agricultural product i.e. cotton via protection of it is plant. The usage of safe alternatives to the pesticides has become crucial due to several serious issues associated with the use of insecticides. Therefore, the families of new eco-friendly organic compounds that contain manly oxopropylthiourea scaffold will synthesis in their pure state by using green procedures. This compounds includes (i) poly functional substituted oxopropylthiourea, (ii) dihydroquinoline carboxylic acid, In second category, the structure of this compounds which may be related to the most famous insect growth regulators insecticides, will confirmed by elemental and modern spectroscopic analyses (such as IR, UV, 1HNMR and 13CNMR). In the final category, the synthesized compounds was checked toward the second & forth instar larvae of cotton leafworm, Spodoptera littoralis. The present data proved that values of LC50 of the most effected synthesized compound 8 was 2.412 ppm in which LC50 for commercial lufenuron was 2.295 ppm. Component 8 may be particularly effective due to the presence of fluorophenyl, cyanoacetamide, and carboxalic acid groups in their chemical makeup. In an additional effort to slightly improve insecticidal compounds, evaluation of the latent effects of the examined components on a number of biological parameters, such as adult longevity, pupal weight, proportion of normal, deformed pupae, & adult emergency, fecundity, & egg hatchability, was carried out.

SOIL CONDITIONS AND EFFECT OF FERTILIZATION ON THE EMISSION OF GREENHOUSE GASES IN AN ANDEAN COFFEE GRADIENT

Coffee (Coffea arabica and C. canephora) is an important agricultural export product in Ecuador, but yields reported at most coffee farms are low. The main reasons for this are a lack of understanding of soil nutritional status and fertilization management, which implies fertilizer misuse and results in gas emissions into the environment. In this study, the soil nutritional status of coffee plantations was evaluated along an altitudinal gradient of the Ecuadorian Andes as an indicator of soil fertilization plans. A total of 471 farmlands were selected and their pH, soil organic matter, and main macronutrients were determined. The impact of soil fertilization on nitrous oxide emissions was evaluated; for this purpose, an experimental coffee farm was chosen where different doses of mineral and organic soil fertilization were tested, and N2O emissions were determined. The results showed a negative correlation between soil organic matter, pH, and nitrate concentration with altitude. In all altitudinal strata, the nitrate concentration was higher than that of ammonium. In addition, a strong correlation was observed between soil organic matter and soil nitrate concentration. The amount of potassium decreased as altitude increased, whereas medium and high concentrations of available phosphorus were observed in all altitudinal ranges. However, significant statistical differences were found when comparing low mineral fertilization doses to organic fertilization. The N2O analyses showed that coffee plantations fertilized with mineral fertilizers emit from 300 to 1142 mg N2O m-2 into the environment. High mineral fertilization resulted in the highest N2O emissions, with statistically significant differences when compared to low mineral doses and organic fertilization. Therefore, it was concluded that changes in soil nutritional status were observed along the Andean gradient of coffee plantations in southern Ecuador, and that high doses of mineral fertilizer can have a significant impact on N2O emissions.

Seed Testing to Improve Cultivation Using Android Application

Abstract: Corn is one of the most important agricultural products produced in India. Customers can get it in a variety of provinces and cities. Before just being distributed to consumers, corn kernels must undergo quality assurance. Most farmers in the nation use manual human inspection as the only method of classifying and evaluating maize kernels, and these methods are inconsistent, leading to inconclusive results. When dealing with a lot of kernels that need to be certified, this is more common. Through the use of a neural network method of inspection, this study proposes to reduce the inconsistencies. Because the physical characteristics of damaged maize kernels may be used to detect the damage, the neural network can rapidly determine the type of damage in a given sample. The following categories of damage, in addition to the healthy kernels, were examined in this study: drier damage, heat damage, OCOL (Other Color) Type A, and OCOL Type B. The neural network that will be employed is a convolutional neural network, which layers of processing on the images of the samples. In this research, colored image edge detection is also used.

KLASIFIKASI MUTU BERAS MENGGUNAKAN K-NN BERBASIS BACKWARD ELIMINATION

CLASSIFICATION RICE QUALITY USING K-NN BACKWARD-BASED ELIMINATIONRice is one of the most important agricultural products. And it is a strategic commodity because almost all Indonesian people need it. Because of the importance of the function of rice as a staple food ingredient, the quality of the rice to be consumed must be ensured to be of high quality. Determination of the quality or quality of rice until now has been done by many previous researchers. However, of the several methods that have been selected, the majority use image processing. Rice quality data processing using data mining is still rarely done. In this study, the dataset that will be used comes from the Probolinggo Regency Agriculture Service database which has 1 special attribute and 9 regular attributes. The attributes are: variety, length, shape, color, taste, rice planting technique, season, pests, PH and quality. The method that will be used in this study is the backward elimination-based K-NN method.From the results of the analysis and computation of several methods, it can be concluded that the backward elimination-based K-NN method used to increase the accuracy of rice classification resulted in several conclusions. Namely the attributes that affect the determination of rice quality are variety, shape, color, technique, season, pests and PH. While the features that are considered to have no effect are taste and length. As for the data as much as 4952, the best accuracy is 83.08% when k = 1, while for the data as much as 2000, then the best accuracy is 87.70% at k = 1, while for the data as much as 1000, the best accuracy is 98.60%, namely when k=1.

Spatiotemporal Characteristics of Drought in Northwest China Based on SPEI Analysis

Drought has a direct impact on regional agricultural production, ecological environment, and economic development. The northwest region of China is an important agricultural production area, but it is also one of the most serious areas of water shortage due to drought and little rain. It is of great significance to make full use of agricultural resources to clarify the temporal and spatial distribution characteristics of the drought regime in Northwest China. Based on the Standardized Precipitation Evapotranspiration Index (SPEI), this paper used the methods of Mann–Kendall non-parameter trend, mutation test, and Morlet wavelet analysis to explore the drought characteristics in Northwest China from 1961 to 2017. The results showed that the spatial distribution of SPEI on annual and seasonal scales differed slightly in different regions, but from northwest to southeast, the distribution was generally wetter to drier. The drought intensity (Sij) had a step-like distribution with a range of 1.14–1.98. Based on Sij analysis, the frequency of drought in Northwest China was moderate, followed by extreme drought, severe drought, and light drought. The inter-annual drought station proportion (Pj) ranged from 7.4% to 84.1%. A total of 25, 18, 7, and 5 years of pan-regional drought, regional drought, partial region drought, and local drought occurred, respectively, based on Pj analysis. Moreover, from the whole study period, the regional drought changes tended to cause humidification to different degrees. The results of Morlet wavelet analysis showed that there were multiple time scales of 33–52, 11–19, and 4–7 years of SPEI in the entire time domain, and dry and wet trends occurred. The results of the present research can provide a reference for the efficient utilization of water resources, drought monitoring and early warning, drought prevention, and drought relief in Northwest China.

Bioconversion of olive oil pomace by black soldier fly increases eco-efficiency in solid waste stream reduction producing tailored value-added insect meals.

Olive oil is one of the most important agricultural products in Mediterranean areas, and currently the European Union is the largest producer. Due to technological innovations, Portugal has become one of the main olive oil producing countries over the last few years, accompanied by large amounts of olive oil pomace (OOP), the most representative residue of the olive oil extraction process. This is causing serious waste management problems since current management solutions also present environmental impacts. Here we explored the black soldier fly (Hermetia illucens) potential to biotransform OOP into valuable insect meals by feeding them OOP-based diets as substrates. Results show that despite survival rates not being affected by higher replacement (75% and 50%) levels of OOP, there was an increase in larval instar duration. Substrate reduction was significantly lower for higher replacement levels but was not affected up to the 50% replacement level. Feed conversion rate differed among all the treatments, increasing as the replacement level increased, while bioconversion rate, which also differed among all the treatments, decreased as replacement level increased. Differences in larval protein content were only seen at higher replacement levels (75%), with an increase in protein content for replacements of up to 25%. One of the most striking results was the change in fatty acid profile, which became more abundant in monounsaturated fatty acids (mostly oleic acid) as the olive pomace replacement levels increased in comparison with the control substrate, rich in saturated fatty acids (palmitic acid). These results show that BSF can be an effective OOP bioconversion agent, and resulting insect meals can be used as alternatives to currently available saturated fatty acid insect meals.

Agent-based model development of a complex socio-ecological system: Methods for overcoming data and domain limitations

Agent-based models (ABMs) are appropriate tools for modelling socio-ecological systems due to their ability to handle complexity. However, development of such models is often an intensive process. There are many tutorials on the general methods and steps in ABM development but there are not necessarily practical details on how to overcome certain challenges. Honeybush (Cyclopia spp.), a kind of fynbos vegetation found in the Western and Eastern Cape mountains, is an important ecological and agricultural product in South Africa. It is considered a complex system due to its variability and unpredictability. The honeybush tea industry faces the challenge of meeting emerging market demands while maintaining sustainable harvesting practices, in the midst of an uncertain future due to climate change. We created a prototype model, HoneybushModel, using the MARS framework, a C# multi-agent simulation toolkit. The model was validated using historic data. Whilst outlining the development processes used to create the HoneybushModel, this paper provides a methodology for the development of such models and demonstrates techniques for addressing data, domain and framework limitations. The implemented model also acts as a case study for similar systems that could be modelled using an ABM.

A novel two-stage multi-objective optimization model for sustainable soybean supply chain design under uncertainty

Soybean is one of the most important agricultural products in international markets due to its high global consumption. However, there are limited studies considering sustainability issues and global economic aspects of the soybean supply chain design and optimization. Moreover, it is challenging to integrate many sustainability criteria into a single-stage optimization model for a soybean supply chain configuration. This research proposes a novel two-stage approach, integrating a multi-criteria decision-making technique and a new multi-objective optimization model to design and optimize a soybean supply chain network in Canada, considering sustainability and global factors. In Stage 1, several qualitative and quantitative sustainability criteria are considered to calculate the sustainability scores for the potential suppliers, using the Interval Type 2 Trapezoidal Best Worst Method. Then, the scores are used as input in Stage 2, where a new optimization model with four objective functions is formulated to design and optimize a soybean supply chain. The objective functions include maximization of total profit, created job opportunities, and suppliers' sustainability, and minimization of CO2 emissions. Then, the Pareto frontier is generated, using the augmented ε-constraint method which helps policymakers to make appropriate decisions. Furthermore, four cases are proposed and analyzed to assess the impacts of the objective functions on strategic and tactical decisions. The results show the importance of the presented method as an integrated approach, considering sustainability pillars in agri-food supply chains. In addition, the results indicate that the proposed stochastic multi-objective model can handle fluctuations in uncertain parameters.

Identification of adulterated honey with different varieties and concentrations based on hyperspectral imaging technology combined with deep learning

Honey is an important agricultural and sideline product in China, which contains the high nutritional value and commercial value. An advanced honey adulteration identification model can help beekeepers and consumers better identify honey and avoid losses. Given the complex operation and high technical requirements of traditional honey identification experimental instruments, a new model for quickly and efficiently identifying honey adulteration with different kinds and concentrations was developed in this study. Based on the data of adulterated honey with different varieties and concentrations obtained by hyperspectral imaging technology, a large number of regions of interest were randomly selected as samples. Then, the classification model is established by adopting preprocessing methods such as standardization, centralization, multivariate scattering correction, standard variable transformation, first-order difference, and second-order difference, combining the advantages of convolutional neural network and support vector machine. Finally, the accuracy of the results is compared, and D1-CNN-SVM is determined as the best classification prediction model, with an accuracy rate of 100%. At the same time, through the analysis of the confusion matrix of experimental results, this study summarizes the difficulties in identifying adulterated honey of different varieties and concentrations.

Valorization of Baker Yeast Industry Waste in Agriculture by Improving Germination and Growth of Barley and Pea.

Industrial waste still present an environmental danger for the nature and survival of all living beings. Among these toxic products, the focus has been on liquid effluents from the baker's yeast industry that cause real environmental problems mainly due to their pollutant load and the release of unpleasant odors. In order to minimize these hazards and to take advantage of these wastes for the sake of our environment, the present work consists on valorizing effluents from the baker's yeast industry on barley (Hordeum vulgare) and pea (Pisum sativum), two important agricultural products of Tunisian north-west. Results showed that this waste is characterized by its richness in organic matter, and the presence of proteins traces with high chemical and biochemical oxygen demand (COD and BOD5) values. Diluted effluent at a dose of 2.5mg/g significantly improves germination of both plant seeds by germination index (GI) calculation, to reach a maximum of 190 ± 17% and 150 ± 14% for barley and pea, respectively. In fertigation experiment, the use of a lower dose of .62mg/g of diluted effluent promotes plant length to reach 52 ± 4cm and 45 ± 1.4cm, respectively, for H. vulgare and P. sativum. Gas chromatography coupled to mass spectrometry (GC-MS) analysis after derivatization showed significant enhancement of auxin production in pea treated with .62mg/g of cream compared to control with a concentration of 10.60 ± .81 and 8.16 ± .43ng/gFW, respectively. In another experiment, the irrigation of pea plants with furfural, as major compound of cream, promotes length and auxin production to reach 9.89 ± .56ng/gFW for a furfural dose of .31mg/g. This leads us to valorize baker's yeast effluent as an environment-friendly natural product in pea and barley agricultural and give insight to its mode of action.

Agrochemical Input Behavior and Cleaner Production Adoption Willingness of Farmers in Beijing–Tianjin–Hebei, China

Beijing–Tianjin–Hebei is an important agricultural production area in China, and farmers’ agrochemical input behavior directly affects the risk of agricultural non-point source pollution and the effect of green agricultural development. Based on a questionnaire survey and field interview data, this study investigated the agrochemical input behavior of farmers in Beijing–Tianjin–Hebei, and analyzed its influencing factors. Using the Probit model, we carried out an empirical study on farmers’ willingness to invest in cleaner production of agrochemicals from four aspects: farmers’ characteristics, agricultural input, environmental awareness and technical cognition. The results showed that the kinds of fertilizer were mainly compound fertilizer, urea and organic fertilizer, and the fertilization method was mainly surface spreading, accounting for 50.6% of the total surveys; the number of agrochemicals was determined chiefly by agricultural sellers, accounting for 55.5%. The proportion of the guidance from technical departments in Beijing was higher than that of Tianjin and Hebei. The first influencing factor for farmers’ behavior towards agrochemical input was the pursuit of high yield and high profit, accounting for 24.9%, 22.6% and 26.0%, respectively. The guidance of relevant technical departments still did not fully cover the use of agrochemicals. The study also found that factors such as the price of farming materials, the price of agricultural products, family income, farmland facilities, government propaganda, technical training and subsidies all impacted the agrochemical input behavior. Pre-production technical guidance and farmers’ awareness significantly affected the willingness to adopt cleaner production. Technical training was helpful to improve farmers’ willingness to participate actively, and enhancing the pertinence of training played an important role in the adoption of cleaner production technology. In conclusion, the influencing factors of farmers’ agrochemical input in Beijing, Tianjin and Hebei were complex, and the scientific application level still needs to be improved. This paper finally discusses and puts forward some countermeasures and suggestions for agrochemical reduction and efficiency improvement.

Sustainable model of agricultural product logistics integration based on intelligent blockchain technology

Agricultural product logistics plays a high role in the development of Chinese economy, which is the most important basic link in the process of agricultural industrialization, scale and modernization. The logistics of agricultural products in China has always been at a low standard of development, slow development or even stagnation. As the most basic and important agricultural product industry in the national economy, the degree and mode of development of agricultural products have a great impact on the development of Chinese economy and people’s quality of living. Therefore, new models and approaches for the construction and development of agricultural product logistics must be actively explored to promote the standardization and scale of China’s agricultural product logistics industry. Therefore, the paper constructed a sustainable model of agricultural products logistics integration based on blockchain technology, and proposed a comprehensive logistics model of agricultural products based on intelligent blockchain, which was expected to provide some help to solve the problems of supply and demand mismatch, quality safety management, agricultural product price fluctuation and other problems in the current agricultural product circulation. The paper first introduced the intelligent blockchain technology and the concept of agricultural product logistics integration, and then constructed a sustainable model of agricultural product logistics integration. The paper gave a general description of the model and conduct comparative experiments on its effectiveness. The paper found that the agricultural product logistics industry based on intelligent blockchain technology could achieved at least 40% of the additional revenue. After verification, the limitations of intelligent blockchain technology were also proposed and corresponding suggestions are given. At the end of this paper, the paper proposed that blockchain technology can realize the information visualization and traceability of the whole life cycle of products, which can effectively solve some new problems in the agricultural supply side structural reform and had broad application prospects.

Türkiye’ de ve dünyada soğan üretiminin durumu, abiyotik ve biyotik stres faktörlerinin etkileri

Onion plant is an indispensable additive for meals in the world and in our country. It is an important strategic agricultural product containing phytochemicals effective in the treatment of various diseases, as a medicinal and aromatic plant, as well as for consumption as food for humans. In the light of the statistical information examined, it is seen that there are changes in the supply of the onion plant to the market from year to year. The reasons for this seem to be annual land planning, input prices and human factors effective during production, as well as the damage rates of abiotic and biotic factors. In this study, the status of onion cultivation in Türkiye and in the world and the effects of abiotic and biotic factors encountered in cultivation are explained. In order to prevent fluctuations in supply to and prices in the market, it should be at the forefront of annual product planning, and producers should focus on raising awareness and training activities for growing healthy onions with high tolerance to diseases and pests.

Field, plant, to leaf: A meta-analysis on crop water use efficiency response to potassium fertilization

Applying potassium (K) fertilizer to fields is considered to be an important agricultural production practice to improve crop water use efficiency (WUE). However, the magnitude of crop WUE response to K fertilization has only been reported for individual regions, crops and scales due to lack of extensive and complete global datasets. Here we quantified the responses of crop WUE to K fertilization at the three scales of field-population (WUEfield), whole-plant (WUEplant) and single-leaf (WUEleaf) through synthesizing 797 paired observations from 81 field-based studies worldwide. Meta-analysis results showed that K fertilization increased WUEfield, WUEplant and WUEleaf of crops by 19.0%, 12.0% and 29.9%, respectively, with the key factors influencing this being crop type, mean annual precipitation and soil pH, respectively. It should be noted that the magnitude of WUEfield, WUEplant and WUEleaf response to K fertilization was significantly positively correlated with mean annual precipitation, while significantly negatively correlated with soil pH, which implying that K fertilization is an effective way to improve crop WUE in the region with humid climate or acidic soil. Furthermore, the conclusive findings of this meta-analysis showed that the relative importance of environmental factors in the magnitude of the WUEfield, WUEplant and WUEleaf response to K fertilization was 49.8%, 68.8% and 82.0%, respectively, which indicated that climatic characteristics and soil properties were drivers of crop WUE response to K fertilization rather than management practices. Overall, our meta-analysis provides new insight into the crop WUE response to K fertilization from field, plant, to leaf was driven by environmental factors and highlights the great potential of improved field K fertilization strategies in developing sustainable agriculture under the condition of climate change.

The effect of chitosan coating combined with cold plasma on the quality and safety of pistachio during storage.

Pistachios are one of the most important agricultural and export products of Iran. Fresh pistachio fruit has soft skin, is highly perishable, and therefore has a short life after harvesting, which has made traders and consumers have a great desire to increase the shelf life of this product. For this purpose, in this study, the effect of different concentrations of chitosan as an edible coating (0.5 and 1.5% w/v) and the duration of cold plasma treatment (60 and 120 s) were investigated during 180 days of pistachio storage. The effect of treatments on the shelf life of pistachio fruit was evaluated by determining moisture content, color components, peroxide value, total mold and yeast, hardness, aflatoxin content, and sensory evaluations. The results showed that the treatment with 1.5% chitosan coating and 120 s of cold plasma treatment preserved the hardness of the pistachio and the color indices in the best way (p < .05). Also, this treatment had the minimum number of peroxide, aflatoxin, and mold and yeast counts during the storage time. The treatments with chitosan coating and under plasma application did not cause any unpleasant odor or taste during the storage time. In conclusion, according to the results of this research, it was determined that the simultaneous use of chitosan coating and cold plasma treatment can potentially be used as a new approach for commercial applications and the export of fresh pistachios.

Storing Grain in the Land: The Gestation, Delineation Framework, and Case of the Two Zones Policy in China

Cultivated land (CL) protection is an overarching strategic concern for stabilizing the agricultural foundation and for achieving the sustainable development of the national economy and society. Faced with the challenges of the dual drives of complex domestic and international situations, China’s CL protection system has coupled the quantity and quality dimensions and focused on a dynamic balancing system and permanent basic farmland (PBF) policy. However, it has had difficulty meeting the objectives of sustainable agricultural development and is undergoing upgrades. Accordingly, the Chinese government has issued a CL protection policy that includes adjusting the planting structure, optimizing the agricultural layout, and adding the three dimensions of quantity, quality, and planting structure, namely “Delimitation of the Grain Production Functional Zone and the Important Agricultural Product Production-Protection Zone” (the “two zones” policy). With regard to the ambiguous understanding of the two zones policy, this study aims to explore the following issues: (1) How was the two zones policy conceived? (2) What mechanism does it use to make up for the deficiencies of the previous policy? (3) How does it integrate the three dimensions of quantity, quality, and planting structure? (4) How to reasonably delimit the two zones. To solve these problems, this paper first reviews the evolution of China’s CL protection policies and explains the incubation process of the two zones policy and its connotation and mechanism. Then, a delineation framework process is proposed and the approaches of executing the two zones policy on a regional scale are discussed. Furthermore, a real delimitation was conducted in Qianguo County to validate the framework. The evidence shows that customizing CL use according to regional resource potential differentiation and forming a CL protection policy with the three dimensions of quantity, quality, and structure are effective in improving the productive potential of CL and promoting the adjustment of the planting structure. Furthermore, the framework and case study findings of the delimitation provide a theoretical reference and practical foundation to translate macro policy into micro management.

Role of arbuscular mycorrhizal fungi in cadmium tolerance in rice (Oryza sativa L): a meta-analysis

Rice is an important agricultural product consumed globally. Rice polluted by cadmium (Cd) poses serious health risks. Numerous studies have shown that arbuscular mycorrhizal fungi (AMF) decrease Cd concentrations in the grain, shoots, and roots of rice. However, one study showed that AMF increased the root Cd concentration in rice. Therefore, a meta-analysis of the contribution of AMF to rice Cd tolerance became necessary. This meta-analysis was conducted to analyze the role of AMF in Cd tolerance in rice by searching the following databases: ProQuest, PubMed, Scopus, and ScienceDirect. A total of 571 studies were found, of which nine studies and 25 datasets were used in the meta-analysis. The period of inclusion of research reports was from January 1992 to April 2022. The results showed that with the addition of Rhizophagus irregularis, Cd concentration in the roots was higher than in the control group, although the overall Cd concentration in the plant was reduced. Four species of AMF reduced Cd concentration in rice shoots and grain tissues. These AMF species increased the biomass of rice root and shoot tissues; however, they did not affect grain biomass. AMF decreased the transfer factor (TF), and the TF of Glomus versiforme (12.99%) was significantly lower than the other three AMF types. We proposed that Cd could be enriched in rice roots, and the transfer of Cd to the grain could be inhibited. At the time of grain harvesting, rice roots are removed from the soil, thus removing Cd from the soil. This operation can efficiently improve both land-bearing capacity and soil without affecting rice yield. Thus, Cd was enriched in rice roots, and the poten-tial for Cd transfer to the grain was inhibited due to the decreased TF. The future research must focus on how R. irregularis could improve the HMA3 gene expression in rice root, and prevents the transportation of Cd from the roots to shoots.

Gene enrichment and co-expression analysis shed light on transcriptional responses to Ralstonia solanacearum in tomato

BackgroundTomato (Solanum lycopersicum) is both an important agricultural product and an excellent model system for studying plant-pathogen interactions. It is susceptible to bacterial wilt caused by Ralstonia solanacearum (Rs), and infection can result in severe yield and quality losses. To investigate which genes are involved in the resistance response to this pathogen, we sequenced the transcriptomes of both resistant and susceptible tomato inbred lines before and after Rs inoculation.ResultsIn total, 75.02 Gb of high-quality reads were generated from 12 RNA-seq libraries. A total of 1,312 differentially expressed genes (DEGs) were identified, including 693 up-regulated and 621 down-regulated genes. Additionally, 836 unique DEGs were obtained when comparing two tomato lines, including 27 co-expression hub genes. A total of 1,290 DEGs were functionally annotated using eight databases, most of which were found to be involved in biological pathways such as DNA and chromatin activity, plant-pathogen interaction, plant hormone signal transduction, secondary metabolite biosynthesis, and defense response. Among the core-enriched genes in 12 key pathways related to resistance, 36 genotype-specific DEGs were identified. RT-qPCR integrated analysis revealed that multiple DEGs may play a significant role in tomato response to Rs. In particular, Solyc01g073985.1 (NLR disease resistance protein) and Solyc04g058170.1 (calcium-binding protein) in plant-pathogen interaction are likely to be involved in the resistance.ConclusionWe analyzed the transcriptomes of both resistant and susceptible tomato lines during control and inoculated conditions and identified several key genotype-specific hub genes involved in a variety of different biological processes. These findings lay a foundation for better understanding the molecular basis by which resistant tomato lines respond to Rs.

Identification of HIR, EDS1 and PAD4 Genes Reveals Differences between Coffea Species That May Impact Disease Resistance

Coffee, a widely consumed important agricultural product, is mainly produced from two species, Coffea arabica (Arabica coffee) and C. canephora (Robusta coffee). Timor Hybrid (HDT) is a population resulting from a natural cross between C. arabica and C. canephora. HDT derivatives have a high spectrum of resistance to different races of Hemileia vastatrix (Hv), the causal agent of coffee leaf rust. A RNAseq database, obtained from HDT832/2 leaves inoculated with Hv (Host Resistance) and Uromyces vignae (Uv, Nonhost Resistance), showed the presence of genes implicated in the hypersensitive response and salicylic acid pathway. Hypersensitive Induced Reaction (HIR) gene family, Enhanced Disease Susceptibility1 gene (EDS1), and Phytoalexin Deficient 4 (PAD4) gene are involved in host and nonhost resistance. Relative expression calculated by RT-qPCR was used to confirm and expand the transcriptome analysis. HDTHIR4, HDTEDS1, and HDTPAD4 showed the highest upregulation in response to Hv and Uv inoculation, confirming a similar trend in host and nonhost resistance in HDT. HIR and EDS1/PAD4 gene families were characterized for the first time in the three available Coffea genomes. HIR genes were quite conserved between Coffea species. Surprisingly, EDS1 and PAD4 genes revealed major differences in gene structure. The PAD4 predicted protein from C. arabica does not include both conserved domains of the EDS1/PAD4 family, and the EDS1 putative protein from C. canephora includes a formin domain unusual in the same protein family. The variability shown by EDS1/PAD4 gene family may impact the disease resistance response of Coffea species, which can be surveyed for the gene sequences that will produce a more resistant phenotype.