Kiziltepe Şemistan, Karakurt Emin, Eser Gizem
et al.
Ovine pulmonary adenocarcinoma (OPA) is an infectious and neoplastic disease etiologically linked to the Jaagsiekte sheep retrovirus (JSRV), characterised by tumour lesions of the lung. Because of the economic losses it induces, OPA is of great importance for flock health. In this study, oxidative stress markers and adenosine deaminase (ADA) activity were quantified in lung tissue from sheep, both healthy and those naturally afflicted with OPA. Compared to healthy sheep, malondialdehyde (MDA), nitric oxide (NO ), ceruloplasmin (CP) and ADA concentrations/activities were significantly increased (P<0.05 and P<0.001) in fresh lung tissues from JSRV–infected sheep, while reduced glutathione (GSH) levels were significantly decreased (P<0.05). In conclusion, pronounced oxidative stress and increased ADA enzyme activity were detected in the JSRV–infected sheep. These findings suggest that ADA activity could serve as a biomarker for disease diagnosis.
Adoption of improved agricultural technologies remains to be a promising strategy to achieve food security and poverty reduction in many developing countries. However, there are limited rigorous impact evaluations on the contributions of such technologies on household welfare. This paper investigates the impact of improved agricultural technology use on farm household income in eastern Ethiopia. Primary data for the study was obtained from a random sample of 248 rural households, 119 of which are improved technology users and the rest are non-users. The research employed the Propensity Score Matching (PSM) procedure to establish the causal relationship between adoption of improved crop and livestock technologies and changes in farm income. Results from the econometric analysis show that households using improved agricultural technologies had, on average, 23,031.28 Birr (Birr is the official currency of Ethiopia. The exchange rate according to the National Bank of Ethiopia (NBE) was 1 USD = 27.6017 Birr on 04 October 2018.) higher annual farm income compared to those households not using such technologies. Our findings highlight the importance of promoting multiple and complementary agricultural technologies among rural smallholders. We suggest that rural technology generation, dissemination and adoption interventions be strengthened. Moreover, the linkage among research, extension, universities and farmers needs to be enhanced through facilitating a multistakeholders innovation platforms.
Abstract The frequent outbreaks of agricultural pests have resulted in the reduction of crop production and seriously restricted agricultural production. And many kinds of agricultural pests bring challenges to the accurate identification of agricultural pests for agricultural workers. Currently, the traditional methods of agricultural pest detection cannot satisfy the needs of agricultural production because of low efficiency and accuracy. In this paper, we put forward an anchor-free region convolutional neural network (AF-RCNN) for precision recognition and classification of 24-classes pests. First, a feature fusion module is designed to extract effective feature information of agricultural pests, especially small pests. Then, we propose an anchor-free region proposal network (AFRPN) that is used for getting high-quality object proposals as possible pest positions based on the fusion feature maps. Finally, our anchor-free region convolutional neural network (AF-RCNN) is employed to detect 24-classes pest via an end-to-end way by merging our AFRPN with Fast R-CNN into a single network. We evaluate the performance of our method on the pest dataset including 20k images and 24 classes. Experimental results demonstrate that our method is able to obtain 56.4% mAP and 85.1% mRecall on 24-classes pest dataset, 7.5% and 15.3% higher than Faster R-CNN, and 39.4% and 56.5% higher than YOLO detector. The running time could achieve 0.07 s per image, meeting the real-time detection. The proposed method is effective and applicable for accurate and real-time intelligent pest detection.
Aiming to address a series of problems caused by inefficient nitrogen fixation in soybean within the maize–soybean rotation system under cold-region conditions in Heilongjiang Province, China—such as reduced crop yields, declining soil fertility, and increased dependence on chemical fertilisers—this study investigated the partial substitution of chemical nitrogen fertilisers with bio-organic fertilisers at replacement rates of 10%, 20%, and 30% during soybean cultivation. The treatments included bio-organic fertilisers (OB1, OB2, OB3), inactivated bio-organic fertilisers (O1, O2, O3), <i>Bacillus subtilis</i> (B1, B2, B3), and a control (CK) with the conventional application of chemical fertilisers. In the rotational maize cropping phase, a 50% nitrogen reduction was applied. The results showed that replacing 20% of soybean nitrogen fertiliser with bio-organic fertiliser (OB2 treatment) yielded the most significant increase in productivity and economic return. Compared with CK, the OB2 treatment increased soybean yield by 26.56%, maize yield by 26.69%, and nitrogen fertiliser use efficiency by 3–5%. According to the GRA-TOPSIS model, the OB2 treatment demonstrated the greatest capacity to improve quality and efficiency in the maize–soybean rotation system. At the soybean maturity stage, the OB2 treatment increased soil total organic carbon, available phosphorus, and soil protease activity by 25.36%, 22.20%, and 87.50%, respectively, compared with CK. At maize maturity, soil ammonium nitrogen and soil protease activity increased by 80.24% and 62.47%, respectively. Bio-organic fertilisers combine the benefits of organic fertiliser substrates with those of functional microorganisms. Correlation, cluster, and interaction analyses revealed that the synergistic mechanisms between maize–soybean rotation and bio-organic fertilisers in cold regions are primarily reflected in improved soil quality, enhanced nutrient cycling efficiency, increased nitrogen fixation in soybean root nodules, stimulated microbial activity, and greater resilience to environmental stress. Sustainable agricultural production in cold regions can be achieved through the integrated functioning of these system components. This study provides a theoretical basis for enhancing yield and efficiency in maize–soybean rotation systems under cold climatic conditions.
Transcriptomics and 4D label-free quantitative phosphoproteomics technologies were used to study the molecular basis of fruiting body development in Pleurotus ostreatus at both the transcriptional and post-translational levels. During the transition from the mycelium to the primordium stage, a greater number of differentially expressed genes (DEGs) were down-regulated, and phosphorylation levels decreased in most differentially phosphorylated proteins (DPPs). During the transition from primordium to fruiting body stage, was characterized by a predominance of up-regulated DEGs and enhanced phosphorylation levels in a larger proportion of DPPs. During the transition from primordium to fruiting body stage, a greater number of DEGs were up-regulated, and phosphorylation levels were enhanced in the DPPs. KEGG pathway enrichment analysis of key DPPs revealed that the mitogen-activated protein kinase (MAPK) signaling pathway, ribosome, spliceosome, and RNA transport were critical pathways influencing fruiting body development. Functional validation of the key gene PoMPK1 in the MAPK signaling pathway was performed using Agrobacterium tumefaciens-mediated genetic transformation. The results demonstrated that interference with the PoMPK1 gene promoted fruiting body development, indicating that PoMPK1 negatively regulates fruiting body development in P. ostreatus. This work provides a theoretical reference for the molecular mechanism of fruiting body development in P. ostreatus.
Abstract The advent of agricultural robotics research worldwide has brought substantial improvement for various applications. This article provides a comprehensive review of published research and development work, emphasizing robotics enabling machine capabilities. These machine capabilities of perception, reasoning and learning, communication, task planning and execution, and systems integration have opened possibilities for intelligent automation of current and future agricultural operations, including precision livestock farming. We have focused on the Agricultural Intelligent Automation Systems which have a high potential to be applied to agricultural production and processing, especially with applicability to poultry production. Most of the published work on agricultural robotics has been in the areas of perception and reasoning. The emphases have been in the identification of objects, evaluation of product quality, monitoring of plant and animal growth and development, yield prediction, and machine guidance. There has been limited published work on the task execution and systems integration aspects of agricultural robotics. Moreover, we have reviewed agricultural robotics research from 24 universities worldwide. Agricultural robots can be divided into three categories (monitor, harvester, and both) according to various functions. Several tables are presented to summarize the information on the key subject areas reviewed in this article. We have found that there are still many challenges that need to be addressed in robotizing agricultural tasks in general and in poultry production specifically. The most common challenges in robotics applications have been developing robots for specific agricultural tasks. Examples in poultry production include monitoring environmental conditions and chicken health, egg picking, and encouraging chicken movement. The approaches to addressing the technical needs have been creating intelligent movable machines for use alongside the chickens in poultry house. The most noticeable results include Octopus Poultry Safe (OPS) robot for sanitizing poultry houses autonomously, PoultryBot for picking floor eggs, and Spoutnic for training hens to move. This trend of research and development is expected to continue. An emerging research emphasis is systems approach to study the interactions of automated tasks to achieve high efficiency in whole poultry house management.
Chemical fertilizers, pesticides, and fungicides are widely used in agriculture to improve crop yields. Most of the compounds used are synthetic, and their overuse causes environmental pollution and human health problems. Currently, several countries are working to reduce the use of agrochemicals. Organic agriculture is now emerging as a sustainable alternative to traditional agriculture using environmentally friendly strategies such as the application of organic fertilizers from plant and animal waste and pesticides based on plant extracts and microbials. However, the availability of commercial biopesticides and organic fertilizers is very limited because there are certain barriers to the commercialization of biological products. These barriers include small available quantities of raw materials and strict registration laws requiring toxicological tests and other studies that are expensive and time consuming. The objective of this review is to provide details about the various organic fertilizers and pesticides that do not have the same disadvantages as synthetic compounds in terms of persistence and toxicity.
This paper estimates the role of agronomic inputs in cereal yield improvements and the consequences for countries' processes of structural change. The results suggest a clear role for fertilizer, modern seeds and water in boosting yields. We then test for respective empirical links between agricultural yields and economic growth, labor share in agriculture and non-agricultural value added per worker. The identification strategy includes a novel instrumental variable that exploits the unique economic geography of fertilizer production and transport costs to countries' agricultural heartlands. We estimate that a half ton increase in staple yields generates a 14 to 19 percent higher GDP per capita and a 4.6 to 5.6 percentage point lower labor share in agriculture five years later. The results suggest a strong role for agricultural productivity as a driver of structural change.
Agricultural insurance and green agriculture are strongly related. Agricultural insurance not only motivates farmers to adopt environmentally friendly production technology and enhances the effectiveness of production, but it also accomplishes the goal of lowering the number of chemicals that are put into the environment. This article investigates the dynamic relationship between agricultural insurance, air pollution, and agricultural green total factor productivity. To complete the aim, the authors used the panel auto-regressive distributed lags method (PMG method) and panel data from 50 states of the United States between 2005 and 2019. The empirical findings demonstrate a considerable co-integration and a cross-sectional reliance between agricultural insurance, air pollution, and agricultural green total factor production. Expanding agricultural insurance may boost agricultural green whole factor output but also exacerbate air pollution. However, significant air pollution does not increase agricultural production’s green total factor productivity. The panel Granger causality test shows a one-way causal relationship between agricultural insurance, green total factor productivity, and air pollution. A one-way causal relationship exists between air pollution and agricultural green total factor productivity. The author concluded that improving agricultural insurance coverage or cutting down on air pollution will boost agricultural green total factor output. These findings have long-term policy and management repercussions, particularly for those involved in agriculture policy and environmental management.
Sorena Vahedipour-Dahraie, Younes Zahedi, Mir Daryoush Shakouri
SUMMARY: Because of the side effects of growth stimulant antibiotics employed for poultry nutrition the poultry industry attempts to substitute them with a safer one like as phytogenic or organic acids. Thus, the objective of this study was to determine the influence of single and double supplementation of broiler chickens diet with eugenol (0, 500, and 1,000 ppm) and butyric acid glycerides (BAG) (0 and 0.2% w/w) on the chemical, technological and sensory traits of the chicken breast during 60 d of storage. The biological trial was carried out on a total of 300 mixed-sex one-day-old Ross 308 chicks, which were randomly distributed into 6 dietary treatments, with 5 replicates and 10 birds each. The results revealed that L* and b* color values of the fillet samples changed significantly (p < 0.05). The pH values reduced significantly from 5.79 to 5.69 as an effect of eugenol supplementation in the diet (p < 0.05). Water binding ability of the fillet samples evaluated by drip loss, cooking loss and water holding capacity assays was not influenced by addition of BAG and eugenol to the diet of broilers. Sensorial traits of the meat samples were not negatively affected by the dietary supplementation process. Thiobarbituric acid reactive substances (TBARS) and total volatile basic nitrogen (TVBN) values of the fillets were not influenced meaningfully by treatments. Overall, dietary supplementation of broiler chickens by eugenol and BAG did not result in important modifications of the physicochemical characteristics of chicken's breast.
Governments in developing countries have been increasingly involved in the support of commercial agricultural (crop and livestock) insurance programs in recent years. A striking example is China, where, with support (and premium subsidies) from the central and provincial governments, the agricultural insurance market grew dramatically to become the second largest market in the world (after the United States) in 2008. In India and Mexico, weather-based crop insurance has been developed on a large scale to protect farmers against the vagaries of the weather. Many other countries have investigated the feasibility of agricultural insurance, and some have implemented pilot programs. This book aims to inform and update public and private decision makers involved in promoting agricultural insurance about recent developments in agriculture insurance. The literature is heavily biased toward the practice and experience of a few very large public-private programs in Northern America and Europe, which are driven by large public financial subsidies. This book provides decision makers with a framework for developing agricultural insurance. It is based on an analytical review of the rationale for public intervention in agricultural insurance and a detailed comparative analysis of crop and livestock insurance programs provided with and without government support in more than 65 developed and developing countries. The comparative analysis is based on a survey conducted by the World Bank's agricultural insurance team in 2008. Drawing on the survey results, the book identifies some key roles governments can play to support the development of sustainable, affordable, and cost-effective agricultural insurance programs.
Abstract Blockchain technology is a disruptive technology that changes business and supply chain models. Using distributed software architecture and advanced computing, blockchain can change the way information is exchanged between actors in the chain. Blockchain technology provides a platform for solving the problem of tracking product information in supply chain management. Accordingly, the present study aims to provide a model for evaluating the maturity of blockchain technology in the agricultural supply chain. The present research is applied that has been done in three stages. In the first phase, the dimensions of the blockchain are ranked by agricultural experts using the SWARA method. The research experts are 13 faculty members of the department of agriculture active in the field of technology application. In the second phase, a model is designed to evaluate blockchain maturity using each dimension of blockchain technology and maturity dimensions. In the third phase, the proposed model is tested using data collected by a questionnaire in the supply chain of a company active in the agriculture sector. The research findings show that smart contracts, Internet of Things (IoT), and transaction records are of the highest importance among the blockchain dimensions. Also, the supply chain under study is in a good condition in digital documents. Theoretically, the originality aspect of the research is that it determines the importance of blockchain dimensions in the field of agriculture and from an applied point of view, it introduces the maturity model of blockchain in supply chain management.