The Role of Agribusiness Firms in Agricultural Research: The Case of China

Despite the efforts of various economists and agricultural scientists in calling for more investments, funding for agricultural R&D has been stagnated for the last two decades in China. This will pose a great challenge for the China's agricultural sector. Productivity has leveled off, and farmers' income has been flat. As a result, poverty reduction in recent years has also not shown any significant progress. On the other hand, agribusiness firms have emerged rapidly since the rural reforms initiated in 1978. Emerging of these firms has fundamentally changed the landscape of Chinese agricultural production. In 2003, they account for a significant share in agricultural GDP (7%), and agricultural employment. More importantly, it is their role in agricultural research and technology adoption that will drastically affect the Chinese agricultural research system, and as a result the structure of the Chinese agricultural economy. In 2003, these firms invested more than 10% equivalence of public spending in agricultural research. If their spending on technology-intensive capital is included, the percentage rose to 30%. Back in the middle of the 1990s, these shares are minimal. It is obvious that these firms will play an even larger role in investing in agricultural research in China. But this increase didn't come automatically. It is the change in the investment environment and government policies that can be attributed to. The objective of the proposed paper is to investigate the structure of these agribusiness firms by sector, location and ownership, and their performance in agricultural research, and to analyze the determinants of growth of these firms and their investment in agricultural research. The data used for the proposed study will be based on a survey conducted by the Ministry of Science and Technology in 2003. The authors provided substantial inputs in the design of questionnaire. More than 500 leading firms (based on their sales) were surveyed. They are located in different parts of China: coastal, central and western. They also represent different sectors, for example, crop production, livestock, feed processing and supply, vegetables/fruits/tree, tea, fishery, seed development/sales and biotechnology/medicine. There firms also vary by their ownership, for example state-, private-, and collective-owned, shareholding, and multinational companies. The proposed study will develop a conceptual framework and to empirically analyze how different factors have affected the performance of these firms. The performance indicators may include profitability, productivity, and more importantly their behavior in investing agricultural R&D. The factors may include their size, ownership (state, private, shareholding, or foreign), location (coastal, central or western), different types of businesses (crop production, livestock, fishery, processing, feed supply, seed breeding and supply, or biotechnology), credit/capital constraint, intellectual property rights regime, tax concession policy, and public investment in agricultural R&D. Many variables are province-specific as many government policies such as those on credit/capital, tax are made at this level of government. These variables will have to be treated carefully as they are potentially endogenous by themselves. Special econometric techniques will be used to minimize the potential bias. In addition, some firm-specific variables such as sectors they involve, ownership, and even locations are self-selected. Again, certain econometric techniques have to be used to test and to minimize the potential selection bias. The expected results will not only have potential contribution to the policy debate on how to mobilize private resources to support to agricultural research in China, but also have strong policy implications for many other developing countries. For the last decade, many developing countries have experienced stagnation or contraction in their public support to agricultural research. How government policies and public investment in agricultural research can build a productive partnership is a very much needed research topic. We hope that our research will shed light on this issue.Research and Development/Tech Change/Emerging Technologies,

National and international agricultural research and rural poverty: the case of rice research in India and China

The study attempts to measure the total benefits from rice varietal improvement research in China and India using variety adoption and performance data over the last two decades. It then uses genetic or pedigree information to partition the total benefits between these two countries and IRRI. Finally, the study uses reported elasticity of poverty reduction with respect to agricultural output growth to assess the effects of national and international research on poverty reduction in rural India and China. The results indicate that rice varietal improvement research has contributed tremendously to increase in rice production, accounting for 14-23 percent of total production value over the last two decades in both countries. Rice research has also helped reduce large numbers of rural poor. IRRI played a crucial role in these successes. In 1999, for every $1 million invested at IRRI, more than 800 and 15,000 rural poor were lifted above the poverty line in China and India, respectively. These poverty-reduction effects were even larger in the earlier years." Authors' AbstractRice Asia., Rice Research., Rice Varieties., Rice Yields., Poverty alleviation., genetically modified organisms,

Rhizosphere phage communities drive soil suppressiveness to bacterial wilt disease

Publisher Copyright: © 2023, The Author(s).Background: Bacterial viruses, phages, play a key role in nutrient turnover and lysis of bacteria in terrestrial ecosystems. While phages are abundant in soils, their effects on plant pathogens and rhizosphere bacterial communities are poorly understood. Here, we used metagenomics and direct experiments to causally test if differences in rhizosphere phage communities could explain variation in soil suppressiveness and bacterial wilt plant disease outcomes by plant-pathogenic Ralstonia solanacearum bacterium. Specifically, we tested two hypotheses: (1) that healthy plants are associated with stronger top-down pathogen control by R. solanacearum-specific phages (i.e. ‘primary phages’) and (2) that ‘secondary phages’ that target pathogen-inhibiting bacteria play a stronger role in diseased plant rhizosphere microbiomes by indirectly ‘helping’ the pathogen. Results: Using a repeated sampling of tomato rhizosphere soil in the field, we show that healthy plants are associated with distinct phage communities that contain relatively higher abundances of R. solanacearum-specific phages that exert strong top-down pathogen density control. Moreover, ‘secondary phages’ that targeted pathogen-inhibiting bacteria were more abundant in the diseased plant microbiomes. The roles of R. solanacearum-specific and ‘secondary phages’ were directly validated in separate greenhouse experiments where we causally show that phages can reduce soil suppressiveness, both directly and indirectly, via top-down control of pathogen densities and by alleviating interference competition between pathogen-inhibiting bacteria and the pathogen. Conclusions: Together, our findings demonstrate that soil suppressiveness, which is most often attributed to bacteria, could be driven by rhizosphere phage communities that regulate R. solanacearum densities and strength of interference competition with pathogen-suppressing bacteria. Rhizosphere phage communities are hence likely to be important in determining bacterial wilt disease outcomes and soil suppressiveness in agricultural fields. [MediaObject not available: see fulltext.].Peer reviewe

A comparative analysis of growth and nutritional quality of the hybrid grouper (Epinephelus fuscoguttatus ♀ × Epinephelus lanceolatus ♂) in a simulated pond system and a recirculating aquaculture system

Groupers, as a popular economic fish species, are now more frequently cultured in land-based facilities, however, traditional pond-farming methods are plagued by frequent disease outbreaks, unstable economic benefits, and environmental pollution. To explore a new farming mode for a grouper, an 80-day cultivation experiment was conducted using both a simulated pond system (SPS) and a recirculating aquaculture system (RAS). The research aims to evaluate the growth performance, health (pathogenic bacteria, intestinal microbiota), off-flavor compounds (geosmin, 2-methylisoborneol), and nutritional component (amino acids, fatty acid composition and content) of a hybrid grouper (Pinephelus fuscoguttatus ♀ × Epinephelus lanceolatus ♂) under different aquaculture systems. The results showed that the hybrid grouper in a RAS exhibited better growth performance; the concentration of Vibrio in the fish tissue in the RAS was significantly lower than that in the SPS. Moreover, the content of fresh amino acids in the RAS was significantly higher, and the levels of saturated fatty acids (SFAs) and ω-6 polyunsaturated fatty acids (ω-6PUFAs) were significantly higher in the RAS. This finding indicates the superior flavor and nutritional value of the grouper. These results prove that the RAS is suitable for the widespread cultivation of grouper

Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report

The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based image signal processing (ISP) pipeline replacing the standard mobile ISPs that can run on modern smartphone GPUs using TensorFlow Lite. The participants were provided with a large-scale Fujifilm UltraISP dataset consisting of thousands of paired photos captured with a normal mobile camera sensor and a professional 102MP medium-format FujiFilm GFX100 camera. The runtime of the resulting models was evaluated on the Snapdragon's 8 Gen 1 GPU that provides excellent acceleration results for the majority of common deep learning ops. The proposed solutions are compatible with all recent mobile GPUs, being able to process Full HD photos in less than 20-50 milliseconds while achieving high fidelity results. A detailed description of all models developed in this challenge is provided in this paper

Qwen Technical Report

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to humans. In this work, we introduce Qwen, the first installment of our large language model series. Qwen is a comprehensive language model series that encompasses distinct models with varying parameter counts. It includes Qwen, the base pretrained language models, and Qwen-Chat, the chat models finetuned with human alignment techniques. The base language models consistently demonstrate superior performance across a multitude of downstream tasks, and the chat models, particularly those trained using Reinforcement Learning from Human Feedback (RLHF), are highly competitive. The chat models possess advanced tool-use and planning capabilities for creating agent applications, showcasing impressive performance even when compared to bigger models on complex tasks like utilizing a code interpreter. Furthermore, we have developed coding-specialized models, Code-Qwen and Code-Qwen-Chat, as well as mathematics-focused models, Math-Qwen-Chat, which are built upon base language models. These models demonstrate significantly improved performance in comparison with open-source models, and slightly fall behind the proprietary models.Comment: 59 pages, 5 figure

TSP-1 Secreted by Bone Marrow Stromal Cells Contributes to Retinal Ganglion Cell Neurite Outgrowth and Survival

BACKGROUND: Bone marrow stromal cells (BMSCs) are pluripotent and thereby a potential candidate for cell replacement therapy for central nervous system degenerative disorders and traumatic injury. However, the mechanism of their differentiation and effect on neural tissues has not been fully elucidated. This study evaluates the effect of BMSCs on neural cell growth and survival in a retinal ganglion cell (RGCs) model by assessing the effect of changes in the expression of a BMSC-secreted protein, thrombospondin-1 (TSP-1), as a putative mechanistic agent acting on RGCs. METHODS AND FINDINGS: The effect of co-culturing BMSCs and RGCs in vitro was evaluated by measuring the following parameters: neurite outgrowth, RGC survival, BMSC neural-like differentiation, and the effect of TSP-1 on both cell lines under basal secretion conditions and when TSP-1 expression was inhibited. Our data show that BMSCs improved RGC survival and neurite outgrowth. Synaptophysin, MAP-2, and TGF-beta expression are up-regulated in RGCs co-cultured with BMSCs. Interestingly, the BMSCs progressively displayed neural-like morphology over the seven-day study period. Restriction display polymerase chain reaction (RD-PCR) was performed to screen for differentially expressed genes in BMSCs cultured alone or co-cultured with RGCs. TSP-1, a multifactorial extracellular matrix protein, is critically important in the formation of neural connections during development, so its function in our co-culture model was investigated by small interfering RNA (siRNA) transfection. When TSP-1 expression was decreased with siRNA silencing, BMSCs had no impact on RGC survival, but reduced neurite outgrowth and decreased expression of synaptophysin, MAP-2 and TGF-beta in RGCs. Furthermore, the number of BMSCs with neural-like characteristics was significantly decreased by more than two-fold using siRNA silencing. CONCLUSIONS: Our data suggest that the TSP-1 signaling pathway might have an important role in neural-like differentiation in BMSCs and neurite outgrowth in RGCs. This study provides new insights into the potential reparative mechanisms of neural cell repair