Challenges in commercialisation of protected university agricultural research outputs: a review in the context of global hunger and the Kenyan experience

Challenges in commercialisation of protected university agricultural research outputs: a review in the context of global hunger and the Kenyan experience

This study examined the impact of agriculture sector growth on unemployment level as well as the direction of causality between agricultural sector output and unemployment level in Nigeria. Secondary annual time series data between 1981 and 2016 were used for the study. Data on unemployment rate, agriculture sector output, public expenditure and industrial output were obtained from the Central Bank of Nigeria’s statistical Bulletin while data on FDI and population growth were obtained from the World Bank World Development Indicators. The data were analyzed using ADF (Augmented Dickey Fuller Test) unit root test, Autoregressive distributed lag Bounds test of cointegration, Autoregressive distributed lag error correction model estimation and Granger causality. The results of ADF unit root test revealed variables were at different orders of integration, the ARDL bounds test revealed cointegration between variables, and the Autoregressive distributed lag error correction model estimation revealed that change in agriculture output in the current period is negative and significant for current unemployment level in Nigeria, while the change in one period lagged agriculture output was positive and significant for current unemployment level in Nigeria. Also the error correction term indicated that about 74.10 percent of the disequilibrium in the system in the previous year would be corrected in the current year. Granger causality test results revealed bi-directional causality between agriculture output and unemployment level in Nigeria. The study recommends that the Nigeria government should using strategic policies targeted at boosting agriculture output such as increasing access to land for peasant rural farmers, investments in agricultural research, and so on, seek to boost agriculture output in order to reduce unemployment in Nigeria. Further, the Nigeria government should ensure that agriculture sector development policies are consistent with the objective of reducing unemployment in Nigeria.

Allocative decisions concerning public sector agricultural research appear to be driven by both supply and politically mediated demand forces. In‐sample Granger tests, along with post‐sample predictive tests, suggest that simultaneity issues should not be ignored when modeling the research expenditure‐output relationship. The results also provide strong evidence that the impact of research expenditures on agricultural output may persist for as long as thirty years. These lags are substantially longer than those commonly used for agricultural research to date. The lagged effect of output on research appears to be shorter, though still between ten and twelve years.

This article investigated the causal relationship between public agricultural research expenditures and agricultural output in Lesotho. Cointegration and Granger-causality tests were performed to determine the causal relationship between agricultural research and agricultural output. Lag length tests were performed to facilitate the Cointegration analysis. Results of the empirical analysis indicated that agriculture in Lesotho is driven by agricultural research. The results also showed that it takes seven to eight years for public agricultural research expenditures to have a significant impact on agricultural output in Lesotho.

• By 2050, global agricultural demand is projected to grow by 70-100 percent due to population growth, energy demands, and higher incomes in developing countries. Meeting this demand from existing agricultural resources will require raising global agricultural total factor productivity (TFP)1 by a similar level. Maintaining the U.S. contribution to global food supply would also require a similar rise in U.S. agricultural TFP. • TFP growth in U.S. agriculture is predicated on long-term investments in public agricultural research and development (R&D). Productivity growth also springs from agricultural extension, farmer education, rural infrastructure, private agricultural R&D, and technology transfers, but the force of these factors is compounded by public agricultural research. • The rate of TFP growth (and therefore output growth) of U.S. agriculture has averaged about 1.5 percent annually over the past 50 years. Stagnant (inflation-adjusted) funding for public agricultural research since the 1980s may be causing agricultural TFP growth to slow down, although statistical analyses of productivity growth trends are inconclusive. • ERS simulations indicate that if U.S. public agricultural R&D spending remains constant (in nominal terms) until 2050, the annual rate of agricultural TFP growth will fall to under 0.75 percent and U.S. agricultural output will increase by only 40 percent by 2050. Under this scenario, raising output beyond this level would require bringing more land, labor, capital, materials, and other resources into production. • Additional public agricultural R&D spending would raise U.S. agricultural productivity and output growth. Raising R&D spending by 3.73 percent annually (offsetting the historical rate of inflation in research costs) would increase U.S. agricultural output by 73 percent by 2050. Raising R&D spending by 4.73 percent per year (1-percent annual growth in inflation-adjusted spending) would increase output by 83 percent by 2050.

AI is transforming the intellectual property landscape, presenting both challenges and opportunities for research, innovation, and businesses. This study aimed to perform an in-depth examination of the current state of Ethiopian intellectual property legislation concerning the protection of agricultural research outputs generated using artificial intelligence. This study was conducted through qualitative research methodology by reviewing academic literature, policy documents, and IP legislations. The Study focused on analyzing the impact of AI on Ethiopian patent, copyright, and data protection laws to protect agricultural research outputs. When AI-assisted research and innovations grow in agricultural research, the traditional IP regimes should not answer the ownership rights of the research output. The result shows that the current IP laws do not provide full protection for AI-generated research outputs. As a result, Ethiopia should revise the provisions of the existing patent, copyright, and data protection laws in consideration of AI-generated technologies.

Turning university research output into useful products such as drugs, devices and diagnostics requires skills, knowledge, and resources traditionally attributed to private industry. When it comes to intangibles such as care delivery models, informatics and algorithms, and the software behind smart wearables, the commercialization challenges are even greater. With notable exceptions, Academic Medical Centers have typically not excelled in advancing commercialization of such non-patent intellectual property (IP). We believe that this is in part because the traditional closed form university IP policy, formulated since Bayh–Dole (1980), is ill-suited to non-patent IP. In this paper, we reflect on the evolving challenges that new forms of healthcare-related discoveries, specifically non-patent IP, are placing on the traditional university intellectual property and technology transfer regime, and to offer suggestions on how universities can begin to modernize their IP policies to support the valorization of non-patent IP.

The implementation of new technologies comes with the use of digitalization and Artificial Intelligence (AI) as core drivers. AI, including machine learning and deep learning, thrives in digitally mature environments with robust infrastructures and vast data availability With respect to AI innovations, digitalization is equally important because it provides the necessary computation power, data frameworks, and even the network systems needed to spearhead innovations. However, global disparities exist, with the United States and China excelling in AI commercialization, while Europe leads in academic research but struggles with industry adoption due to fragmented policies and inconsistent investment in AI-driven enterprises. This study conducts a systematic bibliometric analysis to examine the relationship between digitalization and AI research productivity. Using data from the Web of Science Core Collection, bibliometric techniques such as keyword co-occurrence analysis, citation network mapping, and thematic clustering were applied to assess AI research trends and their connection to digitalization. Responding to the outlining issue: How has digitalization influenced AI research evolution, and what are the key bibliometric trends? Findings confirm that digitally advanced regions lead in AI research output, while Europe faces commercialization challenges due to regulatory constraints and weak industry-academia collaboration. This study offers a novel contribution by integrating bibliometric analysis with policy insights to examine AI commercialization challenges, a dimension that has received limited attention in prior systematic reviews. This analysis points to insufficient academic activity and industrial adoption and calls for collaboration, dedicated policies for AI, and infrastructure investments. This helps policymakers focused on AI innovation as well as those in charge of AI governance and business leaders aiming to improve industry competition and commercialization.

Organic farming is a good choice for agricultural development in southwest China under the trade-off between environmental protection and agricultural development. However, no researcher has investigated the current state and development of organic agriculture in southwest China. As a result, this paper explored the spatial structure of organic agriculture in southwest China by examining the distribution of organic certificates, as well as the environmental and socioeconomic impacts. The results show a dramatically uneven distribution of certified organics among different provinces, cities, and organic certificate types. On the province scale, Guizhou has the highest number (1174) and density (73.40 per 1010 m2) of organic certificates. On the city scale, Zunyi and Chengdu have the highest densities (218.77 and 342.52 per 1010 m2, respectively). Most of the certified organics are plants, accounting for 76.95%. The spatial distribution of organic farming is influenced by the interaction of several factors, including precipitation, temperature, GDP, highway density, gross agriculture output, agriculture machinery, and rural employed persons. However, the related and determinant factors of organic certificate distribution vary greatly across different regions, spatial scales, economic development levels, and agricultural development statuses. For the entirety of southwestern China, the factors significantly related to the distribution of organic certificates are GDP, highway density, gross agriculture output, agriculture machinery, and rural employed persons. However, these factors are GDP, gross agriculture output, agriculture machinery, and rural employed persons for Sichuan, and gross agriculture output and rural employed persons for Guizhou. Factors constraining the development of organic agriculture in regions with better economic and agricultural conditions are much fewer than in poorer regions. All of the nine selected variables, except global radiation, are significantly related to organic certificate distribution in regions with better economic conditions, while none of them had a significant correlation with organic certificate distribution in poorer regions. Furthermore, climate is no longer a constraint in regions with better agricultural conditions. These findings are of great significance for the development and research of organic agriculture in southwest China. The development of organic agriculture in southwest China requires consideration of both the combination of multiple factors and the stage of regional economic and agricultural development.

In order to improve the performance of agriculture in Nigeria different agricultural research institutions were established. Realising the fact that economic and social development is based on progress in agricultural as well, these agricultural institutions have been striving to ensure food security in the country. But all these efforts have not yielded the desired result as the agricultural output in Nigeria can still not compete favourably with developed countries. Though, it has been established that there can be no research without information. Information is one of the components to achieve sustainable progress in agricultural research. Could it be that the agricultural researchers are not getting enough information for their research activities or they are not satisfied with information provided for research? Thus this study assessed agricultural researcher’s satisfaction in terms of information facilities, sources, resources and contents using the researcher in all agricultural research institutions affiliated to agricultural research council of Nigeria (ARCN). The findings revealed that satisfaction with information facilities and information resources are high; but there is need for upgrade in information content and services for better satisfaction. Thus the study made some recommendations for better satisfaction so that there can be increased in research output which will in turn improve agricultural output in Nigeria. Key words: User's satisfaction, information provision, agriculture, researchers, research institutes.

Driving initiatives for future improvements of specialty agricultural crops

To estimate the local effect of establishing land grant colleges, I compare locations that receive a land grant college to “runner-up” counties that were in contention to receive the land grant but did not for as-good-as-random reasons. I find that establishing a land grant college causes an increase in local invention, including in particular agricultural inventions, in college counties relative to the runner-up counties. But land grant college counties see only small and imprecisely estimated improvements in agricultural performance, measured by yield and output, relative to runner-up counties. I discuss several alternative interpretations of these findings. By comparing the establishment of land grant colleges to non-land grant colleges, I show that land grants appear to cause smaller increases in local invention, population, and agricultural output, but larger increases in agricultural yields and new crop varieties. The effect of land grant colleges on local innovations is largest, even relative to non-land grant colleges, following the passage of legislation that increases funding to agricultural research.

This paper reviews the long-term impact of public investments on irrigation and agricultural research and development along with other control variables, including physical capital, irrigated area, fertilizer consumption, level of mechanization, and CO2 emissions on China’s agricultural output from 1986 to 2017. This study applied various econometric methods such as the ARDL bound-testing approach and Johansen co-integration procedure to determine the long-term co-integrating connection amid the variables. The empirical outcomes from the ARDL bound-testing method confirm a long-term co-integrating connection among the variables. The long-run results demonstrated that public investment in agricultural research and development and irrigation have a substantial positive effect on agricultural productivity. Furthermore, results revealed that physical capital and fertilizer consumption also have a significant positive effect on agricultural output; however, CO2 emissions have a substantial negative effect on agricultural production. These findings therefore suggest that the policy makers of China should initiate more effective policies to increase irrigation and agricultural research and development investments. Increasing irrigation and agricultural research and development investments will enhance agricultural productivity by ensuring food security in the country.

Agricultural research, as with many other governmental services, can be performed efficiently at the state level but produces benefits that accrue to a broader area than just the originating state or region. Results from basic research, for example, would be unrestricted by geographic boundaries. Even applied research which is designed to solve specific problems encountered in a particular state may result in spi1lovers--geographically external benefits--to other areas. For example, some research results can readily be applied over wide geographic areas while other results need only additional adaptive research before they are suitable for other areas. The idea that the benefits of agricultural research are not realized solely by the state or region providing the research expenditures is not a new one. Several researchers have analyzed the interregional diffusion of a particular technology (Peterson and Hayami, 1977, pp. 524-526). In the study of hybrid corn diffusion, Griliches (1957) found that differences among regions in adoption rates were dependent on such factors as the size and density of commodity production and profitability of the new technology. Despite the widespread concern over the diffusion of a particular technology, the external benefits of agricultural research have not received much attention from economists working in the general area of research evaluation and planning. Attempts at measuring the contribution of agricultural research to agricultural production have often utilized a production function for a commodity or agricultural sector as a whole in such a manner that research was included as a separate variable (Peterson and Hayami, 1977, pp. 520-521). The majority of studies which have included research as a separate variable in a production function have been aimed at the national level rather than the regional or state levels. Griliches' (1964) work was one of the first publications in the area and Evenson's (1967) work was really important because it revealed the nature of the lag between the research input and increased output. The production function approach provides an estimate of the marginal product of agricultural research which is particularly useful in guiding decisions about allocation of resources to agricultural research. Studies directed at the state or regional level confront a major problem not encountered in a national analysis: interregional spillovers of the benefits from agricultural research results. This problem has been termed pervasiveness, indicating the tendency for research results generated in one region to be incorporated into farm production functions in other regions (Evenson, 1971, p. 173). Latimer and Paar1berg (1965) and Evenson (1971) recognized the pervasiveness problem. Latimer and Paarlberg were unable to find a statistically significant relationship between research expenditures within the state and agricultural output. They attributed these findings to the pervasive nature of agricultural research results (Latimer and Paarlberg, p. 239). Evenson included a variable which measured the intensity of commodity research in an attempt to control for the pervasiveness of research (1971, p. 177). If research results were completely pervasive, Evenson argued, this variable would dominate the state research variable. The variable was statistically significant indicating that the interregional transfer of agricultural research results should be taken into account in cross-sectional analyses. The existence of spillover benefits has a bearing on the allocation of research funds both within and between states. One important problem is to determine the appropriate balance between federal and state government in financing agricultural research. More specifically, what portion of the research expenditures should be financed by the federal government? The federal government initially served as a catalyst in developing the institutional framework to conduct agricultural research. The Morrill Land Grant College Act of 1862 and the Hatch Agricultural Experiment Station Act of 1887 reflect the emergence of a dual federal-state approach to agricultural research (Peterson and Fitzharris, 1977, pp. 72-73). Under these acts, each state received funds for a college of agricultural and mechanical arts and for an agricultural experiment station. This institutional framework is still a dominant force in agricultural research. Federal funds are allocated by a formula which is based largely on a state's rural and farm population (Peterson and Hayami, 1977, p. 522). Assuming that this system of finance was appropriate when it was first devised, is it still equitable after almost a century? This paper deals with the effects of spillovers of agricultural research benefits on the financing of research by federal and state governments. It considers conceptual problems of financing government services which produce spillovers and proposes a model to align a region's investment in agricultural research with social benefits by compensating for spillovers with funds from the federal government. Interregional spillovers of the benefits from agricultural research results are empirically measured in order to determine the appropriate balance between federal and state funding of agricultural research.

Chapter three - Significance of Phosphorus for Agriculture and the Environment in the West Asia and North Africa Region