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This paper aims to review the current status of wheat production, farming systems, production constraints and wheat demand-supply chain analysis; the role of international and national breeding programs and their approaches in wheat genetic improvement including targeting mega environments, shuttle breeding, doubled haploids, marker-assisted selection and key location phenotyping; and future prospects and opportunities of wheat production in Sub Saharan Africa (SSA).

Relevant literature works have been used and cited accordingly.

Though traditionally wheat was not the leading staple crop in SSA, it is becoming an important food crop because of rapid population growth associated with increased urbanization and change in food preference for easy and fast food such as bread, biscuits, pasta, noodles and porridge. In 2013, total wheat consumption in SSA reached 25 million tons with import accounting for 17.5 million tons at a price of USD6 billion, while during the same period the region produces only 7.3 million tons on a total area of 2.9 million hectares. The low productivity (2t/ha) in the region is principally because of abiotic (drought and heat) and biotic (yellow rust, stem rust, septoria and fusarium) stresses which are increasing in intensity and frequency associated with climate change. Furthermore, increased cost of production, growing populations, increased rural-urban migration, low public and private investments, weak extension systems and policies, and low adoption rates of new technologies remain to be major challenges for wheat production in SSA. Wheat breeding in SSA is dominantly carried out by National Agricultural Research Systems, in partnership with the international research centers [International center for improvement of maize and wheat (CIMMYT) and International center for agricultural research in the dry areas (ICARDA)], to develop high yielding and widely adapted wheat genotypes with increased water-use efficiency, heat tolerance and resistance to major diseases and pests. Most of the cultivars grown in SSA are originated from the international research centers, CIMMYT and ICARDA.

This paper will help to promote available wheat technologies in SSA by creating awareness to wheat scientists, extension agents and policymakers.

This manuscript is an original review paper which has not been published in this form elsewhere.

Animal production is still a major UK industry of about £10 billion and like all aspects of agriculture faces a number of challenges. The biotechnology revolution is also sweeping through the industry with a range of major emerging technologies becoming available. Describes these technologies and discusses their potential impact on the agro‐food industry and the public. Although the issues raised appear at first sight novel, they can be regulated under the current framework available within the UK; public concern over some of the technologies is genuine but in most cases can be answered. Currently research in the UK puts this country at the forefront of these technologies and the emerging commercial opportunities must not be lost.

The purpose of this paper is to develop an analytical model to value traits at different developmental phases and to determine the value of drought tolerance (DT) in wheat using GM technology.

A stochastic binomial real-options model of GM traits was developed to estimate the value of a DT wheat trait.

The results indicate that the value of DT wheat using GM technology is in-the-money at each development phase. The greatest value would accrue for the Prairie Gateway and Northern Great Plains regions in the USA.

The approach is useful for valuing high-cost risky investments in technology and results provide guidance for development strategies.

The model is original and its applications to wheat are unique.

The purpose of this paper is to express a general review on how best in the present time can one market genetically modified (GM) foods in the face of the controversial arguments faced globally. Despite the importance of marketing, many organizations though they understand its worth, fail to find radical strategic solutions for the problems encountered by their products. In fact most of them find that disclosing GM ingredients will prohibit consumers from buying their products, whilst, the few GM foods that were proactively marketed indicated the potential of effective marketing and successful product placement.

To be able to market GM foods, an understanding of customer value and problems customers envisage is discussed. The paper attempts to provide a general global perspective on consumer’s views about these issues and with the help of a conceptual model it attempts to identify some of the problems related with marketing GM foods.

The findings indicate that these products would have to be repositioned as being seen as less risky and more beneficial to consumers in the light that they can be scientifically proven.

This research is innovative in the sense it demonstrates an understanding of how to provide customer value for not only consumers who are the ultimate end users but also provides an insight to a broader audience such as manufacturers, agriculturalists and marketing professionals as to what are some of the contributing factors that consumers look for to make an informed choice.

The retention and success of engineering undergraduates are increasing concern for higher-education institutions. The study of success determinants are initial steps in any remedial initiative targeted to enhance student success and prevent any immature withdrawals. This study provides a comprehensive approach toward the prediction of student academic performance through the lens of the knowledge, attitudes and behavioral skills (KAB) model. The purpose of this paper is to aim to improve the modeling accuracy of students’ performance by introducing two methodologies based on variable selection and dimensionality reduction.

The performance of the proposed methodologies was evaluated using a real data set of ten critical-to-success factors on both attitude and skill-related behaviors of 320 first-year students. The study used two models. In the first model, exploratory factor analysis is used. The second model uses regression model selection. Ridge regression is used as a second step in each model. The efficiency of each model is discussed in the Results section of this paper.

The two methods were powerful in providing small mean-squared errors and hence, in improving the prediction of student performance. The results show that the quality of both methods is sensitive to the size of the reduced model and to the magnitude of the penalization parameter.

First, the survey could have been conducted in two parts; students needed more time than expected to complete it. Second, if the study is to be carried out for second-year students, grades of general engineering courses can be included in the model for better estimation of students’ grade point averages. Third, the study only applies to first-year and second-year students because factors covered are those that are essential for students’ survival through the first few years of study.

The study proposes that vulnerable students could be identified as early as possible in the academic year. These students could be encouraged to engage more in their learning process. Carrying out such measurement at the beginning of the college year can provide professional and college administration with valuable insight on students perception of their own skills and attitudes toward engineering.

This study employs the KAB model as a comprehensive approach to the study of success predictors. The implementation of two new methodologies to improve the prediction accuracy of student success.

Development of new cultivars requires extensive genetic knowledge, trained personnel, and significant financial resources, so it is crucial for breeders to focus on the attributes most preferred by the key supply chain stakeholders such as consumers and producers. The purpose of this paper is to identify which attributes generate the highest total revenue or social surplus, information that breeders can take into account as they allocate resources to focus on attributes in their breeding programs.

This study used mail-in and online surveys to collect consumer and producer choice experiment data, and then employed mixed logit models to analyze and simulate individual producer and consumer willingness to pay (WTP) for the apple attributes.

Based on the simulation results, this study derived the supply and demand curves and the market equilibrium prices and quantities for each apple attribute. Based on the WTP analysis for both consumer and producer, this paper found the highest equilibrium price and welfare for apples come from crispness, followed by flavor.

The authors propose a framework to estimate the equilibrium prices and quantities of a product based on the results of choice experiments. The framework can be easily adapted to understand any countries’ producer and consumer preferences for certain products.

Circumstances that are have a significant impact on it. In particular, environmental sustainability related to the increase of worldwide population, and market demand for agricultural products (with consumers more and more aware about cultivation and breeding techniques and interested in healthy and high-quality products) represent two of the key challenges that the agricultural sector is going to face in next years. In such a landscape, technological innovations that can support organizations and entrepreneurs to face these problems become increasingly important, and Industry 4.0 is the most striking example. Indeed, the Industry 4.0 paradigm aims to integrate digital technologies into business processes to raise productivity levels and to develop new business models. Accordingly, digital technologies play a similar role in the precision agriculture domain, and the purpose of this paper is to understand if the technologies at the basis of these two paradigms are the same or not.

The present work investigates how the two domains of Industry 4.0 and precision agriculture are connected to one another by analyzing the most used technologies in both the fields in order to highlight common patterns and technological overlaps. To reach such goal, an approach combining manual and automated analysis was developed.

The research work generated three main results: a dictionary of precision agriculture technologies including 324 terms; a graph, describing the connections between the technologies composing the dictionary; and a representation of the main technological clusters identified.

These show how the two domains under analysis are directly connected and describe the most important technologies to leverage when approaching digital transformation processes in the agricultural sector.

β-Carotene is the most appropriate and significant precursor of vitamin A. Synthetic carotene supplements have been known to pose a threat to human health, making natural sources such as the indefensible choice for the production and extraction of carotene.

This study considers Blakeslea trispora, a filamentous fungus, as a source of production of carotenoids by fermentation and wet and dry mycelium were used to analyse and obtain better extraction results.

In this study, natural oils such as soy oil and cottonseed oil were incorporated into fermentation media to increase the production of carotene. For the optimization process, Plackett–Burman and one-factor-at-a-time (OVAT) models were identified as being of great value.

OVAT was carried out for corn starch because it plays a major role in the production of carotene and the corn starch at 30 g/L concentration has shown the maximum activity of 3.48 mg/gm. After optimizing process variables, submerged fermentation was eventually carried out under highly controlled media conditions. The resulting product was quantified using UV spectroscopy and extraction of carotene has been observed in the presence of various solvents. Among a range of solvents used, the methylene Di chloride produced-carotene at 86% recovery at a significantly lower temperature of 35°C.

The purpose of this paper is to analyze geographic heterogeneity of consumer preferences for intrinsic quality attributes of rice in South and Southeast Asia and the drivers of demand for these attributes, with a particular focus on rice fragrance and the role of gender.

Stated-preference surveys were conducted with 4,231 urban and rural consumers in 37 cities across seven countries (Bangladesh, India, Cambodia, Indonesia, the Philippines, Thailand, and Vietnam) during 2013–2014 and analyzed through a rank-ordered logistic regression with incomplete ranking choice data.

Preferences for rice attributes are found to be significantly heterogeneous among consumers in South and Southeast Asia. Urban Thai consumers tend to prioritize appearance and cooking characteristics over taste and nutritional benefits, relative to all other surveyed consumers. In contrast with South Asian consumers, Southeast Asian consumers have largely adopted Thai preferences for rice texture and fragrance, a trend that was earlier coined “Jasminization.” We find that demand for rice fragrance is mainly driven by women, educated consumers, large families, families spending a lower share of their food expenditures on rice, and consumers in Southeast Asia (particularly the Philippines and Cambodia).

Little is known about geographic heterogeneity, drivers, and the role of gender in demand for rice fragrance. This paper fills these knowledge gaps. Our findings suggest that the more women are empowered in grocery decision-making, the more demand for aromatic rice is expected to rise. These insights can assist market-driven and gender-responsive rice breeding programs in simultaneously enhancing rice farmers' livelihoods and gender equity.