An integrated molecular and conventional breeding scheme for enhancing genetic gain in maize in Africa

Open Access Journal; Published online: 06 Nov 2019Maize production in West and Central Africa (WCA) is constrained by a wide range of interacting stresses that keep productivity below potential yields. Among the many problems afflicting maize production in WCA, drought, foliar diseases, and parasitic weeds are the most critical. Several decades of efforts devoted to the genetic improvement of maize have resulted in remarkable genetic gain, leading to increased yields of maize on farmers’ fields. The revolution unfolding in the areas of genomics, bioinformatics, and phenomics is generating innovative tools, resources, and technologies for transforming crop breeding programs. It is envisaged that such tools will be integrated within maize breeding programs, thereby advancing these programs and addressing current and future challenges. Accordingly, the maize improvement program within International Institute of Tropical Agriculture (IITA) is undergoing a process of modernization through the introduction of innovative tools and new schemes that are expected to enhance genetic gains and impact on smallholder farmers in the region. Genomic tools enable genetic dissections of complex traits and promote an understanding of the physiological basis of key agronomic and nutritional quality traits. Marker-aided selection and genome-wide selection schemes are being implemented to accelerate genetic gain relating to yield, resilience, and nutritional quality. Therefore, strategies that effectively combine genotypic information with data from field phenotyping and laboratory-based analysis are currently being optimized. Molecular breeding, guided by methodically defined product profiles tailored to different agroecological zones and conditions of climate change, supported by state-of-the-art decision-making tools, is pivotal for the advancement of modern, genomics-aided maize improvement programs. Accelerated genetic gain, in turn, catalyzes a faster variety replacement rate. It is critical to forge and strengthen partnerships for enhancing the impacts of breeding products on farmers’ livelihood. IITA has well-established channels for delivering its research products/technologies to partner organizations for further testing, multiplication, and dissemination across various countries within the subregion. Capacity building of national agricultural research system (NARS) will facilitate the smooth transfer of technologies and best practices from IITA and its partners

Variety testing for organic farming: current status and problems in Europe

Report is part of Deliverable 4 of 6th FP SSA project “Environmental friendly food production system: requirements for plant breeding and seed production” (ENVIRFOOD) and contains information about current status and problems in EU regarding to organic variety testing

Abandon Statistical Significance

We discuss problems the null hypothesis significance testing (NHST) paradigm poses for replication and more broadly in the biomedical and social sciences as well as how these problems remain unresolved by proposals involving modified p-value thresholds, confidence intervals, and Bayes factors. We then discuss our own proposal, which is to abandon statistical significance. We recommend dropping the NHST paradigm--and the p-value thresholds intrinsic to it--as the default statistical paradigm for research, publication, and discovery in the biomedical and social sciences. Specifically, we propose that the p-value be demoted from its threshold screening role and instead, treated continuously, be considered along with currently subordinate factors (e.g., related prior evidence, plausibility of mechanism, study design and data quality, real world costs and benefits, novelty of finding, and other factors that vary by research domain) as just one among many pieces of evidence. We have no desire to "ban" p-values or other purely statistical measures. Rather, we believe that such measures should not be thresholded and that, thresholded or not, they should not take priority over the currently subordinate factors. We also argue that it seldom makes sense to calibrate evidence as a function of p-values or other purely statistical measures. We offer recommendations for how our proposal can be implemented in the scientific publication process as well as in statistical decision making more broadly

Case study in six sigma methadology : manufacturing quality improvement and guidence for managers

This article discusses the successful implementation of Six Sigma methodology in a high precision and critical process in the manufacture of automotive products. The Six Sigma define–measure–analyse–improve–control approach resulted in a reduction of tolerance-related problems and improved the first pass yield from 85% to 99.4%. Data were collected on all possible causes and regression analysis, hypothesis testing, Taguchi methods, classification and regression tree, etc. were used to analyse the data and draw conclusions. Implementation of Six Sigma methodology had a significant financial impact on the profitability of the company. An approximate saving of US$70,000 per annum was reported, which is in addition to the customer-facing benefits of improved quality on returns and sales. The project also had the benefit of allowing the company to learn useful messages that will guide future Six Sigma activities

Strain comparisons in aquaculture species: a manual

When different strains or breeds of a particular species are available, the best choice is seldom immediately obvious for producers. Scientists are also interested in the relative performance of different strains because it provides a basis for recommendations to producers and it often stimulates the conduct of work aimed at unraveling the underlying biological mechanisms involved in the expression of such differences. Hence, strain or breed comparisons of some sort are frequently conducted. This manual is designed to provide general guidelines for the design of strain comparison trials in aquaculture species. Example analyzes are provided using SAS and SPSS. The manual is intended to serve a wide range of readers from developing countries with limited access to information. The users, however, are expected to have a basic knowledge of quantitative genetics and experience in statistical methods and data analysis as well as familiarity with computer software. The manual mainly focuses on the practical aspects of design and data analysis, and interpretation of results

How predictable is technological progress?

Recently it has become clear that many technologies follow a generalized version of Moore's law, i.e. costs tend to drop exponentially, at different rates that depend on the technology. Here we formulate Moore's law as a correlated geometric random walk with drift, and apply it to historical data on 53 technologies. We derive a closed form expression approximating the distribution of forecast errors as a function of time. Based on hind-casting experiments we show that this works well, making it possible to collapse the forecast errors for many different technologies at different time horizons onto the same universal distribution. This is valuable because it allows us to make forecasts for any given technology with a clear understanding of the quality of the forecasts. As a practical demonstration we make distributional forecasts at different time horizons for solar photovoltaic modules, and show how our method can be used to estimate the probability that a given technology will outperform another technology at a given point in the future

EffiTest: Efficient Delay Test and Statistical Prediction for Configuring Post-silicon Tunable Buffers

At nanometer manufacturing technology nodes, process variations significantly affect circuit performance. To combat them, post- silicon clock tuning buffers can be deployed to balance timing bud- gets of critical paths for each individual chip after manufacturing. The challenge of this method is that path delays should be mea- sured for each chip to configure the tuning buffers properly. Current methods for this delay measurement rely on path-wise frequency stepping. This strategy, however, requires too much time from ex- pensive testers. In this paper, we propose an efficient delay test framework (EffiTest) to solve the post-silicon testing problem by aligning path delays using the already-existing tuning buffers in the circuit. In addition, we only test representative paths and the delays of other paths are estimated by statistical delay prediction. Exper- imental results demonstrate that the proposed method can reduce the number of frequency stepping iterations by more than 94% with only a slight yield loss.Comment: ACM/IEEE Design Automation Conference (DAC), June 201