Agricultural Genetics and Plant Breeding in Early Twentieth-Century Italy

This thesis is about plant breeding in Early 20th-Century Italy. The stories of the two most prominent Italian plant-breeders of the time, Nazareno Strampelli and Francesco Todaro, are used to explore a fragment of the often-neglected history of Italian agricultural research. While Italy was not at the forefront of agricultural innovation, research programs aimed at varietal innovation did emerge in the country, along with an early diffusion of Mendelism. Using philosophical as well as historical analysis, plant breeding is analysed throughout this thesis as a process: a sequence of steps that lays on practical skills and theoretical assumptions, acting on various elements of production. Systematic plant-breeding programs in Italy started from small individual efforts, attracting more and more resources until they became a crucial part of the fascist regime's infamous agricultural policy. Hybrid varieties developed in the early 20th century survived World War II and are now ancestors of the varieties that are still cultivated today. Despite this relevance, the history of Italian wheat hybrids is today largely forgotten: this thesis is an effort to re-evaluate a part of it. The research did allow previously unknown or neglected facts to emerge, giving a new perspective on the infamous alliance between plant-breeding programs and the fascist regime. This thesis undertakes an analysis of Italian plant-breeding programs as processes. Those processes had a practical as well as a theoretical side, and involved various elements of production. Although a complete history of Italian plant breeding still remains to be written, the Italian case can now be considered along with the other case-studies that other scholars have developed in the history of plant breeding. The hope is that this historical and philosophical analysis will contribute to the on-going effort to understand the history of plants.

Genome projects and gene pools: New germplasm for plant breeding?

Crop gene pools have adapted to and sustained the demands of agricultural systems for thousands of years. Yet, very little is known about their content, distribution, architecture, or circuitry. The presumably shallow elite gene pools often continue to yield genetic gains while the exotic pools remain mostly untapped, uncharacterized, and underutilized. The concept and content of a crop’s gene pools are being changed by advancements in plant science and technology. In the first generation of plant genomics, DNA markers have refined some perceptions of genetic variation by providing a glimpse of a primary source, DNA polymorphism. The markers have provided new and more powerful ways of assessing genetic relationships, diversity, and merit by infusing genetic information for the first time in many scenarios or in a more comprehensive manner for others. As a result, crop gene pools may be supplemented through more rapid and directed methods from a greater variety of sources. Previously limited by the barriers of sexual reproduction, the native gene pools will soon be complemented by another gene pool (transgenes) and perhaps by other native exotic gene pools through comparative analyses of plants’ biological repertoire. Plant genomics will be an important force of change for crop improvement. The plant science community and crop gene pools may be united and enriched as never before. Also, the genomes and gene pools, the products of evolution and crop domestication, will be reduced and subjected to the vagaries and potential divisiveness of intellectual property considerations. Let the gains begin.

Plant-breeding; comments on the experiments of Nilsson and Burbank,

Mode of access: Internet.

Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials

For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.

Estimation and prediction of parameters and breeding values in soybean using REML/BLUP and Least Squares

The aim of this study was to compare REML/BLUP and Least Square procedures in the prediction and estimation of genetic parameters and breeding values in soybean progenies. F(2:3) and F(4:5) progenies were evaluated in the 2005/06 growing season and the F(2:4) and F(4:6) generations derived thereof were evaluated in 2006/07. These progenies were originated from two semi-early, experimental lines that differ in grain yield. The experiments were conducted in a lattice design and plots consisted of a 2 m row, spaced 0.5 m apart. The trait grain yield per plot was evaluated. It was observed that early selection is more efficient for the discrimination of the best lines from the F(4) generation onwards. No practical differences were observed between the least square and REML/BLUP procedures in the case of the models and simplifications for REML/BLUP used here.