The development of Raparadish (x Brassicoraphanus, 2n=38), a new crop in agriculture

Summary Raparadish, x Brassicoraphanus, the amphidiploid hybrid between Brassica rapa (syn. B.campestris) and Raphanus sativus (fodder radish) was made by Dolstra (1982). Primary hybrid plants grew vigorously, suggesting that the amphidiploid AARR might be useful as a fodder crop. Three populations of this new material were studied, with special attention to improvement of fertility and resistance to beet cyst nematode (Heterodera schachtii), whilst preserving genetic variability. For lack of progress one of the populations was abandoned after the fourth generation. The other two populations were observed through nine or ten generations. Apart from the last two generations mass selection for seed set was carried out on the basis of single plants. This led to a considerable increase in average seed production, without losing a wide variation for this trait. Thus more progress is being expected. Five cycles of mass selection for resistance to beet cyst nematodes led to a considerable increase of the level of resistance of both populations. The prospects of this new agricultural crop are discussed.     

Diallel analysis of yield components,fibre quality and bacterial blight resistance using spaced plants of cotton

Summary Hayman analysis for lint percentage, boll weight, fibre quality and bacterial blight resistance of a ten-parent half-diallel set of crosses was conducted in Upland cotton. The ten parents represented a fixed sample of the best germplasm available to Australian breeders for the characters of commercial importance. Heterosis and inbreeding depression were detected particulady for boll weight and blight resistance. An analysis of genetic components and parameters indicated that since additive effects were substantial and heritability high, early-generation selection of spaced plants and pure-line breeding should be successful. Some genotypes were identified as being potentially good donors for hybridization since they possessed dominant genes for improved character expression. Acala C-1 was identified as the first-choice parent for increased boll size. Coker 315 for increased span length, while Namcala was the best parent for breeding improved fibre strength. McNair 220 possessed the most dominant genes for high lint percentage. Reba P279 and Siokra were the only parents with resistance to the prevelant race of bacterial blight.     

Distribution and Origin of Hybrid Necrosis Genes in German Winter Wheat (Triticum aestivum L.) Cultivars

Hybrid necrosis in Triticum is known to be caused by the interaction of two complementary dominant genes. In the present paper, the genotypes for hybrid necrosis of 64 winter wheat cultivars are presented. 41 cultivars were found to possess the Ne₂ necrosis gene, whereas 23 cultivars were non-carriers. The Ne₁ gene was not found in any of the cultivars analyzed.     

Genetic studies on the interspecific cytoplasm substitution lines of an Asian perennial strain of Oryza rufipogon Griff. and O. glaberrima Steud.

Summary It is shown that the restorer gene Rf _j extracted from the Japanese rice variety Akebono is effective on pollen restoration in the cytoplasm substitution line having the nucleus of Oryza glaberrima and japonica or indica cytoplasm of O. sativa, and is of the sporophytic type.The Asian perennial type of the wild rice species O. rufipogon is considered to be the progenitor of O. sativa. Two substitution lines having the cytoplasm of a perennial strain of O. rufipogon from Sri Lanka and the nucleus of O. glaberrima with or without the gene Rf _j in homozygous condition have been bred by means of successive backcrosses. These lines have now reached the BC₅ generation. Plants of the lines resemble morphologically the recurrent parent, but do not show pollen restoration, indicating that the cytoplasm of the rufipogon strain induced male sterility and that the gene Rf _j does not act as the restorer.     

QTL analysis of Cercospora leaf spot resistance in sugar beet

The inheritance of Cercospora leaf spot resistance in sugar beet was investigated by means of quantitative trait loci (QTL) analysis of a segregating population of 193 individuals, using 110 AFLP and 35 restriction fragment length polymorphism (RFLP) markers. Five QTL were found through composite interval mapping on linkage groups 1, 2, 3, and 9, respectively, two of which were linked on linkage group 3. The significance of these QTL was tested by permutation analysis The QTL had mostly additive, but also certain negative dominance effects; all the resistance alleles came from the Cercospora-resistant parent. Each quantitative trait locus accounted for 7-18% of the phenotypic variation, leaving 37% of the variation unexplained. The results are discussed in relation to the potential use of marker-assisted breeding for Cercospora leaf spot resistance in sugar beet.     

丹东地区种植冬油菜可行性试验

通过对冬油菜品种的适应性、播种时间、种植密度等内容进行试验对比,确定陇油6号适于在丹东地区种植,其越冬成活率受环境因素影响较大;冬油菜越冬能力最强为叶龄8叶左右,适宜播种时间为8月末,种植密度为每5.0万~6.0万株/666.7 m~2。     

Apium graveolens PI 181714 is a source of resistance to Fusarium oxysporum f. sp. apii race 4 in celery (A. graveolens var. dulce)

Celery has little genetic diversity and is highly susceptible to the new fungal pathogen Fusarium oxysporum f. sp. apii (Foa) race 4. After screening an Apium graveolens germplasm collection for resistance to Foa race 4, we crossed celery cv. 'Challenger', which is Foa race 2-resistant but Foa race 4-susceptible and A. graveolens PI 181714, which is Foa races 2- and 4-resistant but non-celery type. After selfing F₁s, we screened the F₁S₁ for race 4-resistance and celery-type and then selfed selected F₁S₁. Greenhouse and field trials indicate that three selected F₁S₂ families (76–8-4, 76–8-27 and 76–8-36) are suitable as germplasm for celery breeders for resistance to Foa race 4. A F1S3 76–8–36-124 is either fixed or nearly so for resistance to Foa races 4 and 2. Furthermore, quantitative PCR indicates that PI 181714 is resistant, rather than tolerant, to Foa races 4 and 2, and that this resistance has been introgressed into F1S3 76–8–36-124.     

New techniques for breeding maize (Zea mays) varieties with fall armyworm resistance and market-preferred traits for sub-Saharan Africa

Deploying maize varieties with fall armyworm (Spodoptera frugiperda [J.E. Smith]; FAW) resistance, desirable product profiles (PPs) and climate resilience is fundamental for food and economic security in sub-Saharan Africa (SSA). This study reviewed and identified challenges and opportunities for effective and accelerated breeding of demand-led maize hybrids with FAW resistance and adaptation to the diverse agro-ecologies of SSA. Lessons were drawn on improving breeding efficiency through adequate genetic variation delivered via prebreeding programmes, speed breeding and a reduced breeding stage plan. Appropriate PPs aligned with demand-led breeding approaches were highlighted as foundations for variety design and commercialization. Challenges to accelerated FAW resistance breeding in maize included inadequate funds and modern tools; poor adaptation of some exotic donor parental lines; lack of information on FAW resistance among local varieties; lack of integration of molecular markers associated with FAW resistance and agronomic traits into selection plans; and limited infrastructure for FAW rearing and germplasm screening. Integration of modern breeding tools and scientific innovations were recommended for accelerated development and release of FAW resistant and market-preferred maize varieties.     

Evidence of scientific research on organic plant breeding: A bibliometric study

Use of varieties bred under organic conditions is essential in order to minimize the yield gap between organic and conventional agriculture. The aim of this study was to analyse research publications related to the topic ‘organic plant breeding’ from the Web of Science database using bibliometric science mapping and visualization tools. The number of analysed documents in the bibliographic dataset was 204 from the 53 sources. The overall trend in the organic plant breeding literature showed that the number of publications increased during the observed time-span. We found that in total, 65 countries and 337 institutions are active in the field of organic plant breeding with a high degree of international collaboration. The top five countries according to the number of publications were the United States, Italy, Germany, France, and Canada, while the most active institutions were Wageningen University, Iowa State University, University of Alberta, University of Copenhagen, and University of Hohenheim. All keywords from the organic plant breeding research in the agronomy category were separated into seven clusters for different research topics. Although there is evident progress viewed through the increased trend in the number of publications, organic plant breeding needs further expansion and development. This is especially through the implementation of novel plant breeding techniques and methods aiming to improve traits that are highly specific to organic conditions.     

Designing optimal training sets for genomic prediction using adversarial validation with probit regression

Genomic selection (GS) is a disruptive methodology that is revolutionizing animal and plant breeding. However, its practical implementation is challenging since many times there is a mismatch in the distribution of the training and testing sets. Adversarial validation is an approach popular in machine learning to detect and address the difference between the training and testing distributions. For this reason, the adversarial validation method in this research was implemented using probit regression to detect the mismatch in distributions and also to select an optimal training set. We evaluated the proposed method with 14 datasets, and the results were benchmarked regarding of using the whole reference population and simple random samples. We found that the proposed method is effective for detecting the mismatch in distributions and outperformed in prediction accuracy by 11.67% (in terms of mean square error) and by 5.35% (in terms of normalized mean square error) when the whole reference population was used as training sets. Also, in general, this outperformed some existing methods for optimal training designs in the context of GS.