Читать книгу Biotechnology of Fruit and Nut Crops - Группа авторов - Страница 129

BREEDING FOR OIL YIELD. Although conventional breeding in combination with improved field management has increased crude palm oil yield from 2.6 t/ha to 4.0 t/ha during the past 60 years, there is still a big yield gap between that and the estimated theoretical potential of 18.2 t/ha (Barcelos et al., 2015). Breeding for oil yield still remains one of the major challenges for breeders and molecular biologists as it is a major goal for maximizing production (Tittonell, 2014; Woittiez et al., 2017). Oil yield results from a composite character made up of many traits including sex ratio, fruit to bunch ratio, weight per bunch, bunch number and oil per fruit. These characters vary continuously although some of them are highly heritable and may be amenable to quantitative trait loci (QTL) analysis using molecular markers.

BREEDING FOR INTEGRATED PEST MANAGEMENT. Attention must be paid to the oil palm responses to the occurrence and spread of pest and diseases on the one hand and to changes in patho-systems on the other hand. Indeed, Paterson et al. (2013) anticipated that land will become increasingly unsuitable for growing oil palm and the plants will become more stressed, thus allowing the ingress of fungal diseases. It is thus of paramount importance to explore the genetic determinisms governing tolerance to major diseases. Indeed, the oil palm is susceptible to three rather specific diseases in each of the three continents where it is cultivated. In Africa, vascular wilt, caused by Fusarium oxysporum elaeidis, can cause up to 70% mortality. In South-east Asia, Ganoderma boninense has been found to cause up to 80% mortality in some regions. In Latin America, a bud rot disease of yet unknown origin, although Phytophthora is a prime suspect, can be responsible for 100% losses in oil palm plantations (Cochard et al., 2005). For these three rather endemic diseases, genetic control strategies are being developed; indeed, the improvement of oil palm for disease tolerance is based on field observations of the susceptibility of parental material and their crosses and on the assessment of the tolerance of each cross of interest through inoculation of the pathogens at the pre-nursery stage. This process is very long and uncertain as to the genetic value of the parents and to the relationship between controlled inoculations and natural infection in the field, and this has to be assessed on a case-by-case basis. However, the data already generated and currently being processed have allowed the implementation of quantitative genetic analyses to explore the genetic basis of oil palm tolerance to these three major diseases. QTL research is being implemented for Fusarium wilt tolerance through the pre-nursery inoculation of a large mapping population, while testing for Ganoderma tolerance is based on a multi-parental genetic trial involving 14 families evaluated in the field in Indonesia for 25 years. In Latin America, bud rot resistance is assessed on first- and second-generation interspecific backcrosses planted in zones severely affected by the disease. The identification of genetic determinisms by appropriate methods will allow: (i) identification of candidate genes on the basis of variation in disease tolerance within the species; (ii) elucidation of the key processes involved in tolerance through cross-checking between different diseases and between nursery tests and natural conditions; and (iii) implementation of marker-assisted selection (MAS) for the rapid and relevant integration of resistance sources into elite genotypes.

In order to process field data obtained under natural conditions of infection, analyses are based on epidemiological models coupled with genetic models, such as QTL or genome-wide association study (GWAS), or bulk segregant analysis. When the disease is very aggressive, the use of early tests at the pre-nursery stage requires preliminary analyses before being implemented. In both cases, the genetic mapping approach is coupled with transcriptomic studies on crosses identified as sensitive or resistant in order to identify genes that are differentially expressed during infection and between susceptible and resistant material. The combination of the two approaches will enable the identification of candidate genes as a basis for functional and diversity studies with the aim of involving such genes in an MAS scheme.

Multi-parental populations are promising tools for identifying quantitative disease resistance loci. Stem rot is a major threat to palm oil production, prompting premature replantation of palms. There is evidence of genetic resistance sources (Durand-Gasselin et al., 2005), but the genetic architecture of Ganoderma resistance has not yet been investigated. Tisné et al. (2017) identified Ganoderma resistance loci using an oil palm multi-parental population derived from nine major founders of ongoing breeding programmes. A total of 1200 palm trees of the multi-parental population were planted in plots naturally infected by Ganoderma, and their health status was assessed biannually over 25 years. The data were treated as survival data, and modelled using the Cox regression model, including a spatial effect to take the spatial component in the spread of Ganoderma into account. Based on the genotypes of 757 palm trees out of the 1200 planted, and on pedigree information, resistance loci were identified using a random effect with identity-by-descent kinship matrices as covariance matrices in the Cox model. Four Ganoderma resistance loci were identified, two controlling the occurrence of the initial stem rot symptoms, and two controlling the death of palm trees, while favourable haplotypes were identified among a major gene pool for ongoing breeding programmes. Tisné et al. (2017) developed an efficient and flexible QTL mapping approach and generated unique valuable information for the selection of oil palm with resistance to stem rot disease.

BREEDING FOR CLIMATE CHANGE. Breeding the oil palm for resilience to global change requires multidisciplinary and collaborative research involving almost all disciplines related to life sciences (Rival, 2017). Research also relies on identifying genetic variation in the plant responses to stress and this implies the exploitation of natural variation, germplasm collections, selected genitors from breeding programmes together with material of interest collected from smallholders. The phenotyping of selected plant material under biotic/abiotic stresses will involve new methods for high-throughput phenotyping, and genomic approaches will be followed for the identification of genes underlying the variation of traits which will be used as selection targets. Improvements in understanding how climate change may influence chemical and physical processes in soils, how this may affect nutrient availability, and how the plant responds to changed availability of nutrients will also influence oil palm breeding. With genomic resources becoming increasingly available for the oil palm (sequencing, resequencing and chips development) the exploration of the genetic basis of complex traits such as oil yield or resistance to disease is now possible (Forster et al., 2017). Consequently, the availability and sharing of such a large amount of data is currently reshaping most of oil palm breeding strategies.

High fertilizer use in the plantation conflicts with the need to reduce the emissions of greenhouse gases in fertilizer manufacturing, transportation and application. Therefore, improved nutrient uptake efficiency is important and can be addressed by breeding for suitable root systems. A remobilization of nitrogen and micronutrients within the plants will be necessary. Prolonged root uptake and better remobilization of nutrients are targets for breeding, provided there is sufficient plasticity of these characteristics in the oil palm for increases in efficiency to be achieved (Ollivier et al., 2016).