Genomic selection (GS) in plant breeding is explored as a promising tool to solve the problems related to the biotic and abiotic threats. Polyploid plants like bananas (Musa spp.) face the problem of drought and black sigatoka disease (BSD) that restrict their production. The conventional plant breeding is experiencing difficulties, particularly phenotyping costs and long generation interval. To overcome these difficulties, GS in plant breeding is explored as an alternative with a great potential for reducing costs and time in selection process. So far, GS does not have the same success in polyploid plants as with diploid plants because of the complexity of their genome. In this review, we present the main constraints to the application of GS in polyploid plants and the prospects for overcoming these constraints. Particular emphasis is placed on breeding for BSD and drought—two major threats to banana production—used in this review as a model of polyploid plant. It emerges that the difficulty in obtaining markers of good quality in polyploids is the first challenge of GS on polyploid plants, because the main tools used were developed for diploid species. In addition to that, there is a big challenge of mastering genetic interactions such as dominance and epistasis effects as well as the genotype by environment interaction, which are very common in polyploid plants. To get around these challenges, we have presented bioinformatics tools, as well as artificial intelligence approaches, including machine learning. Furthermore, a scheme for applying GS to banana for BSD and drought has been proposed. This review is of paramount impact for breeding programs that seek to reduce the selection cycle of polyploids despite the complexity of their genome.

Introduction: The cochineal scale insect scientifically known as Dactylopius opuntia was first introduced as biological control methods in regions where cactus was considered an invasive weed. Today, D. opuntiae insects is seen as one of the most important limitations to edible cactus production. In the present study, a meta-analysis was performed to assess the effectiveness of various control methods against D. opuntiae and the associated key factors. Methods: The Artificial Intelligence (AI)-based tools were employed to screen scientific production reporting the effectiveness of the fight against D. opuntiae , while robust variance estimation (RVE) and proportional meta-regressions were applied to deal with the abundance of effect sizes within a single study and perform subgroup meta-analysis respectively. Results: The effect sizes were pooled to 4.19 ± 0.08, I ² = 99.99%, for the nymphs and to 3.99 ± 3 0.09 I ² = 99.99%, for the adult insects. The proportional meta-analysis pooled the proportion of nymph’s mortality by 63%, I ² = 99.1%, and adult mortality by 74%, I ² = 98.6%. In subgroup analysis, a significant difference (p < 0.001) was observed among study locations (countries) and trial durations (times), suggesting that these factors can influence the effectiveness of the fight against Dactylopius pest. Importantly, non-chemical control means yielded higher proportion of adult cochineal mortality compared to chemical method. Discussion: Finally, the scientific information obtained in the present study provides valuable insight for decision-makers towards effective, and sustainable control of white cochineal pest. Therefore, consideration of environmental influence (location) and the duration of treatments in this control is recommended.

Black sigatoka disease (BSD) is the most important foliar threat in banana production, and breeding efforts against it should take advantage of genomic selection (GS), which has become one of the most explored tools to increase genetic gain, save time, and reduce selection costs. To evaluate the potential of GS in banana for BSD, 210 triploid accessions were obtained from the African Banana and Plantain Research Center to constitute a training population. The variability in the population was assessed at the phenotypic level using BSD- and agronomic-related traits and at the molecular level using single-nucleotide polymorphisms (SNPs). The analysis of variance showed a significant difference between accessions for almost all traits measured, although at the genomic group level, there was no significant difference for BSD-related traits. The index of non-spotted leaves among accessions ranged from 0.11 to 0.8. The accessions screening in controlled conditions confirmed the susceptibility of all genomic groups to BSD. The principal components analysis with phenotypic data revealed no clear diversity partition of the population. However, the structure analysis and the hierarchical clustering analysis with SNPs grouped the population into four clusters and two subpopulations, respectively. The field and laboratory screening of the banana GS training population confirmed that all genomic groups are susceptible to BSD but did not reveal any genetic structure, whereas SNP markers exhibited clear genetic structure and provided useful information in the perspective of applying GS.

Apate terebrans (Pallas, 1772) is a wood borer that considerably limits the productivity of cashew trees ( Anacardium occidentale Linnaeus, 1753) in West Africa, particularly in Côte d’Ivoire. Systemic chemical control is the main method of controlling this pest. This study aimed to identifying if a cashew accession is less susceptible to A. terebrans . Specifically, infestation rates, agro-morphological and biochemical characteristics of the two most grown cashew accessions, including ‘yellow apple (YA)’ and ‘red apple (RA)’ were assessed under natural conditions. Apate terebrans infestations were assessed monthly on 1924 cashew plants during two production seasons (i.e. 24 months of sampling) in the north-east of Côte d'Ivoire. Agro-morphological characterization of the fruit and analyses of primary compounds and secondary metabolites of cashew bark were carried out. The occurrence of the YA accession in the study sites (54–57%) was significantly higher than RA accession (43–46%) ( P < 0.001). The mean cashew nut weight of accession YA (6.62 ± 1.23 g) was significantly higher than that of accession RA (6.11 ± 1.49 g) ( P < 0.001). However, the average infestation rate of accession RA (4.18%) was significantly lower than that of accession YA (6.58%) ( P = 0.02). Accession RA was lower in primary compounds, but its content of secondary metabolites, polyphenols, flavonoids and tannins was significantly higher than YA accession ( P < 0.01). By highlighting the variability in physico-biochemical characteristics and susceptibility to A. terebrans of RA and YA cashew accessions, this study provides avenues for future varietal selection with a view to sustainably improving cashew tree productivity. Significance of the study: What is already known on this subject? In West Africa, Apate terebrans considerably affects the productivity of cashew trees, which are a crop of socio-economic interest. Several cashew accessions coexist in the orchards, but little is known about their physical and biochemical characteristics and their susceptibility to insect pests. What are the new findings? The two cashew accessions studied, the ‘yellow apple’ and the ‘red apple’, showed significant differences in their physical and biochemical characteristics and in their susceptibility to A. terebrans . The fruits of the ‘yellow apple (YA)’ accession were the largest, with a higher weight. This accession was the most abundant in the orchards. However, the ‘YA’ accession was the least attacked by A. terebrans . These levels of primary compounds (nutrients for the pest) and secondary metabolites (toxins against the pest) were lower and higher, respectively. What are the expected impacts on horticulture? This knowledge will help inform decision-making for developing improved pest-resistant cashew varieties, with the aim of improving cashew tree productivity.