Multi-trait analysis of gene-by-environment interactions in large-scale genetic studies.

Identifying genotype-by-environment interaction (GEI) is challenging because the GEI analysis generally has low power. Large-scale consortium-based studies are ultimately needed to achieve adequate power for identifying GEI. We introduce Multi-Trait Analysis of Gene-Environment Interactions (MTAGEI), a powerful, robust, and computationally efficient framework to test gene-environment interactions on multiple traits in large data sets, such as the UK Biobank (UKB). To facilitate the meta-analysis of GEI studies in a consortium, MTAGEI efficiently generates summary statistics of genetic associations for multiple traits under different environmental conditions and integrates the summary statistics for GEI analysis. MTAGEI enhances the power of GEI analysis by aggregating GEI signals across multiple traits and variants that would otherwise be difficult to detect individually. MTAGEI achieves robustness by combining complementary tests under a wide spectrum of genetic architectures. We demonstrate the advantages of MTAGEI over existing single-trait-based GEI tests through extensive simulation studies and the analysis of the whole exome sequencing data from the UKB.

The genetic basis of dispersal in a vertebrate metapopulation.

Dispersal affects evolutionary processes by changing population size and genetic composition, influencing the viability and persistence of populations. Investigating which mechanisms underlie variation in dispersal phenotypes and whether populations harbour adaptive potential for dispersal is crucial to understanding the eco-evolutionary dynamics of this important trait. Here, we investigate the genetic architecture of dispersal among successfully recruited individuals in an insular metapopulation of house sparrows. We use an extensive long-term individual-based ecological data set and high-density single-nucleotide polymorphism (SNP) genotypes for over 2500 individuals. We conducted a genome-wide association study (GWAS), and found a relationship between dispersal probability and a SNP located near genes known to regulate circadian rhythm, glycogenesis and exercise performance, among other functions. However, this SNP only explained 3.8% of variance, suggesting that dispersal is a polygenic trait. We then used an animal model to estimate heritable genetic variation (σA 2 ), which composes 10% of the total variation in dispersal probability. Finally, we investigated differences in σA 2 across populations occupying ecologically relevant habitat types (farm vs. non-farm) using a genetic groups animal model. We found different adaptive potentials across habitats, with higher mean breeding value, σA 2 , and heritability for the habitat presenting lower dispersal rates, suggesting also different roles of environmental variation. Our results suggest a complex genetic architecture of dispersal and demonstrate that adaptive potential may be environment dependent in key eco-evolutionary traits. The eco-evolutionary implications of such environment dependence and consequent spatial variation are likely to become ever more important with the increased fragmentation and loss of suitable habitats for many natural populations.

Environmental context of phenotypic plasticity in flowering time in sorghum and rice.

Phenotypic plasticity is an important topic in biology and evolution. However, how to generate broadly applicable insights from individual studies remains a challenge. Here, with flowering time observed from a large geographical region for sorghum and rice genetic populations, we examine the consistency of parameter estimation for reaction norms of genotypes across different subsets of environments and searched for potential strategies to inform the study design. Both sample size and environmental mean range of the subset affected the consistency. The subset with either a large range of environmental mean or a large sample size resulted in genetic parameters consistent with the overall pattern. Furthermore, high accuracy through genomic prediction was obtained for reaction norm parameters of untested genotypes using models built from tested genotypes under the subsets of environments with either a large range or a large sample size. With 1428 and 1674 simulated settings, our analyses suggested that the distribution of environmental index values of a site should be considered in designing experiments. Overall, we showed that environmental context was critical, and considerations should be given to better cover the intended range of the environmental variable. Our findings have implications for the genetic architecture of complex traits, plant-environment interaction, and climate adaptation.

Parental Nurturance Moderates the Etiology of Youth Resilience.

Parenting behaviors are among the most robust predictors of youth resilience to adversity. Critically, however, very few studies examining these effects have been genetically-informed, and none have considered parenting as an etiologic moderator of resilience. What's more, despite the multidimensionality of resilience, extant etiologic literature has largely focused on a single domain. The current study sought to fill these respective gaps in the literature by examining whether and how parental nurturance shapes the etiology of academic, social, and psychological resilience, respectively. We employed a unique sample of twins (N = 426 pairs; ages 6-11) exposed to moderate-to-severe levels of environmental adversity (i.e., family poverty, neighborhood poverty, community violence) from the Twin Study of Behavioral and Emotional Development in Children. As expected, parental nurturance was positively correlated with all forms of resilience. Extended univariate genotype-by-environment interaction models revealed that parental nurturance significantly moderated genetic influences on all three domains of resilience (academic resilience A1= -0.53, psychological resilience A1= -1.22, social resilience A1= -0.63; all p < .05), such that as parental nurturance increased, genetic influences on youth resilience decreased. Put another way, children experiencing high levels of parental nurturance were more resilient to disadvantage, regardless of their genetic predisposition towards resilience. In the absence of nurturing parenting, however, genetic influences played an outsized role in the origins of resilience. Such findings indicate that parental nurturance may serve as a malleable protective factor that increases youth resilience regardless of genetic influences.

The Garden of Forking Paths: Reinterpreting Haseman-Elston Regression for a Genotype-by-Environment Model.

Haseman-Elston regression (HE-reg) has been known as a classic tool for detecting an additive genetic variance component. However, in this study we find that HE-reg can capture GxE under certain conditions, so we derive and reinterpret the analytical solution of HE-reg. In the presence of GxE, it leads to a natural discrepancy between linkage and association results, the latter of which is not able to capture GxE if the environment is unknown. Considering linkage and association as symmetric designs, we investigate how the symmetry can and cannot hold in the absence and presence of GxE, and consequently we propose a pair of statistical tests, Symmetry Test I and Symmetry Test II, both of which can be tested using summary statistics. Test statistics, and their statistical power issues are also investigated for Symmetry Tests I and II. Increasing the number of sib pairs is important to improve statistical power for detecting GxE.

Among- and within-population variation in germination response shapes ecological resilience in the Mediterranean cliff species Brassica incana Ten.

BACKGROUND AND AIMS: Understanding how plant species respond to extreme conditions is crucial for predicting their ecological resilience under climate change. Here, we aim to forecast the ecological resilience of the Mediterranean cliff species Brassica incana (Brassicaceae) by estimating population variation in germination response under novel extreme environmental conditions. METHODS: We investigated the thermal germination responses in 14 populations of B. incana by exposing seeds to temperatures within and outside conditions experienced in their local environment. Then, we quantified among- and within-population variation in germination response to extreme temperatures, estimated genotype-by-environment interactions (G × E) and tested if population performance at extreme temperatures is explained by local climate. KEY RESULTS: We found significant among-population differences in germination response, a different level of within-population variability, and different mechanisms underlying G × E patterns. Also, populations experiencing warmer temperatures in their local environment showed a better performance at both cold and hot extremes while populations experiencing colder temperatures showed a limited ability to germinate under extreme conditions. CONCLUSIONS: Our results suggest that populations experiencing warmer temperatures in their local environment have a higher potential to face future thermal extreme conditions and their role is thus crucial to promote species ecological resilience.

Multi-location evaluation of field pea in Indian climates: eco-phenological dynamics, crop-environment relationships, and identification of mega-environments.

Characterization of crop-growing environments in relation to crop's genotypic performance is crucial to harness positive genotype-by-environment interactions (GEI) in systematic breeding programs. Given that, the study aimed to delineate the impact of diverse environments on crop phenology and yield traits of dwarf-statured field pea, pinpointing location(s) favoring higher yield and distinctiveness within breeding lines. We tested twelve field pea breeding lines across twenty locations in India, covering Central Zone (CZ), North Western Plain Zone (NWPZ), North Eastern Plain Zone (NEPZ), and Northern Hill Zone (NHZ). Across these locations, maximum and minimum temperatures during flowering (TMAXF, TMINF) and reproductive period (TMAXRP, TMINRP) ranged 18.9-28.3, 3.3-18.0, 15.0-30.8, and 7.9-22.1oC, respectively. Meanwhile, notable variations in phenological and agronomic traits (coefficient of variation) were observed: flowering (31%), days to maturity (21%), reproductive period (18%), grain yield (48%), and 100-seed weight (18%). Combined ANOVA demonstrated an oversized impact of environment (81%) on yield, while genotype and GEI effects were 2% and 14%, respectively. The variables TMINF, TMINRP, and cumulative growing degree-day showed positive correlations with yield, while extended vegetative and maturity durations negatively influenced yield (p < 0.05). Additionally, linear mixed-models and PCA results explained that instability in crop phenology had significant influence on field pea yield. Seed weight was markedly varied within the locations (9.9-20.8 g) and both higher and lower seed weights were associated with lower yields (Optimal = 17.1 g). HA-GGE biplot-based on environment focus-scaling demonstrated three mega-environments and specific locations viz. Kota (CZ), SK Nagar (CZ), Raipur (CZ), Sehore (CZ), and Pantnagar (NWPZ) as the ideal testing-environments with high efficiency in selecting new genotypes with wider adaptability. The study findings highlight distinct impact of environments on crop phenology and agronomic traits of field pea (dwarf-type), hold substantial value in designing efficient field pea (dwarf-type) breeding program at mega-environment scale.

Transgenerational effects of the maternal gestational environment on the post-natal performance of beef cattle: A reaction norm approach.

In tropical beef cattle production systems, animals are commonly raised on pastures, exposing them to potential stressors. The end of gestation typically overlaps with a dry period characterized by limited food availability. Late gestation is pivotal for fetal development, making it an ideal scenario for inter- and transgenerational effects of the maternal gestational environment. Intergenerational effects occur due to exposure during gestation, impacting the development of the embryo and its future germline. Transgenerational effects, however, extend beyond direct exposure to the subsequent generations. The objective of the present study was to verify these effects on the post-natal performance of zebu beef cattle. We extended the use of a reaction norm model to identify genetic variation in the animals' responses to transgenerational effects. The inter- and transgenerational effects were predominantly positive (-0.09% to 19.74%) for growth and reproductive traits, indicating improved animal performance on the phenotypic scale in more favourable maternal gestational environments. Additionally, these effects were more pronounced in the reproductive performance of females. On average, the ratio of direct additive genetic variances of the slope and intercept of the reaction norm ranged from 1.23% to 3.60% for direct and from 10.17% to 11.42% for maternal effects. Despite its relatively modest magnitude, this variation proved sufficient to prompt modifications in parameter estimates. The average percentage variation of direct heritability estimates ranged from 19.3% for scrotal circumference to 33.2% for yearling weight across the environmental descriptors evaluated. Genetic correlations between distant environments for the studied traits were generally high for direct effects and far from unity for maternal effects. Changes in EBV rankings of sires across different gestational environments were also observed. Due to the multifaceted nature of inter- and transgenerational effects of the maternal gestational environment on various traits of beef cattle raised under tropical pasture conditions, they should not be overlooked by producers and breeders. There were differences in the specific response of beef cattle to variations in the quality of the maternal gestational environment, which can be partially explained by transgenerational epigenetic inheritance. Adopting a reaction norm model to capture a portion of the additive variance induced by inter- or transgenerational effects could be an alternative for future research and animal genetic evaluations.

Niche construction and the environmental term of the price equation: How natural selection changes when organisms alter their environments.

Organisms construct their own environments and phenotypes through the adaptive processes of habitat choice, habitat construction, and phenotypic plasticity. We examine how these processes affect the dynamics of mean fitness change through the environmental change term of the Price Equation. This tends to be ignored in evolutionary theory, owing to the emphasis on the first term describing the effect of natural selection on mean fitness (the additive genetic variance for fitness of Fisher's Fundamental Theorem). Using population genetic models and the Price Equation, we show how adaptive niche constructing traits favorably alter the distribution of environments that organisms encounter and thereby increase population mean fitness. Because niche-constructing traits increase the frequency of higher-fitness environments, selection favors their evolution. Furthermore, their alteration of the actual or experienced environmental distribution creates selective feedback between niche constructing traits and other traits, especially those with genotype-by-environment interaction for fitness. By altering the distribution of experienced environments, niche constructing traits can increase the additive genetic variance for such traits. This effect accelerates the process of overall adaption to the niche-constructed environmental distribution and can contribute to the rapid refinement of alternative phenotypic adaptations to different environments. Our findings suggest that evolutionary biologists revisit and reevaluate the environmental term of the Price Equation: owing to adaptive niche construction, it contributes directly to positive change in mean fitness; its magnitude can be comparable to that of natural selection; and, when there is fitness G × E, it increases the additive genetic variance for fitness, the much-celebrated first term.

Predicting plasticity of rosette growth and metabolic fluxes in Arabidopsis thaliana.

Plants can rapidly mitigate the effects of suboptimal growth environments by phenotypic plasticity of fitness-traits. While genetic variation for phenotypic plasticity offers the means for breeding climate-resilient crop lines, accurate genomic prediction models for plasticity of fitness-related traits are still lacking. Here, we employed condition- and accession-specific metabolic models for 67 Arabidopsis thaliana accessions to dissect and predict plasticity of rosette growth to changes in nitrogen availability. We showed that specific reactions in photorespiration, linking carbon and nitrogen metabolism, as well as key pathways of central carbon metabolism exhibited substantial genetic variation for flux plasticity. We also demonstrated that, in comparison with a genomic prediction model for fresh weight (FW), genomic prediction of growth plasticity improves the predictability of FW under low nitrogen by 58.9% and by additional 15.4% when further integrating data on plasticity of metabolic fluxes. Therefore, the combination of metabolic and statistical modeling provides a stepping stone in understanding the molecular mechanisms and improving the predictability of plasticity for fitness-related traits.

Plasticity in growth is genetically variable and highly conserved across spatial scales in a Mediterranean pine.

Phenotypic plasticity is a main mechanism for sessile organisms to cope with changing environments. Plasticity is genetically based and can evolve under natural selection so that populations within a species show distinct phenotypic responses to environment. An important question that remains elusive is whether the intraspecific variation in plasticity at different spatial scales is independent from each other. To test whether variation in plasticity to macro- and micro-environmental variation is related among each other, we used growth data of 25 Pinus pinaster populations established in seven field common gardens in NW Spain. Phenotypic plasticity to macro-environmental variation was estimated across test sites while plasticity to micro-environmental variation was estimated by using semivariography and kriging for modeling within-site heterogeneity. We provide empirical evidence of among-population variation in the magnitude of plastic responses to both micro- and macro-environmental variation. Importantly, we found that such responses were positively correlated across spatial scales. Selection for plasticity at one scale of environmental variation may impact the expression of plasticity at other scales, having important consequences on the ability of populations to buffer climate change. These results improve our understanding of the ecological drivers underlying the expression of phenotypic plasticity.

Integrating biophysical crop growth models and whole genome prediction for their mutual benefit: a case study in wheat phenology.

Running crop growth models (CGM) coupled with whole genome prediction (WGP) as a CGM-WGP model introduces environmental information to WGP and genomic relatedness information to the genotype-specific parameters modelled through CGMs. Previous studies have primarily used CGM-WGP to infer prediction accuracy without exploring its potential to enhance CGM and WGP. Here, we implemented a heading and maturity date wheat phenology model within a CGM-WGP framework and compared it with CGM and WGP. The CGM-WGP resulted in more heritable genotype-specific parameters with more biologically realistic correlation structures between genotype-specific parameters and phenology traits compared with CGM-modelled genotype-specific parameters that reflected the correlation of measured phenotypes. Another advantage of CGM-WGP is the ability to infer accurate prediction with much smaller and less diverse reference data compared with that required for CGM. A genome-wide association analysis linked the genotype-specific parameters from the CGM-WGP model to nine significant phenology loci including Vrn-A1 and the three PPD1 genes, which were not detected for CGM-modelled genotype-specific parameters. Selection on genotype-specific parameters could be simpler than on observed phenotypes. For example, thermal time traits are theoretically more independent candidates, compared with the highly correlated heading and maturity dates, which could be used to achieve an environment-specific optimal flowering period. CGM-WGP combines the advantages of CGM and WGP to predict more accurate phenotypes for new genotypes under alternative or future environmental conditions.

Using genomic prediction with crop growth models enables the prediction of associated traits in wheat.

Crop growth models (CGM) can predict the performance of a cultivar in untested environments by sampling genotype-specific parameters. As they cannot predict the performance of new cultivars, it has been proposed to integrate CGMs with whole genome prediction (WGP) to combine the benefits of both models. Here, we used a CGM-WGP model to predict the performance of new wheat (Triticum aestivum) genotypes. The CGM was designed to predict phenology, nitrogen, and biomass traits. The CGM-WGP model simulated more heritable GSPs compared with the CGM and gave smaller errors for the observed phenotypes. The WGP model performed better when predicting yield, grain number, and grain protein content, but showed comparable performance to the CGM-WGP model for heading and physiological maturity dates. However, the CGM-WGP model was able to predict unobserved traits (for which there were no phenotypic records in the reference population). The CGM-WGP model also showed superior performance when predicting unrelated individuals that clustered separately from the reference population. Our results demonstrate new advantages for CGM-WGP modelling and suggest future efforts should focus on calibrating CGM-WGP models using high-throughput phenotypic measures that are cheaper and less laborious to collect.

A warmer environment can reduce sociability in an ectotherm.

The costs and benefits of being social vary with environmental conditions, so individuals must weigh the balance between these trade-offs in response to changes in the environment. Temperature is a salient environmental factor that may play a key role in altering the costs and benefits of sociality through its effects on food availability, predator abundance, and other ecological parameters. In ectotherms, changes in temperature also have direct effects on physiological traits linked to social behaviour, such as metabolic rate and locomotor performance. In light of climate change, it is therefore important to understand the potential effects of temperature on sociality. Here, we took the advantage of a 'natural experiment' of threespine sticklebacks from contrasting thermal environments in Iceland: geothermally warmed water bodies (warm habitats) and adjacent ambient-temperature water bodies (cold habitats) that were either linked (sympatric) or physically distinct (allopatric). We first measured the sociability of wild-caught adult fish from warm and cold habitats after acclimation to a low and a high temperature. At both acclimation temperatures, fish from the allopatric warm habitat were less social than those from the allopatric cold habitat, whereas fish from sympatric warm and cold habitats showed no differences in sociability. To determine whether differences in sociability between thermal habitats in the allopatric population were heritable, we used a common garden breeding design where individuals from the warm and the cold habitat were reared at a low or high temperature for two generations. We found that sociability was indeed heritable but also influenced by rearing temperature, suggesting that thermal conditions during early life can play an important role in influencing social behaviour in adulthood. By providing the first evidence for a causal effect of rearing temperature on social behaviour, our study provides novel insights into how a warming world may influence sociality in animal populations.

Bias in Gene-by-Environment Interaction Effects with Sum Scores; An Application to Well-being Phenotypes.

In the current study, we investigated the influence of using skewed sum scores on estimated gene-by-environment interaction effects (GxE) for life satisfaction and happiness with perceived social support. To this end, we analyzed item-level data from a large adult twin sample (Ns between 3610 and 11,305) of the Netherlands Twin Register. Item response theory (IRT) models were incorporated in unmeasured (univariate) GxE models, and measured GxE models (with social support as moderator). We found that skewness introduced spurious GxE effects, with the largest effect for the most skewed variable (social support). Finally, in the IRT model for life satisfaction, but not for happiness, heritability estimates decreased with higher social support, while this was not observed when analyzing sum scores. Together, our results indicate that IRT can be used to address psychometric issues related to the use of sum scores, especially in the context of GxE, for complex traits like well-being.

Genome-wide mapping of regulatory variants for temperature- and salinity-adaptive genes reveals genetic basis of genotype-by-environment interaction in Crassostrea ariakensis.

Regulatory variants in gene expression serve as bridges linking genetic variation and phenotypic plasticity. Environmental conditions typically influence the effects of regulatory variants on phenotypic plasticity; however, such genotype-by-environment interactions (G × E) are poorly understood. This study aimed to investigate the genetic basis of G × E in estuarine oyster (Crassostrea ariakensis), which is an important model animal for studying environmental adaption owing to its high plasticity and large intraspecific divergence. Genome-wide mapping of expression quantitative trait loci (eQTLs) for 23 environmental adaptive genes was performed for 256 estuarine oysters. We identified 1194 eQTL single nucleotide polymorphisms (eSNPs), including 433 cis-eSNPs in four genes and 722 trans-eSNPs in eight genes. The expression variation explanation of cis-eSNPs (9.95%) was significantly higher than that of trans-eSNPs (9.15%). We specifically showed cis- and trans-eSNPs with high linkage disequilibrium (LD) for Traf7, Slc6a5, Ggt, and Dap3. For example, we identified a cis-regulatory LD block containing 68 cis-eSNP and a trans-regulatory LD block, including 20 trans-eSNPs in Traf7. A high proportion (85%) of 40 vital eSNPs exhibited significant G × E effects. We identified crossing and nonparallel interactions of G × E, with the tag cis-eSNPs of Baat and Slc6a5 as representatives. Our results indicated that cis-eQTLs are highly conserved. This study provides insights into the understanding of adaptive evolutionary mechanisms and phenotypic response prediction to variable environments, as well as the genetic improvement for superior adaptive traits for genetic resource conservation and aquaculture.

Evaluation of the Influence of Genetic and Environmental Factors on the Ephedrine Alkaloids Content of Ephedra sinica.

Ephedra herb, a dried terrestrial stem of Ephedra sinica, is used in traditional Japanese medicine (Kampo) and Chinese medicine to treat the common cold, headaches, bronchial asthma, and nasal inflammation. E. sinica predominantly contains two ephedrine alkaloids-(-)-ephedrine and (+)-pseudoephedrine-which are crucial for its medicinal effects. This study aimed to reveal the influence of genetic and environmental factors on ephedrine alkaloids content using statistical genetic analyses. To evaluate the influence of genetic factors on ephedrine alkaloids content, 25 clonal lines were cultivated in Ibaraki and the broad-sense heritability of the traits was estimated. The heritabilities of (-)-ephedrine, (+)-pseudoephedrine, and "total alkaloids" (TA) content were 0.871, 0.969, and 0.865, respectively. The heritabilities of ephedrine alkaloids content were high. To evaluate the influence of environmental factors on ephedrine alkaloids content, four clonal lines which have different genotypes were cultivated in three locations (Ibaraki, Shizuoka, and Yamanashi prefectures). The effects of genotype (G), location (L), and genotype by environment (G × E) interactions on ephedrine alkaloids content were found to be significant (p < 0.05) by two-way ANOVA, and, in particular, the genotypic effects were found to be the largest. Our results indicate that the ephedrine alkaloids content in E. sinica is under relatively strong genetic control and remains stable under various environments. These findings suggest that E. sinica with a higher and stable ephedrine alkaloids content could be cultivated in different locations through selective breeding.

Heat stress on breeding value prediction for milk yield and composition of a Brazilian Holstein cattle population.

Due to the high milk production of Holstein cows, many countries have chosen to import semen to improve local dairy herds. This strategy would be more effective if this semen was used in the same environment conditions in which the bulls were selected. If the effect of genotype by environment (G × E) interaction is not considered, the estimated breeding values (EBVs) may vary, potentially reducing the selection response. We evaluate the impact of heat stress on selection for milk yield and composition of Holstein cows using random regression models. To verify the interference of heat stress in milk yield (MY) and composition traits (fat, protein, total saturated, and total unsaturated fatty acids content in milk), temperature-humidity index (THI) on test-day milk records was used. The threshold value to divide the environments using test-day information from Brazilian Holstein cows was 72 units of THI, i.e., < 72 represented no heat stress and > 72 represented heat stress. Legendre polynomials of second-order (Leg 2) model and two lactation points (33 and 122 DIM) were used to estimate heritabilities and EBVs for five important dairy traits. The heritabilities of milk components and fatty acids were low (0.09-0.29), regardless of lactation period and degree of heat stress, with the exception of protein content (0.30-0.35). Fat content was the only milk component that was reduced according to the degree of heat stress and lactation period. The EBVs tended to decrease in heat stress conditions, thus animals with high genetic potential demonstrated evidence of G × E interaction. However, acclimatization of dairy cows to heat stress in the farm production systems may have been responsible for the low differences among genetic parameters and EBVs with and without heat stress found in this study.

Influence of contrasting cultivation altitudes on the physicochemical, digestive, and functional properties of four Musa starches produced in Cameroon.

BACKGROUND: Bananas and plantains are important food sources for many people in the world. Their high starch content places them among the highest energy providers. This study aimed to determine the effects of altitude on banana starch properties in Cameroon. A dessert banana, a cooking banana, a plantain cultivar, and a plantain-like hybrid were grown at low and high altitudes (respectively at 80 m and 1300 m above sea level). RESULTS: Starch analyses showed an increase in moisture and pH values against a drop in total titratable acidity and dry matter content with respect to altitude. Amylose content, as well as water absorption capacity, oil absorption capacity and syneresis of high-altitude plantain and plantain-like hybrid, were significantly higher. Starch digestibility was low and ranged between 13.4% and 37.9% after 2 h of incubation. High-altitude plantain starches contained more amylose and were more resistant to enzymatic hydrolysis. CONCLUSION: Starches from CARBAP K74 and Kelong mekintu, grown at high altitude, showed good water and oil absorption capacities, low digestibility, and high resistance. The adequate properties of these banana starches predispose them for use as thickeners and gelling agents as well as ingredients for the formulation of low-calorie foods. This study highlights the importance of altitude when discussing banana and plantain starch properties. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Varietal and environmental influences on organoleptic and cooking quality of water yam (Dioscorea alata) landraces.

BACKGROUND: Yam is a major staple food that provides both energy (starch) and bioactive compounds. However, there is a lack of knowledge on its cooking quality. We have determined the cooking quality of five varieties of water yam (among those most appreciated by consumers), when they were steamed or boiled. The yams were grown in two contrasting locations with regard to pedoclimatic conditions. RESULTS: Ratio of length to mean circumference of the tuber, difficulty to peel, cooking time, color attributes, hardness of steamed pulp, and dry matter (DM) and starch contents significantly varied among varieties. Cooking time and hardness of the cooked pulp, either steamed or boiled, were higher for tubers grown at the drier location, with vertisols, than at the rainy one, with a ferralitic soil. The raw pulp was richer in starch at the rainy location. We found no correlation between either textural properties or DM and the cooking time. A slight (r = 0.44) but significant correlation was recorded between the DM of the raw pulp and the hardness of the steamed product. CONCLUSION: We propose a comprehensive multicriteria approach for determination of yam cooking quality, textural properties, color attributes and chemical composition, along with varietal and environmental influences. This approach takes into consideration the complexity of food quality, allows a better understanding of its determinants and provides a basis for useful guidelines for breeders. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.