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The multivariate skew-normal family of distributions is a flexible class of probability models that includes the multivariate normal distribution as a special case. Two procedures for testing that a multivariate random sample comes from the multivariate skew-normal distribution are proposed here based on the estimated canonical form. Canonical data are transformed into approximately multivariate normal observations and then a multivariate version of the Shapiro-Wilk test is used for testing multivariate normality. Critical values for the tests are approximated without using parametric bootstrap. Monte Carlo simulation results provide evidence that the nominal test level is preserved, in general, under the considered settings. The simulation results also indicate that these tests are in general more powerful than existing tests for the same problem versus the studied alternatives.

Genomic selection (GS) has become a tool for selecting candidates in plant and animal breeding programs. In the case of quantitative traits, it is common to assume that the distribution of the response variable can be approximated by a normal distribution. However, it is known that the selection process leads to skewed distributions. There is vast statistical literature on skewed distributions, but the skew normal distribution is of particular interest in this research. This distribution includes a third parameter that drives the skewness, so that it generalizes the normal distribution. We propose an extension of the Bayesian whole-genome regression to skew normal distribution data in the context of GS applications, where usually the number of predictors vastly exceeds the sample size. However, it can also be applied when the number of predictors is smaller than the sample size. We used a stochastic representation of a skew normal random variable, which allows the implementation of standard Markov Chain Monte Carlo (MCMC) techniques to efficiently fit the proposed model. The predictive ability and goodness of fit of the proposed model were evaluated using simulated and real data, and the results were compared to those obtained by the Bayesian Ridge Regression model. Results indicate that the proposed model has a better fit and is as good as the conventional Bayesian Ridge Regression model for prediction, based on the DIC criterion and cross-validation, respectively. A computing program coded in the R statistical package and C programming language to fit the proposed model is available as supplementary material.

Key message A new genomic model that incorporates genotype x environment interaction gave increased prediction accuracy of untested hybrid response for traits such as percent starch content, percent dry matter content and silage yield of maize hybrids. The prediction of hybrid performance (HP) is very important in agricultural breeding programs. In plant breeding, multi-environment trials play an important role in the selection of important traits, such as stability across environments, grain yield and pest resistance. Environmental conditions modulate gene expression causing genotype x environment interaction (G x E), such that the estimated genetic correlations of the performance of individual lines across environments summarize the joint action of genes and environmental conditions. This article proposes a genomic statistical model that incorporates G x E for general and specific combining ability for predicting the performance of hybrids in environments. The proposed model can also be applied to any other hybrid species with distinct parental pools. In this study, we evaluated the predictive ability of two HP prediction models using a cross-validation approach applied in extensive maize hybrid data, comprising 2724 hybrids derived from 507 dent lines and 24 flint lines, which were evaluated for three traits in 58 environments over 12 years; analyses were performed for each year. On average, genomic models that include the interaction of general and specific combining ability with environments have greater predictive ability than genomic models without interaction with environments (ranging from 12 to 22%, depending on the trait). We concluded that including G x E in the prediction of untested maize hybrids increases the accuracy of genomic models.

The aboveground contributions of mangroves to global carbon sequestration reinforce the need to estimate biomass in these systems. The objective was to determine the aboveground biomass storage and quantify the carbon and CO2e content in Rhizophora mangle, Avicennia germinans, and Laguncularia racemosa present in southeastern Mexico. Based on the Forest Protocol for Mexico Version 2.0 methodology, published by Climate Action Reserve, 130 circular plots were randomly selected and established in an area of 930 ha of mangrove vegetation, and the aboveground biomass and stored carbon were determined. The mangrove had a density of 3515 ± 428.5 individuals per hectare. The aboveground biomass of the three species was 120.5 Mg ha−1. The biomass of L. racemosa was 99.5 Mg ha−1, which represents 82.6% of the total biomass. The biomass of R. mangle was 20.33 Mg ha−1, and that of A. germinans was 0.32 Mg ha−1. The total carbon retained in the trees was 60.25 Mg C ha−1 and 221.1 Mg CO2e ha−1. Laguncularia racemosa generated the highest contributions of CO2e. The area of mangroves accumulated 112,065 Mg of aboveground biomass. The carbon contained in this biomass corresponds to 205,623 Mg CO2e. This mangrove contributes to mitigating the effects of climate change globally through the reduction in greenhouse gases.

Tropical soils contain a high diversity of arbuscular mycorrhizal fungi (AMF), which play an essential role in plant nutrition and resilience. This diversity can vary depending on soil properties, the vegetation, and management practices. Therefore, characterising the abundance and diversity of AMF associated with culturally important plant species as well as their relationship with the edaphic properties of the soils in which they are found is crucial for understanding, conserving, and optimising plant productivity. This study aimed to characterise and compare the diversity and composition of AMF in the rhizosphere of Capsicum annuum var. glabriusculum (Dunal) Heiser and Pickersgill in tropical soils with varying physicochemical properties. Soil and rhizosphere root samples were collected from chili plants at 10 sites: six sites on Acrisols and four on Fluvisols. The AMF were identified based on spore morphology; the mycorrhizal colonisation was assessed in stained roots using optical microscopy, and the fungal diversity was analysed using Hill numbers (q₀, q₁, and q₂). Sampling coverage was 100%, with increases in q₀, q₁ and q₂ of 35.2%, 63.13% and 76.19%, respectively, in Acrisols compared to Fluvisols. Twenty-three species and morphospecies belonging to six families and seven genera were recorded; Acaulospora was the most diverse genus, and Glomus was the most abundant, with a relative abundance of up to 10%. The following species were found in both soil types: Acaulospora mellea, Funneliformis geosporum, Glomus sp.2, Glomus sp.3 and Rhizoglomus clarus. Total colonisation ranged from 90-100% in Acrisols to 80-87% in Fluvisols. In Acrisols, hyphae predominated in association with soil organic carbon, N, and B contents and the C/N ratio. In Fluvisols, arbuscules predominated in association with a neutral pH, CEC and Ca, P, Cu and silt contents. Evaluating the diversity of AMF in the rhizosphere of this chili enabled Acaulospora tuberculata to be recorded for the first time in Acrisols, thereby expanding the mycorrhizal inventory in humid tropical soils.

Microbial toxicity tests in the rhizosphere play an important role in the risk assessment and phytoremediation of chemical compounds in the environment. Tests for the inhibition of nodule number (NN), Rhizobia in the rhizosphere (RhR), Rhizobium in nodules (RhN) and arbuscular mycorrhizal fungi (AMFs) are important to evaluate the toxicity as well as the removal of total petroleum hydrocarbons (TPHs), 15 linear alkanes (LAs), and total linear alkanes (TLAs). The inhibition and removal was evaluated at 60 (vegetative stage, VS) and 154 days (reproductive stage, RS) of the life cycle of Crotalaria incana and Crotalaria pallida in soil with four doses of CRO (3, 15, 30, and 45 g/kg) plus a control (16 treatments). Results indicated that RhN and five structures of the AMFs present an index of toxicity (IT < 1), and the microbiological variable is inhibited by the CRO. RhR exhibits a hormesis index (IT > 1) that is stimulated by the CRO in the VS and RS for C. incana and C. pallida. The highest removal of TPHs (77%) was in the rhizosphere of C. incana in the RS with 45 g/kg of CRO. C. pallida removed the greatest amount of TLA (91%). There was a positive correlation between the RhR and the removal of TPHs, TLA, and LAs (higher molecular weight). It could be argued that symbiotic microorganisms are significant for use in toxicity testing, and the rhizosphere of C. incana and C. pallida can be used for the phytoremediation of HTPs and ALs in loamy-clay soil contaminated with CRO.

This study was carried out to evaluate the yield and quality of pineapple fruits of the cultivars MD2, Smooth Cayenne, and Cabezona from plants treated with 2‐(3‐chlorophenoxy) propionic acid (CPA) in the humid tropics of Mexico with respect to three planting dates and two planting densities. The experimental design used was a scheme in sub‐subdivided plots with four replications. The pineapple cultivars were established on three planting dates (February 28, April 28, and June 28, 2022) at two planting densities, that is, those typically used at the regional level (Density 1: MD2 and Smooth Cayenne, 36,000 plants ha −1 ; Cabezona, 26,500 plants ha −1 ), and an increase of 28% in the number of plants planted in Density 1 for each cultivar (Density 2). For floral inhibition, 120 g CPA ha −1 was applied at each density and divided into three applications every 10 days beginning on October 20, 2022. The results revealed that the fruit yield and concentration of total flavonoids were not affected by the planting date, but the fruit/crown ratio, pH, °Brix, percentage of citric acid, maturity index, and total polyphenol concentration (TPC) were. The planting density significantly affected the yield, pH, and maturity index. The yield of the cultivars in Density 2 was 33% higher than that in Density 1, even though the fruits weighed 3.5% less and exhibited decreased °Brix and maturity index values. The fruits harvested from October to November (planting date June 28) presented the highest TPC (89.76 mg 100 g FF −1 ). Among the cultivars, MD2 and Cabezona presented the highest TPC. It is concluded that it is possible to produce pineapples in seasons of product shortage by modifying the dates and planting density without affecting the quality of the product.

The standardized methods used in carbon markets require measurement of the biomass and carbon stored in trees, which can be quantified through allometric equations. The objective of this study was to analyze aboveground biomass estimates with allometric models in three mangrove species and compare them with those used by the Climate Action Reserve (CAR) standard. The mangrove forest in Tabasco, Mexico, was certified with the Forest Protocol for Mexico Version 2.0 (FPM) of the CAR standard. Allometric equations for mangrove species were reviewed to determine the most suitable equation for the calculation of biomass. The predictions of the allometric equations of the FPM were analyzed with data from Tabasco from the National Forest and Soil Inventory 2015–2020, and the percentages of trees within the ranges of diameters of the FPM equations were determined. The FPM equations generated higher biomass values for Rhizophora mangle and lower values for Avicennia germinans than the seven equations with which they were compared. In the mangrove swamp of Ejido Úrsulo Galván, Tabasco, 81.8% of the biomass of A. germinans, 34.4% of Laguncularia racemosa and 24.0% of R. mangle were within the diameter range of the FPM equations, and in Tabasco, 28.5% of A. germinans, 16.7% of L. racemosa and 5.7% of R. mangle were within the diameter range. For A. germinans and R. mangle, we recommend using the equation that considers greater maximum diameters. The allometric equations of the FPM do not adequately predict a large percentage of the biomass.

This study evaluated the effect of crude oil (CO) on plant height, number of total leaves, and basal diameter for 27 weeks, and at week 27 on leaf area, number of total roots, root length, root dry matter, aerial dry matter, bacterial population, actinomycetes, arbuscular mycorrhizal fungy (AMF), and total petroleum hydrocarbons (TPH) removal to propose indices as a basis for toxicity protocols and phytoremediation technologies using Jatropha curcas L. A microtunnel experiment was established for 27 weeks to evaluate the effect of seven doses of oil on the plant. CO inhibited the height and number of leaves, a longer time in the adaptation phase and a shorter time in the linear phase, compared to the control. The basal diameter showed adaptation in the linear phase in all treatments and was stimulated by the first four doses of CO at weeks 19 to 27. Plant height, total leaves, and dry matter, at week 27, were inhibited by CO, with relative toxicity indexes < 1, but leaf area, basal diameter, total roots, and root length were stimulated, with RTI ≥ 1. The population of heterotrophic and hydrocarbonoclastic bacteria, hydrocarbonoclastic fungi, and AMF were stimulated by CO, but the only highly significant positive correlation was between TPH removal and the percentage of hyphae, arbuscules, vesicles, and AMF. The highest removal was in soil with 4 g/kg CO. We conclude that J. curcas is adapted to low oil concentrations. We suggest its use in toxicity and phytoremediation protocols of clay soil contaminated with CO in the Mexican humid tropics.

Secondary metabolites of Capsicum spp. have biological activity, which can be modified by external factors as the amount of incident light and soil water availability during crop growing, and by internal factors as fruit ripeness level. The study aim was to determine by HPLC method the phytochemical profile of C. annuum L. var. glabriusculum (Dunal) Heiser & Pickersgill (AMA and GAR genotypes) and C. frutescens L. (PIP genotype) grown under open sky and 70% shade during dry and rainy harvest season. Phytochemicals were affected by genotype, light level, harvest season, and fruit ripeness level. Phytochemicals number changed among genotypes: PIP > AMA> GAR. In immature fruits AMA (4.74 mg [g.sub.-1]) and GAR (3.83 mg [g.sub.-1]) had highest capsaicin content; and PIP (0.43 [micro]g [g.sub.-1]), AMA (0.18 [micro]g [g.sub.-1]) and GAR (0.14 [micro]g [g.sub.-1]) in lutein content in all harvest seasons and light level conditions studied. In mature fruits, PIP had the highest capsaicin (5.77 mg [g.sub.-1]) and [beta]-carotene (0.45 [micro]g [g.sub.-1]) content. Gallic and syringic acids were major constituents of phenolics acids, and quercetin and rutin for flavonoids. Mature and immature fruits from 70% shade showed the quercetin highest content (108.4-160.02 [micro]g [g.sub.-1]), increasing during dry season (180.9-1368.6 [micro]g [g.sub.-1]). Gallic acid (789.3-1076.7 [micro]g [g.sub.-1]) and rutin (114.0 [micro]g [g.sub.-1]) increased in AMA immature fruits when grown under open sky. Ferulic acid was not detected in GAR under any of the conditions studied. In AMA, ferulic, protocatechuic and p-hydroxybenzoic acids were detected only in rainy season fruits in both light levels. The harvest season and shading level of these Capsicum spp. should be considered when evaluating the biological activity of chili peppers fruits extracts in tropical crops.