Sweet potato (Ipomoea batatas L.) genotype selection using advanced indices and statistical models: A multi-year approach.

In Bangladesh, sweet potato holds the fourth position as a crucial carbohydrate source, trailing rice, wheat, and potato. However, locally grown sweet potato varieties often display limited stability and yield. To tackle this challenge, diverse selection methods and statistical models were utilized to pinpoint sweet potato genotypes showcasing both stability and superior yield and quality traits. In the initial two years, multiple selection methods were employed to narrow down the collections based on preferences for yield and its contributing traits. Subsequently, a multi-environment trial (MET) was conducted in the following year to pinpoint superior and stable genotypes with desirable yield and quality characteristics. An integrated approach involving the Multi-Trait Genotype Ideotype Distance Index (MGIDI), Factor Analysis and Ideotype-Design (FAI-BLUP), and Smith-Hazel Index (SH) led to the identification of 71 superior sweet potato genotypes out of a total of 351 in the initial growing season. In the subsequent season, the MGIDI selection index was applied to the 71 genotypes, resulting in the selection of 11 top-performing genotypes. This selection process was complemented by a detailed analysis of the strengths and weaknesses of the selected genotypes. In the MET, the mixed effect model, specifically the linear mixed model (LMM), identified significant genotypic and genotype-environment interaction (GEI) variances. This points to elevated heritability and selection accuracy, ultimately boosting the model's reliability. By combining the strengths of LMM and additive main effects and multiplicative interaction (AMMI), the best linear unbiased prediction (BLUP) index identified H20 as the top-performing genotype for marketable root yield (MRY), H37 for dry weight of root (DW), H8 for beta carotene (BC) and H41 for vitamin c (VC). These genotypes surpassed the overall average in the WAAS index. For simultaneous stability and high performance, the WAASBY index selected H37 for MRY, H6 for DW, H61 for BC, and H3 for VC. Finally, genotypes H3 and H20 were selected using multi-trait stability index (MTSI), as they possessed high performance and stability. Based on the selection sense, the objective has been achieved with regards to the trait MRW, which serves as a major criterion for a superior variety of sweet potato.

Automated measures of vocal interactions and engagement in inclusive preschool classrooms.

Classroom engagement plays a crucial role in preschoolers' development, yet the correlates of engagement, especially among children with autism spectrum disorder (ASD) and developmental delays (DD), remains unknown. This study examines levels of engagement with classroom social partners and tasks among children in three groups ASD, DD, and typical development (TD). Here, we asked whether children's vocal interactions (vocalizations to and from peers and teachers) were associated with their classroom engagement with social partners (peers and teachers) and with tasks, and whether the association between classroom engagement and vocal interactions differed between children in the ASD group and their peers in the DD and TD groups. Automated measures of vocalizations and location quantified children's vocal interactions with peers and teachers over the course of the school year. Automated location and vocalization data were used to capture both (1) children's vocal output to specific peers and teachers, and (2) the vocal input they received from those peers and teachers. Participants were 72 3-5-year-olds (Mage = 48.6 months, SD = 7.0, 43% girls) and their teachers. Children in the ASD group displayed lower engagement with peers, teachers, and tasks than children in the TD group; they also showed lower engagement with peers than children in the DD group. Overall, children's own vocalizations were positively associated with engagement with social partners. Thus, although children in the ASD group tend to have lower engagement scores than children in the TD group, active participation in vocal interactions appears to support their classroom engagement with teachers and peers.

Determination of organophosphorus and synthetic pyrethroid pesticide residues and their variability in large size fruit crops.

BACKGROUND: Variability of pesticide residues in food item plays a key role for the evaluation of consumer food safety. However, variability factors (VFs) derived from the large size fruit crops are still scarce. Therefore, the present work was aimed to quantify pesticide residues and to estimate VFs in large size fruit crops of mango and guava. RESULTS: A total of 140 mango and 130 guava samples from different marketplaces in Bangladesh were collected to estimate the variability of pesticide residues (acephate, diazinon, malathion, fenitrothion, chlorpyrifos, quinalphos, dimethoate and cypermethrin) by in-house validated methods based on modified QuEChERS extraction and gas chromatography coupled with electron capture detector (ECD) and flame thermionic detector (FTD). The method was validated at three fortification levels (0.01, 0.10 and 0.30 mg kg-1 ) and satisfactory recoveries (80-111%) with relative standard deviation (RSDr ) ≤ 13% were achieved. A wide variation of residues was found in the analyzed samples. In the case of mango, the ranges of residues were 0.011-0.314, 0.015-0.04, and 0.05-0.291 mg kg-1 , respectively, for cypermethrin, chlorpyrifos, and dimethoate, while in the case of guava, the ranges were 0.04-0.113, and 0.03-0.290 mg kg-1 , respectively, for cypermethrin and acephate. The average VF for mango was 4.06 and it was 5.70 for guava. CONCLUSION: VFs originating from the marketed samples of mango and guava are reported in this study for the first time. The estimated VFs were higher than the default value of 3, therefore, the default VFs should be reconsidered when more data are obtained regarding large size crops. © 2021 Society of Chemical Industry.