The persistent yield gap remains a major challenge in organic agriculture despite its increasing importance for sustainable food production. The present study compared the performance of 80 diverse rice genotypes (62 landraces  and 18 modern varieties) under two contrasting production systems (organic and conventional). The experiment was conducted during the Kharif seasons of 2023 and 2024 using an alpha lattice design (8 × 10) with three replications. Agro-morphological and yield-related traits were analysed through pooled mixed-model analysis of variance (ANOVA), genetic variability parameters, correlation and path coefficient analyses, as well as principal component analysis (PCA). The results revealed significant genotypic variation and differential trait expression between the two production systems, with the relative contribution of agro-morphological traits to grain yield varying between production systems. Integrated analysis of genetic variability, correlation, path coefficient analysis, and principal component analysis identified production system-specific trait combinations associated with grain yield. Under the conventional production system, flag leaf breadth (FLB), number of productive tillers per plant (NPTP), hundred seed weight (HSW), and flag leaf length (FLL) were prominent traits, with strong positive direct effects in path analysis, whereas leaf area (LA), NPTP, HSW, plant height (PH), and days to 50% flowering (DFF) were prominent under the organic production system, also showing positive direct effects in path analysis. Genotypic best linear unbiased prediction (BLUP) estimates identified Ponmani samba (G40), Varakkal (G60), and Sengalapattu sirumani (G49) with the highest yield BLUP estimates under the organic production system, whereas Mani samba (G29), TKM1 (G80), and Bavani (G6) showed the highest yield BLUP estimates under the conventional production system. Milagu samba (G31), Polinel (G39), and Ponmani samba (G40) consistently ranked among the top-performing genotypes based on yield BLUP estimates across both production systems, indicating their potential as breeding materials for further evaluation.

Waterlogging-induced hypoxia is becoming an increasingly important constraint to crop production under climate change. Although quinoa (Chenopodium quinoa Willd.) is recognized for its tolerance to drought and salinity, its response to hypoxia remains poorly understood. This study evaluated the effects of hypoxia on growth, root development, biomass accumulation, and individual seed yield in 28 quinoa genotypes. Hypoxia reduced plant height by 31%, leaf area by 47%, root length by 39%, and shoot dry weight by 37% (mean hypoxia tolerance index 0.69, 0.53, 0.61, and 0.63); shoot dry weight remained 44% lower after recovery, whereas root diameter increased by 28% under hypoxia. Correlation analysis revealed that root length and root surface area were positively associated with individual seed yield, whereas root diameter was negatively related to several growth traits, highlighting the importance of maintaining root development under hypoxia. Permutational multivariate analysis of variance across 19 traits attributed 37.1% of overall phenotypic variation to genotype, 30.0% to oxygen regime, and 18.8% to their interaction (each p = 0.001), and hierarchical clustering on hypoxia tolerance indices resolved three genotype groups with contrasting trait profiles. Under hypoxia, Amachuha and Isluga produced the highest individual yields, followed by EDK4 and Chadmo. Under genotype-level validation (leave-one-genotype-out, leave-one-cluster-out, and highland-versus-lowland cross-ecotype splits), no model predicted the individual yield of genotypes excluded from training better than the mean yield of the training genotypes under the same oxygen regime, so trait-based yield prediction does not transfer to unseen quinoa genotypes. These findings provide valuable insights into the mechanisms of hypoxia tolerance and identify promising genetic resources for breeding quinoa cultivars adapted to waterlogging-prone environments.

This randomized clinical trial aimed to compare the effects of cryotherapy, anesthetic spray, and gel on pain, anxiety, physiological responses, taste acceptability, and treatment compliance in children aged 7-10 years undergoing their first dental treatment. 100 healthy children were randomly allocated into four groups: 10% lidocaine spray, 20% benzocaine gel, cryotherapy with distilled water cooled to +4 °C, and lidocaine spray cooled to +4 °C. Following topical application, buccal infiltration anesthesia was administered. Anxiety, pain, and physiological responses were assessed using the Modified Dental Anxiety Scale and Facial Image Scale, Wong-Baker FACES Pain Rating Scale, and pulse-oximeter. Taste acceptability and treatment compliance were evaluated using a three-point Hedonic Scale and the FRANKL Scale. Repeated Measures ANOVA, Mann-Whitney U, and Kruskal-Wallis tests were applied. No significant differences were observed among the groups in anxiety, pain, pulse rate, oxygen saturation, or taste acceptability (p > 0.05). Pulse rate increased from the pre-operative to the post-operative period in all groups (p = 0.006), with no significant group × time interaction. FRANKL scores were significantly higher in the cryotherapy-distilled water group compared with the gel and cooled-spray groups (p = 0.001), a finding considered exploratory. Pain and anxiety outcomes following cryotherapy did not differ significantly from those of the topical anesthetic agents, while treatment compliance was higher, suggesting that cryotherapy may be a promising non-pharmacological option, pending confirmation in non-inferiority trials.

Self-supervised pre-training has transformed adult electrocardiogram (ECG) analysis, but it is unclear whether it can help non-invasive fetal ECG (fECG), where open annotated corpora are orders of magnitude smaller. Self-supervised models have been applied to pregnancy ECG for prenatal stress detection on private cohorts. We ask a different question: on public abdominal recordings, which self-supervised objective, if any, transfers to held-out fetal QRS detection? We compare contrastive (SimCLR), variance-covariance (VICReg) and masked signal modelling objectives on one encoder, pre-trained on 68 open recordings with PhysioNet/CinC 2013 held out. Naive contrastive pre-training collapses (effective rank 2.5 of 64) and underperforms a random encoder. Per-window instance normalisation prevents collapse (effective rank 9.6). All three objectives beat random initialisation on held-out CinC 2013 (record-grouped cross-validation, $\pm$50 ms): masked modelling reaches $F_{1}=0.33{}\pm 0.13{}$ versus $0.27{}\pm 0.09{}$ (paired Wilcoxon $p=1.4\times 10^{-7}{}$; Cohen's $d_{z}=0.75$, 95% CI [0.039,0.072]). The numeric edge over SimCLR ($F_{1}=0.32{}$) is small, not significant ($p=0.14$), and shrinks to 0.004 across three training seeds. With $5\%$ of labels the frozen masked encoder matches a random encoder trained on $100\%$. Under full fine-tuning the gap vanishes ($F_{1}=0.50{}$ vs $0.50{}$, $p=0.53{}$); with 3-6 labelled records pre-training helps under the same 12-epoch protocol ($+0.02$-0.03) but not when fine-tuning runs longer. On the same records, supervised delineation networks reach $F_{1}=0.92$ and classical extractors 0.68, so the probe measures representation quality. Embeddings do not encode gestational age and remain dataset-separable. Code, configurations and seeds are released.

Small-sided games (SSG) are common across a number of team sports and are used for physical conditioning and technical and tactical skill acquisition purposes. As athletes within and between teams interact with each other due to the task structure, individual athletes' performances are inherently interdependent. Accordingly, measurements across athletes are correlated with each other and do not represent independent pieces of information. When data dependencies are not correctly analyzed, this can result in what is called pseudoreplication and lead to erroneous, overly liberal statistical inferences. To assess the magnitude of possible errors, a Monte Carlo simulation was performed comparing analyses using a repeated-measures ANOVA, a Friedman test, and a linear mixed-effects model (LMM). Only the LMM maintained the nominal Type-I error rate whereas increasing the dependency between data points led to large increases in Type-I error rates for the other two methods. A re-analysis of a published small-sided games study indicated high within-game correlations between athletes (ICC = 0.77). To assess the scope of pseudoreplication in SSG research, 102 studies from four leading sport science journals were surveyed. Over 66% of the studies showed indicators of possible pseudoreplication, whereas only 6% reported an appropriate analysis. Small-sided team games researchers accordingly need to be aware of pseudoreplication and how best to avoid this issue through appropriate statistical analysis methods discussed in the present work.

Herbivore-associated stimulation can alter primary and specialized metabolism, but comparative biochemical responses of cereal crops remain insufficiently characterized. This study investigated changes in soluble sugars and targeted phenolic acids in sorghum (Sorghum bicolor L. Moench) cultivar Epuripur sorghum and NERICA 9 rice following simulated caterpillar herbivory. Plants were subjected to mechanical leaf wounding followed by application of diluted oral secretions from fourth- and fifth-instar Mythimna loreyi larvae (WOS), while untreated plants served as controls. After 24 h, leaf tissues were analyzed by high-performance liquid chromatography (HPLC) for glucose, fructose, and seven targeted phenolic acids. Two-way ANOVA evaluated effects of plant material, treatment, and their interaction. WOS treatment significantly reduced glucose and fructose concentrations in both materials (P < 0.001), with significant plant material × treatment interactions. Several phenolic acids increased or became detectable following WOS treatment, including p-hydroxybenzoic, vanillic, syringic, p-coumaric, cinnamic, and chlorobenzoic acids. Significant plant material × treatment interactions occurred for most phenolic acids, whereas the interaction for p-coumaric acid was not significant (P = 0.205). Epuripur sorghum generally exhibited higher concentrations of several metabolites than NERICA 9. These findings indicate material-specific biochemical responses to simulated caterpillar-associated stimulation involving changes in both primary and phenolic metabolism. However, the study does not establish carbon allocation, growth-defense trade-offs, or direct insect resistance. Because wounding-only and oral-secretion-only treatments were not included, their individual effects could not be separated. The results provide candidate biochemical responses for further investigation using direct herbivore feeding, multiple genotypes, time-course sampling, and physiological and insect-performance measurements.