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The recent development of wireless communication technology empowers sensing, monitoring, and data transfer in remote areas through a heterogeneous model. However, managing energy levels for data transfer presents challenges, as energy consumption can lead to packet loss, and delay tolerance can cause latency failures, ultimately impacting network lifetime. To address this, we propose the Cooperative Stabilized Proactive Energy-Aware Cluster Routing Protocol (CSP-EACRP) based on self-balanced cooperative communication in wireless sensor networks. Initially, we estimate neighbour discovery node level depletion and determine the Node response behaviour rate to assess the active transmission level, considering energy, delay, transmission, drop ratio, and latency. This estimation helps determine the absolute mean weight when considering active nodes. We then construct the Adaptive Petal Spider Ant Colony Cluster Algorithm (APSAC2A) to enhance link stability for route optimization. Subsequently, the Cooperative Stabilized Proactive Energy-Aware Cluster Routing Protocol (CSP-EARP) is developed to facilitate self-balanced congestion routing (SBCR) with support from the Lookup Energy Constraint Duty Cycle (LECDC), aiming to improve network lifetime. This, in turn, enhances throughput performance and distributes routing energy efficiently among one or more nodes. Compared to existing transmission models, this proposed system prolongs network lifetime and improves Quality of Service (QoS) performance, yielding superior results. The proposed system achieves energy-efficient data transfer, enhancing delay tolerance at the latency level and increasing throughput to improve communication lifetime.

Abstract Scrub typhus, a neglected disease, is a significant health concern in the Tsutsugamushi triangle of the Asia–Pacific and has raised global concerns due to recent cases occurring outside this region. To estimate the global prevalence of scrub typhus, we conducted a systematic review and meta-analysis. We conducted a systematic search of PubMed, Scopus, and Embase databases for observational studies on scrub typhus. Using a random-effects model, we combined the prevalence estimates with inverse-variance weights while also evaluating heterogeneity and publication bias. Among 3551 reports screened, we identified 181 studies with 1,48,251 samples for inclusion in our synthesis. The overall pooled seroprevalence (95% confidence intervals) of scrub typhus infections was 24.93% (23.27–26.60). Gender-wise pooled prevalence was estimated to be 50.23% (47.05–53.40) for males and 48.84% (45.87–51.80) for females. Eschar prevalence was observed to be 30.34% (22.54–38.15) among the positive cases. One-fourth of all the samples tested positive for scrub typhus and eschar was present in one-third of these total positive cases, encompassing regions beyond the Tsutsugamushi triangle. This estimation underlines the importance of this neglected disease as a public health problem. Strengthening surveillance and implementing disease control measures are needed in the affected regions.

Objectives: The burden of asymptomatic dengue infections is understudied. Therefore, we systematically reviewed the literature to estimate the global prevalence of asymptomatic dengue infections. Methods: We searched cross-sectional studies reporting the prevalence of asymptomatic dengue infections from PubMed, Scopus, and Embase. Prevalence of asymptomatic dengue infections was pooled and reported as proportions with a 95% confidence interval (CI). This systematic review protocol was a priori registered in The International Prospective Register of Systematic Reviews (Reg: No. CRD42020218446). Results: We included 41 studies with 131,953 cases in our analysis. The overall pooled prevalence of asymptomatic dengue infections was 59.26% (95% CI: 43.76-74.75, I2 = 99.93%), with 65.52% (95% CI: 38.73-92.32, I2 = 99.95%) during outbreaks and 30.78% (95% CI: 21.39-40.16, I2 = 98.78%) during non-outbreak periods. The pooled prevalence among the acutely infected individuals was 54.52% (95% CI: 17.73-46.76, I2 = 99.91%), whereas, among primary and secondary asymptomatic dengue infections, it was 65.36% (95% CI: 45.76-84.96, I2 = 98.82) and 48.99% (95% CI: 27.85-70.13, I2 = 99.08%) respectively. Conclusion: The majority of dengue cases are asymptomatic and may play a significant role in disease transmission. Public health strategies aimed at dengue outbreak response and mitigation of disease burden should include early detection of asymptomatic cases.

Cotton is a pivotal global commodity underscored by its economic value and widespread use. In the face of climate change, breeding resilient cultivars for variable environmental conditions becomes increasingly essential. However, the process of phenotyping, crucial to breeding programs, is often viewed as a bottleneck due to the inefficiency of traditional, low-throughput methods. To address this limitation, this study utilizes hyperspectral remote sensing, a promising tool for assessing crucial crop traits across forty cotton varieties. The results from this study demonstrated the effectiveness of four vegetation indices (VIs) in evaluating these varieties for water-use efficiency (WUE). The prediction accuracy for WUE through VIs such as the simple ratio water index (SRWI) and normalized difference water index (NDWI) was higher (up to R2 = 0.66), enabling better detection of phenotypic variations (p < 0.05) among the varieties compared to physiological-related traits (from R2 = 0.21 to R2 = 0.42), with high repeatability and a low RMSE. These VIs also showed high Pearson correlations with WUE (up to r = 0.81) and yield-related traits (up to r = 0.63). We also selected high-performing varieties based on the VIs, WUE, and fiber quality traits. This study demonstrated that the hyperspectral-based proximal sensing approach helps rapidly assess the in-season performance of varieties for imperative traits and aids in precise breeding decisions.

The increasing severity of drought has become a significant threat to global crop production. Early season drought in corn produces poor plant stand and grain yield. Thus, identifying corn hybrids for drought tolerance during the early season is important. Nineteen corn hybrids commonly grown in the Midsouthern US were assessed for drought tolerance using mini-hoop structures. Plants grown under non-stress conditions were exposed to three moisture levels at 100% (0.17 m3 m−3 soil; control), 66% (mild drought; DS1), and 33% (moderate drought; DS2) of the control from one to five leaf stages (V1 to V5). The physiological and morphological traits of corn hybrids were measured to assess variability in drought tolerance. When averaged across the hybrids, shoot parameters declined by 51% and 59% under DS1 and DS2 conditions, respectively, compared to the control. A decline in root traits was noticed under drought stress (38% under DS1 and 48% under DS2) compared to the control, revealing the shoot system sensitivity under drought conditions. In the principal component analysis, the first two principal components accounted for 66% of the phenotypic variation among the corn hybrids under drought stress. Total, shoot, leaf dry weights, root surface area, and root volume captured most of the phenotypic variation among the corn hybrids under drought. The results of the principal component analysis and drought stress response indices complimented the identification of ‘A6659’ and ‘D57VP51’ as drought-tolerant hybrids during the early seedling stage. These hybrids can be used as source material in developing drought-tolerant cultivars. Also, the tolerant hybrids will perform best under rainfed environments prone to early-season drought.

Low rainfall combined with heat stress during grain filling can cause a severe threat to maize production. Compared to individual stress, the impact of combined stressors on plant performance during the grain filling remains less explored. In this study, two maize genotypes, ‘B73’ and ‘Mo17’, were subjected to four treatments (control, drought stress, heat stress, and combined drought and heat stress) to understand how maize genotypes respond to stressors during grain filling. Stomatal conductance displayed an opposite response between drought and heat or combined stresses during the mid-grain filling stage. Averaged over genotypes, decreased stomatal conductance (67.4%) and increased leaf temperature (5.6 °C) under combined stress treatments resulted in a significant yield reduction (78.9%) compared to control. Drought or combined stressors during the grain filling stage had a predominant effect on sink potential (kernel weight) than heat stress. Reduction in kernel size of genotype ‘B73’ was associated with a 5.5% decline in starch under heat stress. Analysis of individual and interactive stressors effects on maize showed that trait responses could vary with stresses during grain filling. The present study showed that the maize phenotypic responses differ between individual and interactive stresses. The genotype ‘Mo17’ exhibited relatively higher tolerance to both individual and combined drought and heat stresses than ‘B73’. The present study highlighted the maize plant responses to individual and combined stresses, which is essential for improving maize tolerance to drought and heat stress conditions.

Drought is a severe threat to agriculture production that affects all growth stages of plants, including corn (Zea mays L.). Any factor affecting early seedling growth and development will significantly impact yield. Despite the recurrence of low rainfall during the growing seasons, corn responses to different early-season soil moisture content levels have not been investigated. In this study, we investigated how corn morpho-physiological and biomass traits responded to varied soil moisture content during the early vegetative stage. Two corn hybrids were grown in a pot-culture facility under five different soil moisture treatments (0.15, 0.12, 0.09, 0.06, and 0.03 m3 m−3 volumetric water content, VWC) to assess the growth and developmental responses to varied soil moisture content during early-season growth (V2 to V7) stage. Sub-optimal soil moisture content limited plant growth and development by reducing physiological and phenotypic expression. Stomatal conductance and transpiration were decreased by an average of 65% and 59% across stress treatments relative to optimum conditions. On average, soil moisture deficit reduced the total leaf area by 71% and 72% compared to the control in ‘A6659VT2RIB’ and ‘P1316YHR’, respectively. Shoot and root dry weights were reduced by 74% and 43% under 0.03 m3 m−3 VWC. An increase in the root-to-shoot ratio was noticed under low VWC conditions compared to the control. Based on the stress tolerance index, the physiology and leaf growth parameters were more sensitive to soil moisture deficit. Our results highlight the impact of sub-optimal soil moisture on physiology and morphological traits during early-season growth. ‘P1316YHR’ demonstrated better physiological performance under stress conditions, while ‘A6659VT2RIB’ produced relatively better root growth. The findings suggest that biomass partitioning between shoot and root components is dynamic and depends on stress intensity. The current findings can help to prioritize traits associated with the early-season drought tolerance in corn. The functional relationships developed between soil moisture content and growth and developmental responses can be integrated into corn crop modeling to allow better irrigation management decisions.

Abstract Drought and heat stresses are the major abiotic stress factors detrimental to maize (Zea mays L.) production. Much attention has been directed toward plant responses to heat or drought stress. However, maize reproductive stage responses to combined heat and drought remain less explored. Therefore, this study aimed to quantify the impact of optimum daytime (30°C, control) and warmer daytime temperatures (35°C, heat stress) on pollen germination, morpho‐physiology, and yield potential using two maize genotypes (“Mo17” and “B73”) under contrasting soil moisture content, that is, 100% and 40% irrigation during flowering. Pollen germination of both genotypes decreased under combined stresses (42%), followed by heat stress (30%) and drought stress (19%). Stomatal conductance and transpiration were comparable between control and heat stress but significantly decreased under combined stresses (83% and 72%) and drought stress (52% and 47%) compared with the control. Genotype “Mo17” reduced its green leaf area to minimize the water loss, which appears to be one of the adaptive strategies of “Mo17” under stress conditions. The leaf reflectance of both genotypes varied across treatments. Vegetation indices associated with pigments (chlorophyll index of green, chlorophyll index of red edge, and carotenoid index) and plant health (normalized difference red‐edge index) were found to be highly sensitive to drought and combined stressors than heat stress. Combined drought and heat stresses caused a significant reduction in yield and yield components in both Mo17 (49%) and B73 (86%) genotypes. The harvest index of genotype “B73” was extremely low, indicating poor partitioning efficiency. At least when it comes to “B73,” the cause of yield reduction appears to be the result of reduced sink number rather than the pollen and source size. To the best of our awareness, this is the first study that showed how the leaf‐level spectra, yield, and quality parameters respond to the short duration of independent and combined stresses during flowering in inbred maize. Further studies are required to validate the responses of potential traits involving diverse maize genotypes under field conditions. This study suggests the need to develop maize with improved tolerance to combined stresses to sustain production under increasing temperatures and low rainfall conditions.