Primary Food Source Research Articles

Shaping the future of bananas: advancing genetic trait regulation and breeding in the postgenomics era.

Bananas (Musa spp.) are among the top-produced food crops, serving as a primary source of food for millions of people. Cultivated bananas originated primarily from the wild diploid species Musa acuminata (A genome) and Musa balbisiana (B genome) through intra- and interspecific hybridization and selections via somatic variation. Following the publication of complete A- and B-genome sequences, prospects for complementary studies on S- and T-genome traits, key gene identification for yield, ripening, quality, and stress resistance, and advances in molecular breeding have significantly expanded. In this review, latest research progress on banana A, B, S, and T genomes is briefly summarized, highlighting key advances in banana cytoplasmic inheritance, flower and fruit development, sterility, and parthenocarpy, postharvest ripening and quality regulation, and biotic and abiotic stress resistance associated with desirable economic traits. We provide updates on transgenic, gene editing, and molecular breeding. We also explore future directions for banana breeding and genetic improvement.

Application of a multi-wavelength excitation fluorometer and machine-learning algorithm for on-site measurement of long-chain polyunsaturated fatty acids in lakes

Aoki N, Fujibayashi M, Sakamaki T, Kuba T. 2025. Application of a multi-wavelength excitation fluorometer and machine-learning algorithm for on-site measurement of long-chain polyunsaturated fatty acids in lakes. Lake Reserv Manage. XXX–XXX. Long-chain polyunsaturated fatty acids, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are important indicators of the nutritional quality of diets for aquatic animals. Seston contributes the primary basal food source; therefore, monitoring the contents (absolute amount per mass or volume) and levels (mass percent of total fatty acids) of these fatty acids in seston is a rational strategy for lake and reservoir management to maintain ecosystem health. However, conventional methods for EPA and DHA analyses in seston are labor-intensive and complex. This study aimed to develop a simple approach for field measurement of EPA and DHA using a multi-wavelength excitation fluorometer (MEX), which was originally designed to estimate the Chl-a concentration derived from each phytoplankton class based on excitation spectra. We proposed that a model could be developed by incorporating machine learning to predict EPA and DHA from excitation spectra. Water samples (151) were collected from the Hokuzan Reservoir in Saga Prefecture. The excitation spectra for each water sample were obtained on-site by MEX, and the EPA and DHA in the seston were analyzed in the laboratory using conventional methods. Based on these data, predictive models were developed using an extra-tree regressor, the one of machine learning algorithms. The model achieved average R2 values of 0.78, 0.74, 0.83, and 0.80 for EPA contents, DHA contents, EPA levels, and DHA levels, respectively. Consequently, using MEX enables novel and simple on-site measurements of EPA and DHA, further facilitating spatiotemporally dense data acquisition and potentially improving lake and reservoir ecosystem management.

The haplotype-resolved assembly of COL40 a cassava (Manihot esculenta) line with broad-spectrum resistance against viruses causing Cassava brown streak disease unveils a region of highly repeated elements on chromosome 12.

Cassava (Manihot esculenta Grantz) is a vital staple crop for millions of people, particularly in Sub-Saharan Africa, where it is a primary source of food and income. However, cassava production is threatened by several viral diseases, including cassava brown streak disease, which causes severe damage to the edible storage roots. Current cassava varieties in Africa lack effective resistance to this disease, leading to significant crop losses. We investigated the genetic diversity of cassava and identified new sources of resistance to the viruses causing cassava brown streak disease. The cassava line, COL40, from a South American germplasm collection showed broad-spectrum resistance against all known strains of the viruses that cause this disease. To further understand the genetic basis of this resistance, we sequenced the genome of COL40 and produced a high-quality, haplotype-resolved genome assembly. This genomic resource provides new insights into cassava's genetic architecture, particularly in regions associated with disease resistance. The sequence reveals significant structural variation, including transposable elements, inversions, and deletions, which may contribute to the resistance phenotype. The reference genome assembly presented here will provide a valuable genomic resource for studying the cassava brown streak resistance and will help in accelerating breeding efforts to introduce virus resistance into African cassava varieties. By identifying genetic variants linked to resistance, future breeding programs can develop cassava cultivars that are more resilient to viral threats, enhancing food security and livelihoods for smallholder farmers across regions affected by the disease.

Novel hybrid transfer neural network for wheat crop growth stages recognition using field images

Wheat is one of the world’s most widely cultivated cereal crops and is a primary food source for a significant portion of the population. Wheat goes through several distinct developmental phases, and accurately identifying these stages is essential for precision farming. Determining wheat growth stages accurately is crucial for increasing the efficiency of agricultural yield in wheat farming. Preliminary research identified obstacles in distinguishing between these stages, negatively impacting crop yields. To address this, this study introduces an innovative approach, MobDenNet, based on data collection and real-time wheat crop stage recognition. The data collection utilized a diverse image dataset covering seven growth phases ‘Crown Root’, ‘Tillering’, ‘Mid Vegetative’, ‘Booting’, ‘Heading’, ‘Anthesis’, and ‘Milking’, comprising 4496 images. The collected image dataset underwent rigorous preprocessing and advanced data augmentation to refine and minimize biases. This study employed deep and transfer learning models, including MobileNetV2, DenseNet-121, NASNet-Large, InceptionV3, and a convolutional neural network (CNN) for performance comparison. Experimental evaluations demonstrated that the transfer model MobileNetV2 achieved 95% accuracy, DenseNet-121 achieved 94% accuracy, NASNet-Large achieved 76% accuracy, InceptionV3 achieved 74% accuracy, and the CNN achieved 68% accuracy. The proposed novel hybrid approach, MobDenNet, that synergistically merges the architectures of MobileNetV2 and DenseNet-121 neural networks, yields highly accurate results with precision, recall, and an F1 score of 99%. We validated the robustness of the proposed approach using the k-fold cross-validation. The proposed research ensures the detection of growth stages with great promise for boosting agricultural productivity and management practices, empowering farmers to optimize resource distribution and make informed decisions.

Gene expression and enzyme activity analysis of carbohydrate digestion in Strongylocentrotus purpuratus larvae.

Carbohydrates play multifaceted roles in marine ecosystems, serving as structural components in algae, energy storage molecules, and vital nutrients for marine organisms. The purple sea urchin Strongylocentrotus purpuratus undergoes metamorphosis during ontogeny, transitioning its feeding strategy from microalgae to macroalgae as the primary food source. However, the digestive mechanisms underlying carbohydrate digestion in sea urchin larvae remain poorly understood. We investigated the carbohydrate digestion capabilities of S. purpuratus larvae, using expression level analysis of candidate genes putatively involved in carbohydrate digestion, quantification of enzyme activity and characterization (pH and temperature optima) for the digestion of starch, laminarin, cellulose, xylan, and trehalose. Transcriptomic analyses revealed the expression of genes encoding putative carbohydrate-degrading enzymes during early larval development. RT-qPCR demonstrated age- and/or feeding-dependent expression patterns of glycosidase candidate genes β-1,3-glucanase (laminarinase), α-amylase, endo-ß-1,4-glucanase D-like (cellulase), xylanase/β-glucanase-like and trehalase. Furthermore, enzymatic assays elucidated differential temporal patterns, and thermal and pH optima of associated carbohydrate-degrading enzymes. A comparison of the enzymatic degradation of five substrates demonstrated that laminarinase activity is five times higher than the enzyme activities involved in digesting starch, cellulose, xylan, and trehalose, opening up a hypothesis regarding the importance of laminarin for larval growth.

Differences and correlation analysis of feeding habits and intestinal microbiome in Schizopygopsis microcephalus and Ptychobarbus kaznakovi in the upper reaches of Yangtze River.

The intestinal microbiota has co-evolved with the host to establish a stable and adaptive microbial community that is essential for maintaining host health and facilitating food digestion. Food selection is a critical factor influencing variations in gut microbial composition, shaping gut microbiome communities, and determining the ecological niches of fish. In this study, high-throughput amplicon sequencing of 16S rRNA and 18S rRNA was utilized to compare the dietary and gut microbial differences between Schizopygopsis microcephalus and Ptychobarbus kaznakovi, both collected from the same sites in the Tuotuo River and Tongtian River, which are tributaries of the Yangtze River. We compared the microbial community structure, diet composition, and diversity between the two fish species using various analytical methods, including LefSe, α-diversity and β-diversity analyses. Additionally, we constructed co-occurrence networks to determine their correlations. The alpha diversity results indicated that S. microcephalus exhibited higher intestinal microbiota and feeding diversity compared to P. kaznakovi. Furthermore, the beta diversity results revealed significant differences in both intestinal microbiota and eukaryotic communities between the two species. The dominant bacterial phyla in both S. microcephalus and P. kaznakovi included Proteobacteria, Firmicutes, Actinobacteriota, Chloroflexi, and Verrucomicrobiota; however, Firmicutes was significantly more abundant in P. kaznakovi (P = 0.006), while Actinobacteriota was significantly higher (P = 0.019) in S. microcephalus at the phylum level. The primary food sources for S. microcephalus and P. kaznakovi were identified as Streptophyta (54.41%, 77.50%) and Cercozoa (8.67%, 1.94%), with Bacillariophyta (25.65%) was also the main food of constituting a major component of the diet for S. microcephalus. These differences suggested that S. microcephalus and P. kaznakovi occupy distinct dietary niches. To further explore the relationship between gut microbiota and feeding habits, we identified significant correlations between various food components and the gut microbial community through co-occurrence networks. This study enhances our understanding of the co-evolution and co-adaptation between host gut microbiota and feeding behaviors in sympatric fish species.

Mass harvested per trunkload as a constraint to forage consumption by the African savanna elephant (Loxodonta africana).

African elephants can convert woodland to shrubland or grassland. Moderate conversion observed at low elephant densities may improve conditions for other animals, while extensive transformation at high densities may reduce plant and animal diversity. The threshold density separating facilitation from habitat destruction varies spatially and is partly determined by food choice, which differs between adult bulls and members of breeding herds. When elephants consume herbaceous forage, woodland damage is low but this increases when woody plants are the primary food source. Consequently, an understanding of diet selection by elephants is important for forecasting the degree of vegetation conversion. One hypothesis is that elephants select forage that provides the highest rate of intake. The mass harvested per trunkload is a constraint to intake and therefore this study sought to determine if trunkload mass changes seasonally; varies across common forage types utilised by elephants; and differs between adult bulls and members of breeding herds. Mechanistic models were used to estimate the mass harvested per trunkload of green grass, mixed green and dry grass, forbs, and leaves and bark from woody plants across a heterogenous, semi-arid savanna at a daily time step for one annual cycle. Separate models were constructed for adult bulls and members of breeding herds. Harvestable mass changed seasonally for herbaceous forage and for leaves from woody plants but was constant for canopy bark. The maximum average trunkload mass of green grass was >75 times heavier than the bite mass reported for other grazers while trunkloads of leaves from woody plants were only eight times heavier than the bite mass reported for other browsers. This is attributed to the advantage provided by the trunk, which increases harvestable mass beyond the constraint of mouth volume, particularly when feeding on grass. Herbaceous forage yielded heavier trunkloads than leaves and bark from woody plants during the wet season, but this was reversed in the dry season. Adult bulls harvested heavier trunkloads than members of breeding herds for all forage types except forbs; and adult bulls harvested disproportionately large trunkloads of grass and bark. The strong correlation between the model outputs and well-established trends in the seasonal changes in elephants' diet suggests that elephants are preferential foragers of the largest trunkload on offer. Consequently, they are grazers when suitable herbaceous forage is available, and browsers when it is scarce. Green grass provides adult bulls with disproportionately large trunkloads and, therefore, adult bulls are predicted to have a strong preference for green grass. Availability of suitable green grass during the dry season may therefore buffer woodlands from heavy impact by adult bulls. Consequently, where possible, protected areas with elephants should aim to include key grass resources.

Ocean color anomaly detection to estimate surface Calanus finmarchicus concentration in the Gulf of Maine

The planktonic copepod, Calanus finmarchicus, plays a pivotal role in the Gulf of Maine (GoM) pelagic food web as a primary food source for many species, including the critically endangered North Atlantic right whale (NARW). Thus, observing C. finmarchicus on a Gulf-wide scale via satellite could be beneficial for understanding changes in the migration patterns of the NARW. This study investigated the application of ocean color remote sensing to detect the surface population levels of C. finmarchicus in the GoM. Using remote sensing reflectance data from the MODIS Aqua sensor, we processed enhanced RGB (eRGB) imagery to detect and quantify the presence of C. finmarchicus, which is identifiable by its red astaxanthin pigment. This study employed a refined approach from the method originally developed off the coast of Norway, which integrates eRGB imagery and radiative transfer modeling to generate optical anomaly maps that are used for quantifying surface C. finmarchicus concentrations in the GoM. We detected surface swarms of C. finmarchicus in the ocean color imagery and estimated their concentrations. However, due to the method’s reliance on astaxanthin/red pigment-based detection, other astaxanthin-rich red/brown plankton were misidentified as C. finmarchicus. While the approach presented is effective for identifying astaxanthin anomalies in ocean color and holds potential for quantifying the surface populations of C. finmarchicus, it requires local knowledge to accurately quantify the C. finmarchicus abundances.

Modeling the spatial distribution of dung beetles under climate change scenarios: insights based on nesting strategy, body size and period of activity

Abstract Climate change is expected to exert varying effects on different taxa and species, affecting both their abundance and distribution ranges. Previous studies have used climate niche models (CNMs) to estimate shifts in the distribution of insects, without considering whether the effects of climate change may vary depending on their functional traits (nesting strategy, body size, and period of activity). Dung beetles, a taxonomic group characterized by using mammalian dung as their primary source of food (coprophagy), respond differently to temperature fluctuations depending on their nesting strategy and body size. In this study, we used CNMs to estimate shifts in the distribution ranges of 33 species of dung beetles under climate change scenarios (the shared socioeconomic pathways from the IPCC’s Sixth Assessment Report) for the period 2041–2060 in North America and Central America (excluding Canada due to absence of data). Additionally, we analyzed whether the effects of climate change on the distribution ranges of the studied species are significantly different depending on their functional traits. Our results showed that climate change will negatively affect the distribution range of the majority of the studied species by the middle of this century, with contrasting effects depending on their nesting strategy and body size. The smallest species and dwellers showed an increase in their occurrence probabilities and percentage of highly suitable habitats, whereas larger-bodied species and tunnelers showed a decrease in both. We found no significant differences between diurnal and nocturnal species. Our results show that by incorporating key traits related to temperature response and ecosystem function, we can analyze shifts in species distribution ranges more precisely, enabling the identification of patterns across functional categories and predictions about their future.

Untapped potential of calcium and nano-calcium to develop abiotic stress resilience in photosynthetic machinery: The primary source of plant food and fuels

Untapped potential of calcium and nano-calcium to develop abiotic stress resilience in photosynthetic machinery: The primary source of plant food and fuels

Leveraging synergies between UAV and Landsat 8 sensors to evaluate the impact of pale lichen biomass on land surface temperature in heath tundra ecosystems.

Leveraging synergies between UAV and Landsat 8 sensors to evaluate the impact of pale lichen biomass on land surface temperature in heath tundra ecosystems.

Measurement of Radioactivity in Common Powered Milk Consumed in Sana’a, Yemen and Estimation of the Associated Annual Effective Dose

This study focuses on measuring the radioactivity in milk, given its critical importance and sensitivity as a fundamental component of humannutrition, particularly due to its vital role as a primary food source for children during the early stages of life. The radionuclides of 232Th, 226 Ra and 40K were measured in 16 brands of powdered milk consumed in Yemen, imported from various regions worldwide. The measurements were conducted using gamma-ray spectroscopy with an HPGe detector, equipped with a specially designed shield. The range of 226 Ra from (0.42±0.08 to 1.86±0.30 with an average of 0.77±0.12) Bq/kg, the range of 232Th from (0.21±0.05 to 0.40±0.07 with an average of 0.30±0.05) Bq/kg, and the range of 40K (from 140.69±3.90 to 195.96±5.29 with an average of 169.06±4.63) Bq/kg, respectively, for infant group (≤ 1 year). The range of 226Ra from (0.14±0.03 to 7.21±1.34 with an average of 1.88±0.54) Bq/kg, the range of 232Th from (0.25±0.04 to 1.22±0.34 with an average of 0.68±0.15) Bq/kg, and the range of 40K (from 141.52±3.90 to 534.39±13.54 with an average of 320.36±8.35) Bq/kg, respectively, for individuals above 2 years, respectively. The total average annual effective dose due to ingestion of radionuclides was calculated for three age groups and found to be (214.50, 123.27, and 41 μSv/year) for infant group (≤ 1 year), children (2-17 years), and adults (>17 years), respectively. Overall, these values are lower than the WHO/FAO and ICRP recommended limit of (1.0 mSv/year) for all age groups, indicating that the radioactivity levels in the tested powdered milk are within acceptable safety limits.

Forecasting of Rice Harvest Results Using SVR Modeling Techniques

Forecasting is an activity that predicts future values {}{}by utilizing existing track record data. The object of this study is rice plants because they are the primary food source for the Indonesian people. Every year, the Government strives for rice farmers throughout Indonesia to produce abundant rice harvests to meet the community's food needs. Therefore, rice farmers need a system that can predict their rice harvests to obtain information about future harvests to find out whether their harvests have decreased or increased so that they can determine efforts that can be made in the future and can be used as a policy maker for the Government in maintaining the national food security chain. This study uses time series data on rice harvests in Pamekasan, Madura, for 2007-2023 using the Support Vector Regression (SVR) model. The results of several trials have shown that the application of the SVR model for forecasting rice harvests in 2024 has produced good accuracy with a relatively low MAPE error rate of 3.97\%, and the rice harvest has reached an average prediction of 15470.08 tons with an average actual data of 7937.884 tons. Therefore, applying this SVR model can be recommended for predicting future rice harvests.

Determination of Optimal Water Requirement for Sweet Corn Crop Based on Meteorological Data and Plant Growth Parameters

Maize (Zea mays L.), or corn, is the world’s leading cereal crop and ranks third in importance after rice and wheat. It is a primary food source for humans and livestock and a raw material in various industries. To reduce dependence on corn imports, Malaysia has initiated large-scale local cultivation. However, the maize industry faces challenges from waterlogging and water scarcity due to the tropical climate, which causes droughts and floods, impacting maize production. This study aims to improve crop water requirement (CWR) estimations for maize using CROPWAT, considering growth stages and soil variability, and validate irrigation management strategies. Based on 30 years of climatic data from MetMalaysia, evapotranspiration (ETc) was estimated using CROPWAT V8. Experimental plots with four irrigation water application (IWA) treatments were used to validate ETc: T1 (50% ETc), T2 (75% ETc), T3 (100% ETc), and T4 (125% ETc). Crop growth parameters were assessed at four growth stages: plant height, stem diameter, shoot fresh weight, and kernel moisture. Results showed T4 (451.07 mm/season) had the highest growth rate and met all hybrid corn growth standards set by the Department of Agriculture, Ministry of Agricultural and Food Security (MAFS). In contrast, T3 (100% ETc) was insufficient for sweet corn, failing to meet several standards. Thus, T4 (125% ETc) proved the most effective IWA practice, particularly for areas within a 30 km radius of the Subang weather station.

Prolonging mulberry leaf longevity with silver-doped copper oxide nanoparticles: a postharvest approach

Mulberry is crucial in silkworm rearing as it provides the primary food source for silkworms, directly impacting the quality and quantity of silk production. This, in turn, supports the global silk industry, which significantly contributes to the economies of many countries through the production of textiles and garments. Postharvest mulberry leaf preservation is required to ensure a continuous and reliable food supply for silkworms, especially during the rainy season when fresh dry leaves are not readily available. Proper preservation techniques will ensure the leaves' nutritional quality, which is essential for the health and productivity of silkworms, ultimately enhancing the efficiency and profitability of silk production. Due to their potent antimicrobial properties, silver-doped copper oxide nanoparticles (Ag-CuO NPs) are explored as preservatives. When used for preservation, Ag-CuO NPs effectively retained primary metabolites, chlorophyll, proteins, and carbohydrates, preserving the leaves' texture and nutritional value. Additionally, the synergistic action of enzymatic antioxidants and carotenoids with Ag-CuO NPs mitigated reactive oxygen species (ROS) damage, delayed senescence, and maintained cellular integrity. Postharvest leaves treated with Ag-CuO NPs supported optimal silkworm larval growth, resulting in higher growth indices, cocoon weights, and silk yields, comparable to fresh leaves. This nanoparticle-based approach extends leaf viability up to seven days, offering a sustainable and non-toxic preservation method with reduced environmental impact, enhancing the efficiency of sericulture practices.

TAENIASIS PREVALENCE AND ASSOCIATED FACTORS IN BORRONG COMMUNE, DEMSA LGA, ADAMAWA STATE, NIGERIA

Taeniasis represents a human parasitic infection originating from three distinct tapeworm species: Taenia saginata, commonly known as the beef tapeworm, Taenia solium, referred to as the pork tapeworm, and Taenia asiatica, identified as the Asian tapeworm. The primary transmission of these parasitic organisms occurs when individuals consume poorly cooked meat, specifically raw or insufficiently cooked beef for T. saginata, or pork for both T. solium and T. asiatica. This research aims to understand how common a particular health issue is in the Borrong Community and explore what factors might be related to its occurrence in this specific area of Adamawa State, Nigeria. 376 people were picked by chance to participate in the research, which covers three villages: Borrong, Dilli, and Gwamba. Data analysis was conducted using SPSS Statistics Version 20. The 376 people studied, 129 were carriers of taeniasis infection with 34.3% infection rate. The highest infection occurred in age group 30-39 years in both males 18(51.4%) and females 16(43.3%), and is lower in ages 1-9 years in both males 1(11.1%) and females 1(9.1%). The source of water supply, hand washing habit after defecation, educational level, and pigs roaming freely, were significantly associated with taeniasis infections. Due to scarce feed resources, pigs in Africa are commonly allowed to move around freely, using waste as their primary food source. Increasing awareness about local risk factors such as pig management, education, and personal hygiene is crucial. This will play a great role in suppressing the taeniasis prevalence.

New Approaches to the Ecology of Triatoma sordida in Peridomestic Environments of an Endemic Area of Minas Gerais, Brazil.

Triatoma sordida is a native South American species and the most frequently captured triatomine in artificial environments in Brazil. Although considered a secondary vector of Trypanosoma cruzi, it is typically associated with low infection rates. To investigate its role in an endemic area for Chagas disease in northern Minas Gerais, Brazil, we employed a multidimensional approach that combined triatomine capture data with quantitative and qualitative analyses of T. cruzi. A total of 1861 T. sordida specimens were captured, of which 1455 were examined and 210 (14.4%) were found to be infected with T. cruzi. The most prevalent discrete typing unit (DTU) was TcI (80%), followed by TcII (8%), TcV (5%), and TcIII (3%). Molecular techniques provided new insights into the ecology of T. sordida, revealing a higher infection rate than previously reported and a parasitic load lower than that observed in other quantified species. Chickens were confirmed as the primary food source, playing an epidemiological role in maintaining infected insects with four T. cruzi DTUs. The observed diversity of T. cruzi DTUs suggests a lack of environmental segregation, likely due to the extensive movement of various host species between wild and domestic habitats, resulting in overlapping transmission cycles.

Effects of Drip Irrigations with Different Irrigation Intervals and Levels on Nutritional Traits of Paddy Cultivars.

Rice serves as the primary food source for the majority of the world's population. In terms of irrigation water, the highest volume of irrigation water is utilized in paddy irrigation. Excessive water use causes both waste of limited water resources and various environmental problems. The drip irrigation method with high water use efficiency will reduce both the need for irrigation water and the environmental footprint of paddy production. This study was conducted to investigate the effects of two different irrigation intervals (2 and 4 days) and four irrigation levels (150%, 125%, 100%, and 75% of evaporation from a Class-A pan) on the nutritional traits of three different paddy cultivars (Ronaldo, Baldo, and Osmancık). Increasing irrigation intervals and decreasing irrigation levels reduced the nutritional properties (protein, oil, starch) of the rice grains. In addition, increasing irrigation levels also increased the phytic acid and dietary fiber contents. The highest protein (7.14%) and total starch (87.10%) contents were obtained from the 150% irrigation treatments. The highest amylose content (20.74%) was obtained from the 75% irrigation treatment. In general, it was found that irrigation levels should be applied at 125% and 150% to increase the mineral content of rice grains. Although water deficits decreased the nutritional properties of the paddy cultivars, drip irrigation at an appropriate level did not have any negative effects on nutritional traits.

Quantitative analysis of the polar cod (Boreogadus saida) hepatic proteome highlights interconnected responses in cellular adaptation and defence mechanisms after dietary benzo[a]pyrene exposure.

Quantitative analysis of the polar cod (Boreogadus saida) hepatic proteome highlights interconnected responses in cellular adaptation and defence mechanisms after dietary benzo[a]pyrene exposure.

ECLIPTA ALBA: A Review of Pharmacological Activity with Phyto-Constituents

Plants are the primary source of food, shelter, and various remedial approaches, they are being in use for treating various kinds of human ailments across the world since the ancient times. The review describes the innumerable herbal medicinal plants named Eclipta alba hassk (Asteraceae) which is commonly known as Bhringraj and false daisy. This plant is known for its extra –ordinary therapeutic properties. It is one of most widely used plant in traditional systems of medicines such as Ayurvedic, Unani, siddha, Homeopathy, Chinese, and folk. Bhringraj (Eclipta prostrate or eclipta alba) is a famous herb known for known for its benefits and usage in hair growth and liver disorders. This article highlights chief constituents, extraction procedure, phytochemistry, pharmacological activities, phytochemical screening& toxicity studies of Eclipta alba. Each part of this medicinal plant contains many important phytochemical constituents such as flavonoids, steroids, saponins. E. alba exhibites many other important biological properties such as anticancer, antibacterial, antiviral, antistress, and immunomodulatory. It increases the production of bile from the liver, improves liver functions, reduce constipation and correct digestion and enhance metabolism.