Indian Institute of Maize Research
Recent publications
Maize (Zea mays L.) is an important cereal in many developing countries, ensuring staple food for millions of people. However, the presence of high-level phytic acid in maize kernels is one of the major nutritional concerns. Reduction of phytic acid has become a major challenge in breeding programmes to increase the nutritional quality of foods and feeds. In the current investigation, an attempt was made to develop low-phytate maize genotypes by incorporating lpa1 and lpa2 genes associated with lower phytic acid (PA) and inorganic phosphorous (Pi) levels in the background of well-adapted agronomically elite tropical maize inbred lines, BML6 and BML45, showing high phytate contents in kernels. The stepwise transfer of lpa1 and lpa2 genes using marker-assisted backcross breeding (MABB) technique was undertaken. The foreground selection in F1 and the segregating generations (BC1F1 and IC1F1–IC1F2) were carried out using umc2230-linked STMS marker and co-dominant SNP. The background selections in segregating generations were performed with genome-wide simple sequence repeats (SSRs). Four distinct BC1F1 lines of BML6 × LPA1 (Cross 1), BML6 × LPA2 (Cross 2), BML45 × LPA1 (Cross 3), and BML45 × LPA2 (Cross 4) having lpa1 and lpa2 genes with the highest recurrent parent genome recovery (RPGR) were intercrossed to develop the IC1F1 and IC1F2 populations. Further, the lpa1 and lpa2 pyramided lines were examined for PA and Pi contents. The IC1F2 lines, #3390 (1.75 ± 0.087 mg/g) of BML6 and #3990 (1.52 ± 0.091 mg/g) of BML45, had significantly lower levels of PA as compared to recurrent parents and on par agronomic performance, whereas the kernel Pi level was found to be the highest (#3390 of BML6: 1.91 ± 0.202 mg/g; #3990 BML45: 1.93 ± 0.066 mg/g in BML45). The improved lines of BML6 and BML45 have the potential to be developed as cultivars for target agro-climatic zones as well as useful genetic stocks for breeding low-phytate maize cultivars. The results hold great significance to alleviate malnutrition issue in India and the world through biofortification of maize.
Maize is an important cereal crop in India and a target crop for bioethanol production. However, significant post-harvest losses occur in maize due to unfavourable climatic conditions or lack of proper storage facilities. Such damaged/spoiled grains are unfit for human consumption but can be either used as feedstock for animals or can be used as low-cost substrate for bioethanol production as they contain a considerable amount of starch (40–60%). The present study was carried out for liquefaction, saccharification and fermentation of damaged and spoiled corn grains for bioethanol production. Crude α-amylase from bacterial isolate AM1 with activity of 8.83 IU/ml and glucoamylase from Aspergillus sp. with activity of 27.71 IU/ml were used for liquefaction and saccharification, respectively. The optimal substrate concentration for enzymatic hydrolysis was found to be 12%. Enzymatic liquefaction of 12% damaged corn grains resulted in an efficiency of 64.54% of liquefaction, employing 3% (v/v) of α-amylase after 2.5 h of liquefaction. A maximum saccharification efficiency of 50.66% was identified with a saccharifying enzyme dose of 1.5% (v/v) with a saccharification time of 48 h and substrate concentration of 12%. At optimized conditions, the maximum ethanol content of 2.9% (v/v) was obtained under Separate Hydrolysis and Fermentation (SHF). In the case of Simultaneous Saccharification and Fermentation (SSF), a maximum ethanol content of 3.6% (v/v) was obtained. Graphical abstract
The synthesis of an array of carbon nanomaterials (CNMs) from agro-industrial wastes is a growing area of research, which offers great potential for sustainable nanotechnology and waste minimization. The novel approach employs a broad spectrum of agro-industrial wastes, including agro-residues, food processing by-products, and forestry residues as renewable feedstocks for CNMs production. Since there are several methods for synthesis, for example, pyrolysis, hydrothermal carbonization, and chemical vapor deposition, we can make these wastes into carbonaceous materials with the desired properties and functionalities by controlling the process. The characterization techniques, such as microscopy and spectroscopy, and even computational modeling, allow for the comprehensive study of nanomaterial structure, morphology, and efficacy, which can be used to further optimize the materials for unique applications. Biocompatibility and toxicity studies are the compliance tools to ensure the safety of CNMs in biomedical, environmental, and industrial sectors, and this in turn guides regulatory compliance and risk management goals. The widespread application of CNMs derived from agro-industrial wastes covers different fields, including energy storage and conversion, pollution treatment, catalysis, biomedical engineering, agriculture, and material science. They possess important features like high surface area, chemical stability, mechanical strength, and electrical conductivity. These features have resulted in innovative solutions in areas like supercapacitors, water purification, drug delivery, and soil improvement. Yet there are still some issues, such as upscaling, cost-effectiveness, and regulatory compliance, which the research is trying to solve by developing a variety of feedstocks, finding sustainable synthesis strategies, and advancing characterization methods to realize the full potential of CNMs. This area of study, however, offers good prospects by addressing such challenges as well as taking advantage of emerging opportunities. There is no doubt that this field of CNMs will redefine the way we manage waste, boost the development of new technologies, and build a circular economy model that is based on efficiency in resource utilization and sustainability.
This chapter examines how breakthrough technology can address climate change and promote sustainability. It begins by reviewing climate change and emphasizing the need for prevention. According to the chapter, improved materials, blockchain, and artificial intelligence may be used in climate adaptation. These technologies can boost agricultural yields, reduce water consumption, and boost food security in a changing climate. Precision agriculture, hydroponics, and vertical farming may transform agriculture and ensure sustainable food production. Energy companies emphasize intelligent grids, energy storage, and renewable energy technology as key to a low-carbon economy and energy resiliency. These technologies help reduce greenhouse gas emissions and provide a sustainable energy future by switching from fossil fuels to renewable energy. It also monitors and manages climate-related threats using digital platforms, big data analytics, and IoT devices. These tools simplify adaptive decision-making, early warning, and community resilience. According to the chapter, enterprises, governments, and communities must work together to use new technology efficiently. It emphasizes the importance of inclusiveness, data privacy, and ethics when employing new climate adaptation technology. The chapter finishes by highlighting the transformative potential of new technologies to create a sustainable future and calling for coordinated efforts to maximize their benefits and resolve related concerns.
In order to meet the rising need for edible grains induced by a mushrooming human population over the past few decades, agriculture has undergone a modernization from traditional to contemporary. Monoculture, which is utilized in contemporary agriculture for intensive grain production system, requires a lot of land preparation, application of pesticides and fertilizers. These processes further imbalances the already weak below-ground and above-ground networks of agroecosystem and also worsen many benefits provided by biodiversity within agroecosystems, such as those related to biological control. As a result, conservation agriculture has been actively advocated as a useful alternative to tillage-based conventional agriculture and a crop husbandry practice that may reconcile these occasionally conflicting objectives. Conservation agriculture is a management strategy that permits permanent soil cover, minimize soil disturbance and, enhance spatio-temporal crop species diversity by the use of sustainable farming methods, which are encouraged as a means of reducing climate change and might also facilitate pest management. The author cites relevant research showing how arthropod pests and natural enemies are influenced by conservation agriculture practices, which not only have a bearing on pest management but also reduce the effects of climate change. Literature analysis reveals crop diversification, particularly the introduction of perennial species, cover cropping, tillage techniques that preserving crop residue, the use of organic fertilizers like compost, manure, and water management techniques are all promising methods for reducing pests and enhancing biological control. These techniques can strengthen crops' resistance to insect attacks and broaden natural enemies' diversity, thus reducing the impact of climate change on the breakdown of biological regulation.
Recessive shrunken2 (sh2)-based sweet corn is preferred worldwide as it possesses higher sugar and extended shelf life. However, traditional sh2-based sweet corn is poor in vitamin A and vitamin E. Here, parental lines of two sh2-based sweet corn hybrids, viz. PSSC-2 and ASKH-2, were targeted for introgression of β-carotene hydroxylase 1 (crtRB1) and γ-tocopherol methyltransferase (vte4) genes through marker-assisted backcross breeding. Seeds with sh2sh2sh2 genotype in the endosperm were selected based on the shrunken phenotype in BC1F1, BC2F1 and BC2F2 generations. Gene-based markers, viz. 3′-TE-InDel and 118-InDel specific for crtRB1 and vte4, respectively, were successfully utilized for foreground selection in BC1F1, BC2F1 and BC2F2. Reconstituted hybrids showed high provitamin A (proA: 19.52 ± 0.52 µg/g) with a maximum of 7.8-fold increase over original hybrids (ASKH-2 and PSSC-2: 3.33 ± 0.28 µg/g). High α-tocopherol (20.75 ± 0.44 µg/g) and α/γ-tocopherol ratio (0.55 ± 0.02) with an average enhancement of 2.3- and 1.7-fold, respectively, was recorded among reconstituted hybrids over original versions (α-tocopherol: 9.21 ± 0.33 µg/g, α/γ-tocopherol ratio: 0.31 ± 0.01). The average yield of reconstituted hybrids (11.40 ± 0.22 t/ha) was at par with the original sweetcorn hybrids (11.60 ± 0.20 t/ha). This is the first report of stacking sh2, crtRB1 and vte4 genes to improve nutritional quality in sweet corn. These biofortified sweet corn hybrids hold immense significance to alleviate micronutrient malnutrition.
Viral diseases severely impact maize yields, with occurrences of maize viruses reported worldwide. Deployment of genetic resistance in a plant breeding program is a sustainable solution to minimize yield loss to viral diseases. The meta-QTL (MQTL) has demonstrated to be a promising approach to pinpoint the most robust QTL(s)/candidate gene(s) in the form of an overlapping or common genomic region identified through leveraging on different research studies that independently report genomic regions significantly associated with the target traits. Here, we employed an MQTL approach by targeting 39 independent research investigations aimed at genetic dissection of the resistance in maize against 14 viral diseases. We could project 27 % (53) of the total 196 QTLs onto the maize genome. Our analysis found a robust set of 14 MQTLs on chromosomes 1, 3 and 10 that explain significant proportion of the variations for resistance against 11 viral diseases. Marker trait associations (MTAs) identified from genome-wide association studies (GWAS) provide evidence in support of the two MQTLs (MQTL3_2 and MQTL10_2) playing crucial roles in viral disease resistance (VDR) in maize. A total of 1,715 candidate genes underlie the identified MQTL regions, of which, we further examined the constitutively-expressed genes for their involvement in various metabolic pathways. The involvement of the identified genes in the antiviral resistance mechanism renders them a valuable genomic resource for allele mining and elucidating plant-virus interactions for maize research and breeding.
Fall armyworm (FAW) Spodoptera frugiperda (J.E. Smith) is an invasive insect pest that poses a severe threat to maize production affecting the livelihood and food security of small holder farmers in African and Asian countries. Host plant resistance is one of the potential methods for FAW management in a sustainable manner. Identification of genotypes with different categories of resistance is important to diversify the basis of resistance to FAW. This study aimed to characterize the antixenosis and antibiosis resistance through oviposition, developmental and survival parameters of FAW on 16 diverse maize genotypes. Antixenosis was assayed under no-choice and multi-choice conditions, while antibiosis was assayed in bioassays in which larvae were reared on leaf tissue. Genotype CML 336 showed strong antixenosis both under no-choice and multi-choice conditions while the genotypes DMRE 63, CML 59, CML 60, CML 70, and CML 501 exhibited antixenosis under multi-choice conditions. Genotypes CML 122, CML 330, CML 332 and CML 337 showed antibiosis characteristics and resulted in prolonged duration of the larval period. Further, the low larval survival (%), larval weight, and pupal weight when fed on DMRE 63 indicated that antibiosis could be conferring resistance to FAW. Based on GGE biplot analysis, the resistant genotypes (DMRE 63, CML 70, CML 337, and CML 122) were grouped along with group one parameters namely larval period and pupal period. The present study provides information on different categories of resistance in maize genotypes and results could be used in breeding programmes focusing on maize resistance to FAW.
Wheat is among the most produced grain crops of the world and alone provides a fifth of the world’s calories and protein. Wheat has played a key role in food security since the crop served as a Neolithic founder crop for the establishment of world agriculture. Projections showing a decline in global wheat yields in changing climates imply that food security targets could be jeopardized. Increased frequency and intensity of drought occurrence is evident in major wheat-producing regions worldwide, and notably, the wheat-producing area under drought is projected to swell globally by 60% by the end of the 21st century. Wheat yields are significantly reduced due to changes in plant morphological, physiological, biochemical, and molecular activities in response to drought stress. Advances in wheat genetics, multi-omics technologies and plant phenotyping have enhanced the understanding of crop responses to drought conditions. Research has elucidated key genomic regions, candidate genes, signalling molecules and associated networks that orchestrate tolerance mechanisms under drought stress. Robust and low-cost selection tools are now available in wheat for screening genetic variations for drought tolerance traits. New breeding techniques and selection tools open a unique opportunity to tailor future wheat crop with optimal trait combinations that help withstand extreme drought. Adoption of the new wheat varieties will increase crop diversity in rain-fed agriculture and ensure sustainable improvements in crop yields to safeguard the world’s food security in drier environments.
Seed is the most basic entity in agriculture that governs the overall value of crop yield and crop health. As growers expect high-quality and genetically pure seed, meticulous seed certification and quality control strategies are inevitable. Traditional methods of physical and genetic purity assessment are laborious, error - prone and time - consuming. Recently, hyperspectral imaging has attracted great attention as a non-destructive and easy method for seed quality and safety assessment. Modern hyperspectral imaging systems produce immense data that carries abundant information, that can be converted into actionable insights. Machine learning and deep learning approaches are some proven approaches for analyzing massive, complex datasets. Hence, coupling the hyperspectral imaging system with machine learning can bring ultimate precision to seed quality analysis. Therefore, this comprehensive review discusses the capability and significant applications of this integrated system in seed classification and grading, seed viability and vigor detection along with the pathological diagnosis and prognosis of insect infestation in seeds. The research carried out in the relevant areas during the last 10 years has been reviewed in scientific databases including PubMed, Web of Science, and Scopus. The first part of this review focuses on the evolution of the hyperspectral imaging system, its principles, and how to merge the chemometric data with that of the hyperspectral data set. The second part would deeply focus on the utility of machine learning modeling based on the hyperspectral data set generated for the prediction of seed quality attributes with high accuracy. The amalgamation of advanced machine learning techniques with hyperspectral imaging could be a game changer for rapid and robust seed quality assessment.
This study investigates the potential of chromium (VI) resistant bacterial isolates to alleviate heavy metal stress in fodder maize plants and enhance phytoremediation. Twenty-one bacterial strains were isolated from contaminated water, with five strains; Bacillus thuringiensis (BHR1), Bacillus cereus (BHR2), Enterobacter cloacae (BHR4), Bacillus pumilus (BHR5), and Bacillus altitudinis (BHR6) selected based on their significant plant-growth promoting (PGP) traits and heavy metal tolerance. Under chromium (Cr VI) stress, the BHR1 strain significantly improved seed germination, seedling length and vigor index of fodder maize variety (J 1007) especially at 150 mg/L Cr (VI), where these parameters increased by 3.75, 3.23 and 6.44 folds, respectively. After 60 days, BHR1 also enhanced shoot and root lengths by 4.91 and 4.06 folds, respectively and increase fresh and dry biomass, especially at higher Cr (VI) concentrations. Photosynthetic pigments, chlorophyll a and b, were also elevated by 3.04 and 2.26 times, respectively. Additionally, BHR1 reduced oxidative stress markers, including proline and malondialdehyde (MDA), and decreased electrolyte leakage, thus improving membrane stability. The strain further increased antioxidant enzyme activities and chromium uptake in root and shoot tissues, enhancing the translocation factor by 95 %. This suggests that BHR1 can significantly promote fodder maize growth and accelerate chromium removal from contaminated soil, offering valuable insights into plant-microbe interactions under Cr (VI) stress.
Genetic engineering (GE) is a powerful tool that allows the introduction of foreign DNA sequence(s) into plants resulting in the development of improved crops. Adoption of such genetically modified (GM) crops in the last two decades has been shown to benefit agriculture immensely, viz., higher crop yields with reduced input costs, development of crops resistant to a wide range of biotic and abiotic stresses, crops with improved nutritional quality, better shelf-life, and hence greater food security. GM crops developed using transgenic technology are currently grown in 29 countries spread across the globe, covering more than 190 million hectares of land. Among various commercialized GM crops, herbicide-tolerant and insect-resistant GM cotton, soybean, and maize have been in cultivation for more than 20 years in some parts of the world, proving the safety and benefits of such crops. However, in India, insect-resistant cotton is the only GM/transgenic crop approved so far for commercial cultivation, while Bt Brinjal developed in India is cultivated in Bangladesh. More recently, the Indian government allowed the environmental release of transgenic mustard, Dhara Mustard Hybrid-11, developed by a public sector institution. Further, several other crops are in the pipeline or awaiting regulatory approval. Considering the numerous challenges posed by agriculture to produce enough quality food to feed the growing population with depleting land availability, reduced water and other resources, GM crops have a huge potential to contribute to the food security of India and address global warming and other environmental issues. However, the adoption of GM crops having foreign gene(s) raises public concerns related to the potential adverse effect on the environment and human health, etc. To address such concerns, the adoption of alternative tools like genome editing (SDN-1 and SDN-II type) may be a viable approach since the transgene-free crop plants with the desirable traits can be generated using this novel tool. In this chapter, we briefly discuss the importance of GM crops in the context of agricultural sustainability and food as well as nutritional security in the Indian scenario.
Maize is a highly versatile crop holding significant importance in global food, feed and nutritional security. Grain yield is a complex trait and difficult to improve without targeting the improvement of grain yield attributing traits, which are relatively less complex in nature. Hence, considering the erosion in genetic diversity, there is an urgent need to use wild relatives for genetic diversification and unravel the genomic regions for grain yield attributing traits in maize. Thus, the current study aimed to identify quantitative trait loci (QTLs) linked with grain yield and yield attributing traits. Two BC2F2 populations developed from the cross of LM13 with Zea parviglumis (population 1) and LM14 with Zea parviglumis (population 2) were genotyped and phenotyped in field conditions in the kharif season. BC2F2:3 lines in both populations were phenotyped again for grain yield and attributing traits in the spring season. In total, three QTLs each for ear height (EH), two QTLs for flag leaf length (FLL) and one QTL each for ear diameter (ED), plant height, flag leaf length (FLL), flag leaf width and 100 kernel-weight were identified in population 1. In population 2, two QTLs for kernel row per ear (KRPE) and one QTL for FLL were detected in. QTLs for EH, FLL and KPRE showed consistency across seasons. Among the identified QTLs, six QTLs were found to be co-localized near identified genomic regions in previous studies, validating their potential in contributing to trait expression. The identified QTLs can be utilized for marker assisted selection, transferring favorable alleles from wild relatives in modern maize.
Use of diverse germplasm for generating heterotic hybrids is the foremost requirement in maize. The present study was conducted by using a diverse set of inbred lines and the line × tester method was applied to identify best performing lines and to group QPM inbred lines into different heterotic groups. The test crosses, developed by following line (66) × tester (CML 161 and CML 165) mating design, were evaluated during winter 2013, rainy 2014 and 2015 seasons at Begusarai and Ludhiana, respectively. Based on the specific combining ability, the lines were categorized into two heterotic groups. Out of 66 novel inbreds, 18 lines with significant SCA with CML165 were classified in group A, 16 inbreds with significant SCA with CML161 were classified in group B and 20 inbreds with significant GCA were classified in group (AB). Nine inbred lines were selected based on their positive GCA values and pedigree crosses were developed in rainy season in 2017. Three crosses were made in heterotic group A and four crosses were in group B for synthesizing new inbred lines by using pedigree method. Heterotic grouping based inbred evaluation trial and biochemical analysis were carried out to estimate per se yield potential of developed lines and to estimate tryptophan content. QIL-4-2491 (Group-A) and QIL-4-2401 (Group-B) were the top yielders. A total of 25 crosses were made among the heterotic groups (A and B) by using 22 lines from groups A and B and three best performing hybrids were identified.
Indo-Gangetic Plains (IGP) of South Asia is known for cereal (rice, wheat, and maize)-based major agri-food systems, which meet food requirement of 50% population in the region. Continuous cultivation of monotonous rice-wheat (RW) cropping system with traditional practices since the last six decades is showing threats to the systems’ sustainability. Future increase in food grain production might not be expected with business-as-usual practices. As per the Intergovernmental Panel on Climate Change (IPCC), the crop production in South Asia is expected to decrease by 30% particularly in cereal crops (rice, wheat, maize) by end of twenty-first century. South Asian farmers are mostly smallholders, their adaptive capacities are limited, and hence they are most vulnerable to climate change. Therefore, climate-smart agriculture (CSA) practices, comprised of three pillars (food security, adaptive capacity, and mitigation potential), are essential to design the new generation cereal systems to reduce farmers’ vulnerability to climate change. Sustainable intensification through the integration of short-duration legumes and by replacement of input exhaustive crops are required to maintain the systems’ sustainability in the region. Based on the on-station and off-station trials in South Asia, CSA-based modules had a potential to increase the system productivity and profitability by 5–15% and 20–25% in major cereal (rice, maize, and wheat) based agri-food systems vis-a-vis reduced the global warming potential by 15–35%. CSA-based production systems are found to be more resilient by improving soil quality (SOC—50–100%; NPK—30–50%). Smart application of input (through subsurface drip irrigation) saved irrigation water (~45%) and N (~20%) with slightly higher yields compared to conventional tillage (CT)-based systems. CSA layered with nutrient management tools like Nutrient Expert (NE) and GreenSeeker (GS) reduced the N input by 15–20%, increased crop yield by 4–8% and reduced the global warming potential by about ~3% in rice and ~15% in wheat. Results showed wider practical applicability and scalability, which may pave a way paradigm for scaling up cereal systems in South Asia in near future.
Maize-based crop systems are promoted in large scale in South Asia because they are more sustainable and efficient than rice-based systems. In the present study, using two combinations of crop residue management practices (CRM) with four precision nitrogen (N) management (PNM) systems, we assessed the impacts on soil physicochemical characteristics [soil organic carbon (SOC), bulk density (BD), soil penetration resistance (PR)] and crop yields in 6 years old continuous zero tillage (ZT) practices under maize-wheat-mungbean cropping system in a sandy loam soil of northwestern India. The highest SOC (5.73 g/kg) was observed in Zero Tillage with Residue Retention (ZT + R) plots. Zero-tillage with residue retention (ZT + R) significantly reduced the bulk density over the zero-tillage with no residue retention (ZT-R) across the soil depth. The bulk density in ZT + R was 6.5 and 10.7% lower at 0–15 cm and 15–30 cm soil depth, respectively, than under ZT-R. The penetration resistance (PR) was significantly lower in ZT + R than in ZT-R across the soil depth. Soil organic carbon (SOC) in ZT + R was 7.4% higher at 0–15 cm depth and 11.9% higher at 15–30 cm depth than under ZT-R treatment. Among PNM treatments, the sequence of treatments in SOC content was 50%N + Green Seeker (GS) >33%N + GS > RDN > 70%N + GS. The system productivity (maize equivalent yield) under ZT + R in combination with 50%BN + GS was 15.0% higher than crops grown under ZT-R with RDN. The wheat equivalent yield under the ZT + R treatment is found to be higher (5.97) in the 50%BN + GS, which was 18% higher than the recommended dose of nitrogen treatment (5.04) and 28% higher than the 70%BN + GS treatment (4.68). Results demonstrated that plots with residue retention performed better, showing a 10% increase in system productivity. The study concludes that a ZT-based system with maize-based crop rotations (MWMb) with crop residue retention and precision nitrogen management can improve soil properties and system productivity in northwestern India.
Background and Objective Fermentation has a huge potential to improve the nutritional and functional properties by using the biological activity of the grain itself. The current study was performed to optimize the conditions for the fermentation of Quality Protein Maize (QPM) and maize further; the impact of fermentation treatment on the bio‐techno‐functional properties of QPM and maize flour was assessed. Findings The technological properties, including oil absorption capacity, water solubility index, emulsion activity and stability, foaming capacity and stability, protein solubility, gel consistency, and least gelation concentration, were found to be increased with the fermentation treatment, while water absorption capacity, paste clarity, and swelling power observed a decline. The findings suggested elevated levels of all the bioactive constituents with the fermentation process. The modulations at the molecular level were confirmed by the scanning electron micrographs of fermented flour. Further, changes in the peaks of Fourier transform infrared spectra and the emergence of new peaks were also reported. Conclusions The fermentation treatment altered the techno‐functional properties, bioactive constituents, macromolecular structure, and molecular interactions of QPM and maize flour. Significance and Novelty Limited literature is available dedicated to the assessment of the nutritional, techno‐functional, and phytochemical components in QPM and maize as influenced by the fermentation process. Further, changes in the structural and molecular interactions in the flour components due to fermentation treatment have not been studied comprehensively.
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27 members
N. Sunil
  • Winter Nursery Centre, Hyderabad
Dharam Chaudhary
  • Department of Biochemistry
Abhijit Das
  • Department of Genetics
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