<div>Background: MicroRNAs (miRNAs) are active regulators of numerous biological and physiological processes and play an important role in the regulation of animal ovaries and other reproductive related organs. To understand the molecular mechanisms of miR-10 family, we investigated the molecular characteristics and the relative expression of sheep miR-10a and miR-10b (miR-10a/b) and conducted bioinformatics analysis. 
 
Methods: During the period 2018-2019 total of 20 samples including blood and tissues such as hypothalamus, pituitary and ovary were collected from the Hu sheep raised in the National Meat Sheep Experimental Station of China (Luoyang City, Henan Province, China). Blood was collected from jugular vein by vacuum and anticoagulation blood collection tube and stored in refrigerator at -20&deg;C. The tissues were placed into the cryopreservation tube treated with Diethy pyrocarbonate (DEPC) water and stored in liquid nitrogen. All the samples were processed for isolation and confirmed with biochemical analysis and Polymerase chain reaction (PCR) and Real-time fluorescence quantitative PCR. 
 
Result: The target genes were predicted by three kinds of target gene predicting software. The function of target genes and their involved pathways were obtained by gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The relative expression of miR-10a/b in sheep ovary was extremely significantly higher than that in hypothalamus and pituitary gland (P &lt; 0.01). The relative expression of miR-10b in ovary or pituitary was extremely significantly higher than that of miR-10a (P &lt; 0.01) and the relative expression of miR-10b in hypothalamus was significantly higher than that of miR-10a (P &lt; 0.05). These results serve as a foundation for further study on the Sheep miR-10 family.</div>

<div>Cloning, Characterization and Bioinformatics Analysis of the Sequences of miR-10a and miR-10b in Sheep (Hu sheep)</div>

Background: Varietal differences in metabolite composition play a crucial role in determining agronomic traits, nutritional quality and stress resilience in Solanum tuberosum.&nbsp; 
 
Methods: Three potatoes varieties; Longshu 7, Longshu 10 and Longshu 14 were selected and bred by the at the Potato Research Institute of Gansu Academy of Agricultural Sciences between December 2021 to December 2023. Thereafter, comparative metabolomics analysis of three new potato varieties (LS7, LS10 and LS14) was undertaken against the well-established Atlantic cultivar. We employed a bioinformatics-based experimental approach to analyze the metabolomic data obtained from the three new potato varieties (LS7, LS10 and LS14) and the Atlantic cultivar. Metabolite profiling was performed using high-throughput liquid chromatography-mass spectrometry (LC-MS) techniques. Differential metabolite analysis and pathway enrichment analysis were conducted to identify significant metabolic differences and enriched pathways among the varieties.&nbsp; 
 
Result: Results revealed substantial differences in metabolite composition and pathway enrichment between the new potato varieties and the Atlantic cultivar. Metabolites involved in diverse metabolic pathways, including glucoside and hydroxyproline in LS7, kaempferol and ascorbic acid in LS10 and phenyl-butyryl-glutamine and ascorbic acid in LS14, exhibited significant upregulation or downregulation compared to the Atlantic cultivar. Pathway enrichment analysis highlighted the prominence of ABC transporters across all comparisons, suggesting their universal role in mediating cellular processes and stress responses in potato varieties. In conclusion, these findings contribute to our understanding of potato metabolism and pave the way for the development of novel breeding approaches to meet the evolving demands of global agriculture and food security.

Comparative Metabolomics Analysis of 3 New Potato Varieties against the Atlantic Cultivar; Bioinformatics based Experimental Study

Background: To investigate the differences between leptin gene in Eothenomys Miletus and other 55 mammal species, this study conducted a comparative analysis of multidimensional characteristics and adaptive differentiation of leptin genes. 
 
Methods: In this study, molecular biology experimental strategies have been used to extract and reverse transcription, gene cloning and sequencing of E. miletus and bioinformatics evaluation techniques have been used to analyze the sequence and structure, multi-sequence alignment and evolutionary evaluation of E. miletus and ecological and distribution statistical strategies had been used to analyze the leptin genes of 56 mammalian species such as E. miletus. 
 
Result: Leptin gene in E. miletus contained a Sec/SPI signal peptide, with &alpha;-helices dominating its structure. A model was constructed using leptin-LepR trimer (8 &times; 80.1. C leptin) as template. It encodes 127 amino acids with high proportions of leucine and serine; its molecular formula is C824H1353N221O252S8&nbsp;(2658 atoms) with molecular weight of 18644.62 and theoretical isoelectric point of 5.86. The protein is unstable and hydrophilic, yet more hydrophobic than Tupaia chinensis and Homo sapiens. E. miletus was genetically close to Microtus, distant from Lagomorpha and clusters with temperate Rodentia. Its codon preference differed from Lagomorpha, with moderate GC content, GC3 content and ENC values. Motifs 1-5 were conserved in its leptin. Functional annotation shows regions related to signal peptide, leptin and extracellular domains. The &omega; value of ~0.5661 suggests evolutionary conservation. These results provide basis for exploring leptin gene evolution in E. miletus and mammals, offering perspective on mammalian adaptation to extreme environments and high-altitude protection.

Multidimensional Characterization and Adaptive Differentiation of Leptin Gene in Eothenomys miletus: Based on Bioinformatics and System Evolution Analysis

Background: The present study aimed to elucidate the fundamental composition of the CDS region sequence of UCP1 gene in Eothenomys miletus, as well as the physicochemical properties, higher-order structure and structural domains of the UCP1 protein. Additionally, we analyzed the selection pressure on the UCP1 gene in mammals inhabiting different latitudes, providing a data foundation for further exploration of the UCP1 gene and its role in mammalian environmental adaptation. 
 
Methods: The CDS region sequence of UCP1 gene was cloned using PCR and the structure and function of the UCP1 gene were characterized employing a bioinformatics platform. The UCP1 gene of Eothenomys miletus was compared with other species for sequence similarity and phylogenetic tree construction. Furthermore, selection pressure on UCP1 genes from mammals at different latitudes was analyzed. 
 
Result: UCP1 gene encodes a protein comprising 307 amino acids, located in the mitochondria, with a molecular formula of C1498H2402N392O434S16. Threonine (Thr, T) is the most abundant amino acid, accounting for 11.1%. The protein is hydrophobic, positively charged, alkaline in nature and contains one potential N-glycosylation site and five O-glycosylation sites. It lacks a transmembrane region or signal peptide distribution and is a non-GPI-anchored protein. The secondary structure is predominantly composed of &alpha;-helices and random coils, featuring three Mito_carr structural domains. Homology comparisons revealed that the highest nucleotide sequence similarity exists between Eothenomys miletus and the species Myodes glareolus, Microtus oregoni and Arvicola amphibius. Selection pressure analysis indicated no positive selection sites for the UCP1 gene in mammals at different latitudes. The UCP1 gene in low-latitude, high-altitude mammals underwent purifying selection, forming a relatively stable function. These findings provided a theoretical basis for subsequent research on the mechanism of fat heat production and energy supply in the Eothenomys miletus UCP1 gene and a data foundation for further exploration of the role of the UCP1 gene in the adaptation of Eothenomys miletus to future environmental changes.

CDS Region of Uncoupling Protein 1 (UCP1) Gene in Eothenomys miletus: A Bioinformatics and Selection Pressure Analysis

<div>Background: Dolichos bean occupies a unique position among the legume vegetables of Indian origin for its high nutritive value and wider climatic adaptability. Despite its wide genetic diversity, no much effort has been undertaken towards genetic improvement of this vegetable crop. Knowledge on genetic variability is an essential pre-requisite as hybrid between two diverse parental lines generates broad spectrum of variability in segregating population. The current study aims to assess the genetic diversity in dolichos genotypes to make an effective selection for yield improvement. 
 
Methods: Twenty genotypes collected from different regions were evaluated during year 2016-17 and 2017-18. Data on twelve quantitative traits was analysed using principal component analysis and single linkage cluster analysis for estimation of genetic diversity. 
 
Result: Principal component analysis revealed that first five principal components possessed Eigen value &gt; 1, cumulatively contributed &gt; 82.53% of total variability. The characters positively contributing towards PC-I to PC-V may be considered for dolichos improvement programme as they are major traits involved in genetic variation of pod yield. All genotypes were grouped into three clusters showing non parallelism between geographic and genetic diversity. Cluster-I was best for earliness and number of cluster/plant. Cluster-II for vine length, per cent fruit set, pod length, pod width, pod weight and number of seed /pod, cluster III for number of pods/cluster and pod yield /plant. Selection of parent genotypes from divergent cluster and component having more than one positive trait of interest for hybridization is likely to give better progenies for development of high yielding varieties in Dolichos bean.</div>

<div>Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis</div>

<div style="text-align:justify">Background: Seventy breeding lines of mung bean were evaluated for 20 different characters and mean values were worked for genetic diversity by Mahalanobis D2 statistic. 
 
Methods: The experiments included 70 mung bean breeding lines which were collected from Plant Breeding Unit, Agricultural Research Station, Badnapur. They were grown during Kharif 2016 at experimental research farm Badnapur of Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani. The data were recorded for 20 different characters on 10 randomly selected plants. The statistical analysis were done by Mahalanobis D2 statistics. 
 
Result: The results of D2 analysis indicated the presence of considerable genetic divergence among these breeding lines. In the present study, inter-cluster distances were worked out considering 20 characters and these distances ranged from 240.96 (between cluster V and cluster VII) to 1080.72 (between cluster V and cluster VIII). The inter-specific derivatives were grouped into eight clusters. The maximum inter-cluster distance was between cluster V and cluster VIII. The maximum inter-cluster distance was between cluster V and cluster VIII (1080.72), followed by cluster II and cluster III (932.25), cluster IV and cluster VIII (910.11), cluster VII and cluster VIII (738.30), cluster I and cluster VIII (732.61), cluster VI and cluster V (660.49) and cluster II and cluster VI (494.93). This suggested that there is wide genetic diversity between these clusters. Based on these studies, crosses can be made between breeding lines of these clusters to obtain desirable results either in transgressive breeding or in heterosis breeding. Cluster VIII and cluster IV showed high mean values for most of the yield contributing traits like100-seed weight, shelling %, harvest index, pod length, primary branches per plant, days to 50% flowering, days to maturity, leaf width and days to shattering. So the lines from cluster IV and cluster VIII can be used for mung bean yield improvement programme.</div>

<div>Multivariate Analysis using D2 and Principal Component Analysis in Mung bean [Vigna radiata (L.) Wilczek] for Study of Genetic Diversity</div>

<div>Background: A complex quantitative characteristic yield is heavily impacted by the environment. The productivity of groundnut can be increased less effectively through direct selection for grain yield. The current study aimed to study the variation among diverse groundnut genotypes. 
 
Methods: Phenotypic data was collected on seven quantitative and six qualitative characters for 24 genotypes under study carried out in randomised block design (RBD). GRAPES software has been used for analysis. 
 
Result: Analysis of variance revealed significant differences among the genotypes for all the characters indicating the prevalence of ample genetic variability within the genotypes. Significant positive associations were observed for primary branches, secondary branches, 100-pod weight, shelling per cent, protein and zinc content. Path analysis revealed that plant height, primary branches per plant, hundred pod weight, shelling percent, protein content and zinc content are the most important characters which could be used as selection criteria for effective improvement of pod yield. Using GRAPES software, Fourteen Principal components are extracted based on mean values of which the first five PCs showed 73.24% variation with eigen values more than 1. Biplot constructed by Principal component analysis revealed Hundred pod weight and hundred kernel weight as important traits for study.</div>

Principal Component Analysis and Path Coefficient Analysis for Groundnut Yield and Seed Quality Attributes (Arachis hypogaea L.)

Background: This paper aims&nbsp;to evaluate the agricultural production of sugarcane in major sugarcane-producing states of India. Even though agriculture&rsquo;s share of India&rsquo;s GDP is decreasing, it still plays a significant role in the labor force by accounting for a sizable number of jobs. Recognizing the importance of sugarcane farming and the variations in resource availability among the states is crucial. The study highlights the importance of enhancing production management and resource allocation to increase sugarcane production and optimize inputs. 
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Methods: The present research employs sophisticated statistical techniques, including Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MPI), to investigate the influence of variables such as land area and labor utilization on the efficacy of sugarcane cultivation at the state level spanning from 2017 to 2022. It uses DEA to analyze the connection between various agricultural inputs and the efficiency of food grain production and provides recommendations for improved resource allocation among Indian states. 
 
Result: The results of the investigation indicate that the mean efficiency of sugarcane cultivation across India is approximately 84.2%. Notably, states such as Uttar Pradesh, Tamil Nadu and Karnataka have demonstrated the highest levels of efficiency in terms of input utilization in sugarcane farming. Conversely, Bihar and Uttarakhand have emerged as the least efficient states in this regard. Furthermore, an analysis using the Malmquist productivity index indicates that Uttar Pradesh has exhibited the most significant average productivity growth, with Maharashtra and Gujarat following closely behind. Conversely, states such as Andhra Pradesh, Punjab, Haryana and Tamil Nadu have demonstrated only marginal enhancements in productivity. The study&rsquo;s insights on sustainable sugarcane production and enhanced farmer-level regulatory frameworks have the potential to greatly benefit sugarcane-producing states. By implementing these ideas, we can work towards boosting revenue and reducing poverty in rural areas.

An Efficiency Analysis of Sugarcane Farming in India: An Interstate Comparison of Performance with Data Envelopment Analysis and Malmquist Index

Background: Broad bean (Vicia faba L.) is an important protein rich underutilized vegetable crop cultivated for its tender green pods and dry seeds. The present study was carried out to assess the genetic divergence among the broad bean genotypes collected for developing high-yielding cultivars. 
 
Methods: The experimental material consisted of 20 broad bean genotypes, raised in randomized block design with three replications at Horticultural Research Station, Nilgiris, Tamil Nadu, India during Kharif 2023. Data concerning 12 quantitative traits and 7 qualitative traits underwent examination using Mahalanobis D2 statistic, principal component analysis and stepwise multiple regression analysis. 
 
Result: The cluster analysis categorized the genotypes into nine clusters, with the highest number of genotypes in Cluster II (4) and the lowest in Clusters VII, VIII and IX (1 each). Cluster IV displayed the highest intra-cluster distance (D2=3358.2), signifying substantial variation among the genotypes within this cluster. The largest inter-cluster distance (D2=316.9) was observed between Clusters I and VII, indicating significant divergence from other clusters, suggesting that genotypes within these clusters could be valuable as diverse parents for hybridization and selection. The PCA combined with stepwise multiple regression analysis highlighted the primary variations and traits influencing pod yield.&nbsp;

Diversity Analysis for Phenotypic and Qualitative Traits of Broad Bean (Vicia faba L.): an Underutilized Vegetable Crop of India by Multivariate Analysis

Thirty three genotypes of chickpea including 9 kabuli and 24 desi types were evaluated for distinctiveness based on 13 qualitative and 7 quantitative morphological DUS descriptors. In desi type, only 4 traits were polymorphic whereas, in kabuli type, only 3 were polymorphic. Identification profiles were generated on the basis of grouping and essential characters prescribed by DUS Guidelines of PPV &amp; FR Authority. However, out of twenty four desi genotypes, distinct profiles could be created only for sixteen varieties and in kabuli type, only three out of nine genotypes could be singled out individually. &nbsp;Image analysis using scanned images of flowers of desi types successfully complemented the morphological descriptors to establish genotypic identity based on differences in the petal colour intensity and venation pattern. Genetic parameters for all the quantitative traits revealed less environmental influence on the characters expression thus, signifying their utility in the varietal characterization. Seven agro-morphological traits were used to assess the variability using Ward&rsquo;s Minimum Variance Cluster Analysis. &nbsp;Thirty three cultivars from both types were grouped into four cluster each, however, none of the clusters contained genotypes with all the desirable traits, which could be directly selected and utilized.

Cultivar identification and diversity analysis based on morphological descriptors and image analysis in chickpea (Cicer arietinum L.) 
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