Agricultural Research Research Articles

Antibiotics resistance and phenotypic virulence factors of Vibrio species isolated from poultry litters at Obafemi Awolowo University, research farm.

The study investigates the antimicrobial resistance and phenotypic virulence factors of Vibrio isolates in poultry litter. Samples were enriched in 5 mL alkaline peptone water 1:10 (w/v) for 6 hours and cultured on Thiosulphate Citrate Bile salt (TCBS) agar. Vibrio isolates were identified through biochemical tests assay and were subjected to antibiotic susceptibility tests using standards disc diffusion technique. The phenotypic virulence factors, including hemolytic and proteolytic activity were determined. A total of 100 Vibrio isolates were identified as Vibrio parahaemolyticus (49%), V. cholerae (26%), V. vulnificus (11%), V. alginolyticus (9%), and V. damsela (5%). The Vibrio isolates showed a significant resistance to the selected antibiotics tested with 99% resistant to Gentamycin, 95% Cefixime, 96% Ofloxacin, 98% Augmentin, 96% Nitrofurantoin, 100% Ciprofloxacin, and 100% Cefuroxime. The Vibrio isolates showed varying levels of haemolysis with 17% alpha haemolysis, 61% beta haemolysis, 22% gamma haemolysis, and 29% proteolytic activity. The study reveals that poultry litter contains Vibrio isolates with antibiotic resistance and virulence factors, increasing their risk of severe infections. The high beta haemolysis prevalence highlights the interconnected relationship between animal, environmental, and human health, underscoring the need for effective management.

Paddy Crop Disease Detection Using Machine Learning

Abstract: India has risen as a significant player in earlier years, the world’s second-largest producer of paddy, yielding approximately 497.7 million metric tons annualy. Sustaining vast paddy fields demand ongoing attention and upkeep. It is critical to recognize the symptoms and understand how this can effectively control the disease. Therefore, inspired by this research paper, a solution is suggested to train machine learning for identify diseases in paddy plants. The system utilizes rea;- time datasets sourced from the Agriculture Research Institute of Lonavala, which are freely accessible. This system can be used for identification purposes four major paddy plant diseases -Leaf Blast, Leaf Scald, Neck Blast and False smut. This Proposed system, first images are pre-processed and then the custom Convolution Neural Network is used to arranging the images. This project work discusses the methodology for disease identifying diseased leaves at an early At this stage, the suggested automated system can assist farmers in mitigating further harm to their crops.

KASP: a high-throughput genotyping system and its applications in major crop plants for biotic and abiotic stress tolerance.

Advances in plant molecular breeding have resulted in the development of new varieties with superior traits, thus improving the crop germplasm. Breeders can screen a large number of accessions without rigorous and time-consuming phenotyping by marker-assisted selection (MAS). Molecular markers are one of the most imperative tools in plant breeding programmes for MAS to develop new cultivars possessing multiple superior traits. Single nucleotide polymorphisms (SNPs) are ideal for MAS due to their low cost, low genotyping error rates, and reproducibility. Kompetitive Allele Specific PCR (KASP) is a globally recognized technology for SNP genotyping. KASP is an allele-specific oligo extension-based PCR assay that uses fluorescence resonance energy transfer (FRET) to detect genetic variations such as SNPs and insertions/deletions (InDels) at a specific locus. Additionally, KASP allows greater flexibility in assay design, which leads to a higher success rate and the capability to genotype a large population. Its versatility and ease of use make it a valuable tool in various fields, including genetics, agriculture, and medical research. KASP has been extensively used in various plant-breeding applications, such as the identification of germplasm resources, quality control (QC) analysis, allele mining, linkage mapping, quantitative trait locus (QTL) mapping, genetic map construction, trait-specific marker development, and MAS. This review provides an overview of the KASP assay and emphasizes its validation in crop improvement related to various biotic and abiotic stress tolerance and quality traits.

Yam Production-Related Agro-climatological Risks and Yam Yield Modeling in Côte d’Ivoire: A Review

In this paper, we present a review of the agro-climatological-related risk of yam production and models developed for yam yield prediction in Côte d’Ivoire. Four official national platforms (Ministry of Agriculture and Rural Development (MINADER), National Center for Agricultural Research (CNRA), National Agency for Rural Development Support (ANADER), Airport, Aeronautical and Meteorological Exploitation and Development Company (SODEXAM)) and six scientific search engines were investigated in this study including Theses.fr, African Journal Online, Science Direct, Google Scholar, WorldCat and Semantic Scholar. Using the boolean parameters “AND”, “OR” and “()” to facilitate and direct our search, we were able to define four key phrases comprising the topic words that were used in the search. Exclusion and inclusion criteria for the selection of documents were also defined in advance, as well as the criteria for reviewing and extracting information from selected documents. The results showed that no work in the field of agro-climatological risks related to yam production and yam yield modeling in Côte d’Ivoire was available on these online research platforms at the time of this literature review. However, other studies similar to the scope of this review on yam exist in several West African countries, particularly Ghana, Benin and Nigeria, and also in the Caribbean. These studies use simulation models such as the Approach for Land Use Sustainability (SALUS) model, the Environmental Policy Integrated Climate (EPIC) model and the Cropping Systems Simulation (CROPSYST) model for growth, yield modeling and the influence of climatic parameters on yam. In addition to these models, artificial intelligence through machine learning models was also seen in this review as an excellent tool for yield prediction for several crops including yams.

Planting and Harvesting Mechanization on Productivity, Energy Efficacy and Profitability of Potato Production

Potato occupied the first position among all the vegetables in respect of area and total production in Bangladesh. Effective and efficient use of energy are necessary for an improved agricultural production. Therefore, this research was undertaken for potato production to assess productivity, quantify energy flow and financial profitability of different production systems. The experimented four systems were manual planting and manual harvesting, machine planting and manual harvesting, manual planting and machine harvesting and machine planting and machine harvesting, respectively. The experiment was conducted at Farm Machinery and Postharvest Process (FMP) Engineering Division of Bangladesh Agricultural Research Institute (BARI) during 2017-18. Yield of potato including yield contributing characters for different treatments was not significantly varied. Direct energy was the highest in mechanical planting and harvesting system (25%) and the lower manual planting and harvesting system (18%). Indirect energy shared 82% in manual planting and harvesting system, 78% in machine planting and manual harvesting system, 80% in manual planting and mechanical harvesting system, and 75% in machine planting and machine harvesting system, respectively. The largest source of indirect energy consumption was from fertilizer (22-27% of the total energy). The higher specific energy of 1.93 MJ/kg was found in manually planted and mechanized harvesting system. The higher product value was from manual planting and mechanical harvesting system. The highest BCR (2.25) was found from machine planted and machine harvested followed by manually planted and mechanically harvested plot (2.16), machine planted and manually harvested plot (1.93) and manual planting and harvesting plot (1.91). Thus, mechanically planted and harvested system can be recommended for potato production since it can reduce 52% labour requirement than manual method and can give higher BCR among the tested production methods. 

Effect of Sulphur and Zinc on Growth and Yield of Black Gram (Phaseolus mungo L.)

A field experiment was conducted during Zaid (summer) season of 2023 at Crop Research Farm, Department of Agronomy. The treatments consisted of 3 levels of Sulphur (10, 20 and 30 kg/ha) and 3 levels of zinc (10kg/ha, 0.1% and 0.2% foliar application) and a control. The experiment was laid out in Randomized Block Design (RBD) with 10 treatment and replicated thrice. Application of Sulphur (30 kg/ha) + Zinc (10kg/ha) (treatment 9) recorded higher Plant height, higher plant dry weight, higher number of Pods/Plant, higher number of seeds/pod, higher test weight and higher seed yield. The (treatment 9) also recorded Maximum benefit cost ratio (2.41)

Genetic Variability Estimation in Forty Pigeonpea Germplasm for Yield and Yield Attributing Traits

Aim: The present research aimed to estimate the genetic variability in forty pigeonpea germplasms for yield and yield-attributing traits such as initial plant stand, final plant stand, days to 50% flowering, primary branches, secondary branches, plant height, days to maturity, wilt incidence%, pod borer infestation %, 100 seed weight, number of pods per plant, yield (g/plot), yield (kg/ha).
 Study Design: study was conducted in randomised block desigh (RBD) design with two replications and spacing of 60 cm X 30 cm.
 Place and Duration of Study: The present investigation was carried out during kharif 2021-2022 and 2022-2023 at the research farm of Birsa Agricultural University farm located at Kanke, Ranchi.
 Methodology: Forty pigeonpea genotypes were studied to determine genetic variability. Pooled data over two years were subjected to statistical analysis for estimation of genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), heritability in broad sense                                 (h2), and genetic advance as a percent of mean for fourteen quantitative traits such                                 as initial plant stand, final plant stand, days to 50% flowering, primary branches,                                  secondary branches, plant height, days to maturity, wilt incidence%, pod borer infestation%, 100 seed weight.
 Results: The PCV varied from 2.45% (days to maturity) to 30.83% [yield (kg/ha), whereas the GCV ranged from 1.12% (days to maturity) to 17.67% [yield (g/plot)]. Days to 50% flowering (6.39%, 4.48%), days to maturity (2.45%, 1.12%), and 100 seed weight (8.53%, 5.65%) all had low GCV and PCV value. The broad sense of heritability (h2) varied between plant height (16.9%) to days to 50% blooming (49.20%). Plant height (16.90%, 4.95%), number of pods per plant (21.10%, 9.95%), and days to maturity (20.90%, 1.05%) showed low heritability and genetic advance as a percentage of the mean, indicating ineffective selection.
 Conclusion: Genotypes showed high magnitude of variability for all the traits under study.

Collaboration networks in agricultural research in Uruguay: An exploration based on social network analysis

Scientific collaboration networks connect researchers across institutions and academic disciplines. Agricultural research involves multiple stakeholders and academic disciplines to address increasingly complex and diverse research agendas. However, the dynamics of collaboration and the patterns of interaction in the agricultural sciences have been little investigated. Uruguay has a rich tradition in agricultural research, but little is known about the ways in which institutional and interdisciplinary collaboration occur and have evolved recently. This article uses relational data from projects documented in researchers’ vitas (CVs) to examine patterns of collaboration in agricultural research in Uruguay during the period 2000–2017. Collaboration networks were explored with social network analysis (SNA) resulting in networks involving varied institutions and academic disciplines. An inter-institutional network with a center and periphery structure is revealed with long-standing science and technology centers as the fundamental nodes. Interdisciplinary collaborations show diversification over time with more academic fields involved in research projects in the agricultural sciences. Joint research between agricultural sciences and other academic fields to address complex current phenomena could benefit from increasing connections with multiple fields in the environmental, social, and health sciences. The study shows the usefulness of SNA and research project data to improve the understanding of collaboration patterns in agricultural research.

Genetic Variability and Character Association among the Yield and Yield Attributing Traits in Niger [Guizotia abyssinica (L. f.) Cass.]

Niger is a minor oil seed crop mostly cultivated in high altitude and tribal zones of India with relatively lower productivity. Development of varieties with higher yielding ability needs keen observations and scientific studies on the genetic variability and character association studies among the available germplasm or in the breeding material. The present investigation was carried out with a main objective to estimate the extent of genetic variability and character association with respect to yield and yield component traits. Thirty five genotypes of niger were collected from different niger stations and sown in rabi, 2022 in a randomized block design at Regional Agricultural Research Station, High Altitude and Tribal Zone, Chintapalle, ANGRAU. Observations were recorded on five plants in each line in each replication for plant height (cm), number of branches plant-1, number of capitula plant-1, test weight (g) and seed yield plant-1 (g). Days to 50 % flowering, days to maturity and seed yield ha-1 (kg/ha) were recorded on plot basis. Analysis of heritability(bs) and genetic advance as percent of mean revealed that four characters viz., plant height, number of branches plant-1, number of capitula plant-1 and seed yield plant-1 are governed by additive gene action, which can be improved further by simple selection methods. Majority of the characters under study are having a significant positive association with seed yield ha-1which helps in indirect selection for higher yield by using these character combinations. All the characters showed significant and positive association with seed yield plant-1which helps in indirect selection of genotypes for improved yielding ability.

Effect of Nitrogen and Crop Geometry on Growth and Yield of Baby Corn

The field experiment was conducted to investigate the Effect of Nitrogen and Crop Geometry on Growth and Yield ofBaby Corn during Zaid season of 2023 at the Crop Research Farm, Department of Agronomy, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj (U.P.) India. The main objectives of experiment is to studythe efficacy of nitrogen and crop geometry on growth and yield of baby corn. The experiment was executed using Randomized Block Design with ten treatments and replicated thrice. The treatments combinations are T1:Nitrogen 60kg/ha + Crop Geometry 40cm × 20cm T2: Nitrogen 80kg/ha + Crop Geometry40cm × 20cm T3: Nitrogen 100kg/ha + Crop Geometry 40cm × 20cm T4: Nitrogen 60kg/ha + Crop Geometry 50cm × 20cm T5: Nitrogen 80kg/ha + Crop Geometry 50cm × 20cm T6: Nitrogen 100kg/ha + Crop Geometry 50cm × 20cm T7: Nitrogen 60kg/ha + Crop Geometry 60cm × 20cm. T8: Nitrogen 80kg/ha + Crop Geometry 60cm × 20cm T9: Nitrogen 100kg/ha + Crop Geometry 60cm × 20cm, T10: Control (RDF-60- 40-40 NPK kg/ha) are used. The result of the study revealed that the higher plant height (173.47 cm), higher plant dry weight (29.3 g/plant), number of cobs/plant (2.1), green fodder yield (33.32 t/ha), cob yield with husk (12.30 t/ha), andcob yield without husk (4.33 t/ha) were significantly showed significant difference with application of Nitrogen100kg/ha + Crop Geometry 50cm × 20cm. It was concluded that for obtaining higher yield components with better quality of baby corn with Nitrogen 100 kg/ha + Crop Geometry 50cm × 20cm was recommended.

Comprehensive Assessment of NDVI Products Derived from Fengyun Satellites across China

NDVI data are crucial for agricultural and environmental research. The Fengyun-3 (FY-3) series satellites are recognized as primary sources for retrieving NDVI products on a global scale. To apply FY-3 NDVI data for long-term studies, such as climate change, this study conducted a thorough evaluation to detect the potentials of the FY-3B and FY-3D satellites for generating a long time series NDVI dataset. For this purpose, the spatiotemporal consistency between the FY-3B and FY-3D satellites was evaluated, and their performances were compared. Then, a grey relational analysis (GRA) method was applied to detect the factors influencing the consistency among the different satellites, and a gradient boosting regression (GBR) model was constructed to create a long-term FY-3 NDVI product. The results indicate an overall high consistency between the FY-3B and FY-3D NDVIs, suggesting that they could be used as complementary datasets for generating a long-term NDVI dataset. The correlations between the FY-3D NDVI and the MODIS NDVI, as well as the leaf area index (LAI) measurements, were both higher than those of FY-3B, which indicates a better performance of FY-3D in retrieving NDVI data. The grey correlation degrees between the NDVI differences and four parameters, which were land cover (LC), DEM, latitude (LAT) and longitude (LON), were calculated, revealing that the LC was the most related to the NDVI differences. Finally, a GBR model with FY-3B NDVI, LC, DEM, LAT and LON as the input variables and FY-3D NDVI as the target variable was established and achieved a robust performance. The R values between the GBR-estimated NDVI and FY-3D NDVI reached 0.947, 0.867 and 0.829 in the training, testing and validation datasets, respectively, indicating the feasibility of the established model for generating long time series NDVI data by combining data from the FY-3B and FY-3D satellites.

Investigating the Impact of the Central Agricultural Research Institute's (CARI) Agricultural Extension Services on the Productivity and Livelihoods of Farmers in Bong County, Liberia, from 2013 to 2017

In Liberia, a country where agriculture plays a pivotal role in socio-economic development and food security, the effectiveness of agricultural extension services remains crucial yet underexplored, especially in the context of transitioning from subsistence to commercial agriculture. This study focuses on assessing the Central Agricultural Research Institute's (CARI) agricultural extension services' impact on the agricultural productivity and livelihoods of farmers in Suakoko, Jorquelleh, and Yealliquelleh districts of Bong County, from 2013 to 2017. The objectives were to evaluate the accessibility and adoption of agricultural innovations disseminated by CARI and analyze the effectiveness of its extension delivery methods. Employing a mixed-methods approach, the research yielded significant findings: 54.1% of respondents were male, indicating a gender disparity in agricultural engagement. The adoption of new technologies and practices was varied, with 43.3% of farmers reporting access to new fertilizer application methods as the most prominent innovation provided by CARI. Despite the extension efforts, 68.8% of farmers did not receive visits from CARI agents, and a considerable 50% reported no access to new innovations or technologies. The study also highlighted a distinct preference for learning through demonstrations (73.7%) and meetings (25%), underscoring the demand for practical and interactive extension services.

Influence of cover crop residue and residual herbicide on emergence dynamics of glyphosate-resistant Palmer amaranth (Amaranthus palmeri) in grain sorghum

Abstract A field study was conducted from 2020 to 2023 at Kansas State University Agricultural Research Center near Hays, KS, to understand the emergence dynamics and periodicity of glyphosate-resistant (GR) Palmer amaranth (Amaranthus palmeri S. Watson) as influenced by cover crop (CC) residue and residual herbicide in grain sorghum [Sorghum bicolor (L.) Moench]. The study site was under a wheat (Triticum aestivum L.)–sorghum–fallow rotation with a natural seedbank of GR A. palmeri. Treatments included (1) fall-planted CC mixture [winter triticale (×Triticosecale Wittm. ex A. Camus [Secale × Triticum])/winter peas (Pisum sativum L.)/rapeseed (Brassica napus L.)/radish (Raphanus sativus L.)] after wheat harvest and terminated at triticale heading stage (next spring before sorghum planting) with glyphosate alone or (2) glyphosate plus acetochlor/atrazine, (3) chemical fallow (no CC but treated with acetochlor/atrazine and dicamba before sorghum planting), and (4) nontreated control (no CC and no herbicide). Results indicated that CC terminated with glyphosate plus acetochlor/atrazine had a delayed and reduced cumulative emergence of GR A. palmeri as compared with chemical fallow and CC terminated with glyphosate alone across all 3 yr. Compared with chemical fallow, the CC terminated with glyphosate alone and glyphosate plus acetochlor/atrazine required 66 to 643 and 105 to 1,257 more cumulative growing degree days, respectively, to achieve 90% cumulative emergence of GR A. palmeri across all 3 yr. The combined effect of CC residue with glyphosate plus acetochlor/atrazine reduced the total emergence counts of GR A. palmeri by 42% to 56% and 82% to 94% as compared with chemical fallow and nontreated control, respectively. These results suggest that fall-planted CC combined with a residual herbicide at termination can be utilized for GR A. palmeri suppression in grain sorghum.

Influence of Phosphorus and Sulphur Levels on Economics and Yield of Safflower (Carthamus tinctorius L.) under the Eastern Zone of UP, India

The present study highlights the influence of Phosphorus and Sulphur Levels on Economics and Yield of Safflower (Carthamus tinctorius L.): A Field Experiment yield of Safflower (Carthamus tinctorius L)". var. "ISF-764" was tested at Crop Research Farm during Rabi 2021–23. Ministry of Agriculture Sciences and technology United University, Prayagraj in the U.P. Safflower (Carthamus tinctorius L.) India ranks second in terms of planted area after food crops and is the world's fourth-largest producer of oilseeds in terms of output. The soil of the experimental plot had a sandy loam texture, was almost pH-neutral (7.5), had low organic carbon content (0.50%), and was readily available. N (228.59 kg/ha), available P (29.80 kg/ha) and available K (125.21 kg/ha). The experiment was laid out in randomized block design with nine treatments consists three level of S 20,30,40 kg/ha and three level of P 30,40,50 kg/ha with control (Farmer practice) were replicated thrice. Results obtained that higher plant height (173.33 cm), Number of branches (19.27), dry weight (117.89 g/day), yield attributes and yield viz., seed yield (2.20 t/ha), stover yield (2.98 t/ha) and Hi (42.44 %) were recorded with the application of 40 kg/ha S + 50 kg/ha P, economics viz. however, higher gross return (113804.07 INR/ha), net return (77799.97 INR/ha) and B:C ratio (2.16) was observed when 40 kg/ha S and 50 kg/ha P were applied. Application of 40 kg/ha S with 50 kg/ha P was therefore more productive and financially viable. It is concluded that treatment T9 with application of S 40 kg/ha + P 50 kg/ha was found to be the best that recorded highest plant height, number of capitulam / plant , dry weight (g), panicle length, number of panicles, number of grains per panicle, seed yield, straw yield, test weight and harvest index.

History and current status of embryogenic culture-based tissue culture, transformation and gene editing of maize (Zea mays L.).

The production of embryogenic callus and somatic embryos is integral to the genetic improvement of crops via genetic transformation and gene editing. Regenerable embryogenic cultures also form the backbone of many micro-propagation processes for crop species. In many species, including maize, the ability to produce embryogenic cultures is highly genotype dependent. While some modern transformation and genome editing methods reduce genotype dependence, these efforts ultimately fall short of producing truly genotype-independent tissue culture methods. Recalcitrant genotypes are still identified in these genotype-flexible processes, and their presence is magnified by the stark contrast with more amenable lines, which may respond more efficiently by orders of magnitude. This review aims to describe the history of research into somatic embryogenesis, embryogenic tissue cultures, and plant transformation, with particular attention paid to maize. Contemporary research into genotype-flexible morphogenic gene-based transformation and genome engineering is also covered in this review. The rapid evolution of plant biotechnology from nascent technologies in the latter half of the 20th century to well-established, work-horse production processes has, and will continue to, fundamentally changed agriculture and plant genetics research.

Bio-efficacy of Herbicides on Weed Density, Weed Control Efficiency, Productivity and Groundnut Quality in Coastal Zone of Karnataka under Rice-Groundnut System

A field experiment was conducted at Agricultural Research Station, Kumta, Uttara Kannada district during the rabi-summer season of 2016-17 to investigate the Bio-efficacy of herbicides on weed density, weed control efficiency, productivity and groundnut quality in coastal zone of Karnataka under rice-groundnut system. The experiment followed a RBD with nine treatments out of which six treatments involved the pre-emergence application of herbicides followed by either hand weeding or early post-emergence application, along with control treatments. The results indicated that the pre-emergence application of pendimethalin 30% E.C. (1.5 kg ha-1), followed by one hand weeding at 25 days after sowing (DAS), resulted in significantly reduced total weed density and weed dry matter. This treatment also demonstrated higher weed control efficiency and lower weed index. Moreover, it led to increased pod yield, kernel yield and improved quality of groundnut compared to other treatments.

Predicting fat cover in beef cattle to make on-farm management decisions: a review of assessing fat and of modeling fat deposition

Abstract Demands of domestic and foreign market specifications of carcass weight and fat cover, of beef cattle, have led to the development of cattle growth models that predict fat cover to assist on-farm managers make management decisions. The objectives of this paper are 4-fold: (1) conduct a brief review of the biological basis of adipose tissue accretion, (2) briefly review live and carcass assessments of beef cattle, and carcass grading systems used to develop quantitative compositional and quality indices, (3) review fat deposition models: Davis growth model (DGM), French National Institute for Agricultural Research growth model (IGM), Cornell Value Discovery System (CVDS), and BeefSpecs drafting tool (BeefSpecsDT) and (4) appraise the process of translating science and practical skills into research/decision support tools that assist the Beef industry improve profitability. The r2 for live and carcass animal assessments, using several techniques across a range of species and traits, ranged from 0.61 to 0.99 and from 0.52 to 0.99, respectively. Model evaluations of DGM and IGM were conducted using Salers heifers (n = 24) and Angus-Hereford steers (n = 15) from an existing publication and model evaluations of CVDS and BeefSpecsDT were conducted using Angus steers (n = 33) from a research trial where steers were grain finished for 101 days in a commercial feedlot. Evaluating the observed and predicted fat mass (FM) is the focus of this review. The FM mean bias (MB) for Salers heifers were 7.5 and 1.3kg and the root mean square error of prediction (RMSEP) were 31.2 and 27.8kg and for Angus-Hereford steers the MB were -4.0 and -10.5kg and the RMSEP were 9.14 and 21.5kg for DGM and IGM, respectively. The FM MB for Angus steers were -5.61 and -2.93kg and the RMSEP were 12.3 and 13.4kg for CVDS and BeefSpecsDT, respectively. The decomposition for bias, slope, and deviance were 21, 12, and 68% and 5, 4, and 91% for CVDS and BeefSpecsDT, respectively. The modeling efficiencies were 0.38 and 0.27 and the models were within a 20kg level of tolerance 91 and 88% for CVDS and BeefSpecsDT, respectively. Fat deposition models reported in this review have the potential to assist the beef industry make on-farm management decisions on live cattle before slaughter and improve profitability. Modelers need to continually assess and improve their models but with a caveat of: (1) striving to minimize inputs, and (2) choosing on-farm inputs that are readily available.

Impact of Different Sowing Dates on Growth and Pod Yield of Vegetable Pea under Sub-Himalayan Foothills Region of India

Background: The optimum sowing date is crucial among the different agronomic procedures for maximizing output. Optimizing a crop's planting time may be one of the most significant climate resilient tactics for increasing production and hence it becomes necessary to study the crop growth behaviors in changing climatic conditions. The proposed field investigations were undertaken to study the influence of different sowing dates on yield of vegetable pea. Methods: Field investigations were undertaken during Rabi seasons of 2020-21 and 2021-22 at the Vegetable Research Farm, Department of Horticulture, Dr. Rajendra Prasad Central Agricultural University, Pusa (85.67oE - 25.98oN.), which comes under sub-Himalayan foothills region of India. The research study was performed in Randomized Block Design with three replications consisting of eight different sowing dates of vegetable pea. cv. Azad Pea-3 at 10 days interval between each sowing dates. Observations were made on various growth and yield attributing parameters. Result: Results revealed that the parameters under study were substantially affected by various sowing dates. Second week of sowing in November in the years produced maximum plant height at 60 DAS (83.77cm), number of branches per plant (3.97), number of nodules per plant at flowering (26.13), number of green pods per plant (20.80), 10 pods weight (75.67g) and pod yield (52.06q/ha).

Avifaunal Diversity in Telangana State: A Case Study in Campus of Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad, India

Population Studies on different agricultural and other bird species were carried out at Students farm, College farm, Agri biodiversity park, and Agricultural Research Institute farm areas of Professor Jayashankar Telangana State Agricultural University (PJTSAU) Campus in semiarid region of Telangana state covering an area of about 36 Sq.km. for a period of eleven years (2012 to 2023). Population diversity of 92 species of different birds, and their distribution within the university campus farm areas were recorded.  Important among them are 9 species namely: Blue rock pigeon (Columba livia), Spotted dove (Streptopelia chinensis), Rose ringed parakeet (Psittacula krameri),Common myna (Acridotheres tristis), House crow (Corvus splendens), House sparrow (Passer domesticus), Baya weaver bird (Ploceus philippinus), White throated munia (Lonchura malabarica), and Peafowl (Pavo cristatus) which depredate experimental field crops among them only  few birds such as: Rose ringed parakeets, House crows, House sparrows, Pigeons, Baya weavers, Peafowls and Munias were serious bird pests to major agricultural and horticultural crops. The University farm areas were found to be the most preferred habitat for many of these birds, it could be due to availability of food, breeding, roosting and resting sites in abundance because of more agricultural croplands and agro forestry trees.

Diagnosing Medicinal Plants and their Fungal Diseases Using Deep Learning Models

Today, with the development of technology, most manual methods have been replaced by automated computer systems for human convenience. Plant identification and disease classification are two major areas of agricultural research and are aimed at introducing computerized systems instead of manual methods. Millions of plant species are in the world and play a significant role in human life. Among all the types of plants, medicinal plants play an essential role in the traditional medical field because herbal plants can heal humans. Currently, there is a reactivation of interest in herbal medicines at the global level, and conventional medicine is now accepting the use of medicines and their products once they have been scientifically validated. To achieve this goal, we evaluated the performance of two common pre-trained deep learning models (VGG19 and ResNet50) and compared their accuracy levels Finally, the system can estimate some performance metrics such as accuracy and error rate for both algorithms and compare the algorithms based on accuracy in the form of graph. These results are promising, as they show that machine-learning techniques could be used for the early identification of medicinal plants. Our algorithm has been able to achieve a high level of accuracy in the classification of medicinal plants in training and test sets, making it a potentially valuable tool for fast and accurate diagnosis in clinical environments. Keywords—VGG19, ResNet50, Traditional medicine, Medicinal Plant Identification and Disease Classification