Optimum Yield Research Articles

Product Distribution of Steady-State and Pulsed Electrochemical Regeneration of 1,4-NADH and Integration with Enzymatic Reaction.

The direct electrochemical reduction of nicotinamide adenine dinucleotide (NAD+) results in various products, complicating the regeneration of the crucial 1,4-NADH cofactor for enzymatic reactions. Previous research primarily focused on steady-state polarization to examine potential impacts on product selectivity. However, this study explores the influence of dynamic conditions on the selectivity of NAD+ reduction products by comparing two dynamic profiles with steady-state conditions. Our findings reveal that the main products, including 1,4-NADH, several dimers, and ADP-ribose, remained consistent across all conditions. A minor by-product, 1,6-NADH, was also identified. The product distribution varied depending on the experimental conditions (steady state vs. dynamic) and the concentration of NAD+, with higher concentrations and overpotentials promoting dimerization. The optimal yield of 1,4-NADH was achieved under steady-state conditions with low overpotential and NAD+ concentrations. While dynamic conditions enhanced the 1,4-NADH yield at shorter reaction times, they also resulted in a significant amount of unidentified products. Furthermore, this study assessed the potential of using pulsed electrochemical regeneration of 1,4-NADH with enoate reductase (XenB) for cyclohexenone reduction.

Effect of Nitrogen Fertilizer and Seed Rates on Growth, Yield and Yield Components of Bread Wheat in Jimma Zone South Western Ethiopia

Wheat is one of the most important cereal crops in terms of production and consumption in Ethiopia. The country has the potential to produce a sufficient amount of wheat grain using irrigation, and government also gave attention to produce wheat and export it. But inappropriate agronomic practices, soil fertility depletion, and drought are among the constraints to the low yield of wheat crops in the country. In view of this, the field experiment was conducted during the irrigation season of 2020/2021 in two districts that are selected as irrigation potential and irrigation facilities namely, Sekacokorsa and Tiroafetadistricts of Jimma zone. The field experiment consisted of four N fertilizer rates (0, 23, 46, 69, and 92 kg Nha<sup>-1</sup>) and three seed rates (125, 150, and 175 kg•ha<sup>-1</sup>). The experiment was laid out in a randomized complete block design with a factorial arrangement in three replications. From the field experiment results, the growth, yield and yield components of the crop were improved by optimizing plant population density and nitrogenfertilizerapplication. Numerically the highest grain yield and above ground biomass of 6.7 and 13.09 t•ha<sup>-1</sup>at Tiroafeta and 3.67 and 9.61 t•ha<sup>-1</sup> at Sekacokorsawas recorded in response to the seed rate of 175 kg•ha<sup>-1</sup> respectively. On other hand in response to N fertilizer rate the maximum grain yield of 6.9 t•ha<sup>-1</sup>and above ground biomass of 14.04 t•ha<sup>-1</sup> at Tiroafetawas recorded from 92kg N ha<sup>-1</sup>and 69 kg N ha<sup>-1</sup> respectively. Whereas at Sekacokorsa the highest grain yield of 3.72 t•ha<sup>-1</sup>and above ground biomass of 9.76 t•ha<sup>-1</sup> was obtained from nitrogen fertilizer rate of 46kg N ha<sup>-1</sup>. In conclusion, N fertilizer rate of 46kg•Nha<sup>-1</sup> and seed rates of 125 kg•ha<sup>-1</sup>in both locationsgavethe optimum yield. But due to the field experiment was done for one year only it should be repeated over the years to give sound recommendationsunder similar agro ecologies.

Study on characteristics of toluene/chlorobenzene nitrification in different microreactors

Aromatic nitrification with mixed acid is an important industrial reaction with fast, strong-exothermic, and high-risk reaction characteristics. To investigate the promotion for the preparation of nitrotoluene (MNT) and nitrochlorobenzene (NCB), three microreactors with different structural features, namely, heart-shaped, diamond-shaped, and zigzag-shaped microreactors, are designed and fabricated. Firstly, the effects of temperature, residence time, and molar ratio on toluene (TOL) and chlorobenzene (CB) nitrification are investigated, and orthogonal experiments are further conducted to determine the optimum reaction conditions. Results showed that channel structures and the residence time τ have negligible effects on the isomers selectivity of the three microreactors, and higher reaction temperatures and mole ratios would lead to the substantial occurrence of side reactions and byproducts in the zigzag microreactor. The heart-shaped microreactor has the highest value of 91.49 % for the MNT's optimal yield, followed by the diamond-shaped and zigzag-shaped microreactors (89.91 % and 89.81 %, respectively). The heart-shaped microreactor provides the maximum amount of NCB preparation (93.95 %), while the yields of the diamond-shaped and zigzag-shaped microreactors are 91.51 % and 88.25 %, respectively. This work provides the experimental basis for the efficient preparation and industrial scale-up of aromatic nitrification in microreactors.

Sustainable microwave-supported biodiesel production using sandbox oil and its waste shell as a nanoparticle green alkali heterogeneous catalyst

This present work explored the possible use of sandbox seed (Hura crepitans) shell (SSS) waste as a feedstock for synthesizing green solid alkali biocatalyst in the microwave-aided sandbox oil (SBO) transesterification to obtain SBO biodiesel (SBOB). The solid catalyst was produced using a calcination method by burning raw SSS in the open air to obtain ash heated for 3 h in a furnace at 500 °C. The calcined sandbox shell ash (CSSA) produced was characterized using standard techniques to establish its catalytic potency. Also, a model was developed to simulate the process and examine the interactive effect of process input variables on SBOB yield using the Taguchi approach. The CSSA characterization showed it composed of K (44.99 %), Ca (1.54 %), and Mg (1.87 %) with crystalline compounds of K and Mg. The physisorption results gave a mean pore size of 18.142 nm and a surface area of 6.1125 m2/g. The best combination of the input variables determined for the process is a heating power of 450 W, methanol:SBO of 8:1, time of 1.5 min, and CSSA loading of 2 wt% with an optimum SBOB yield of 98.27 wt%. The SBOB produced met standard specifications for biodiesel. Microwave application to the SBO transesterification aided in rapidly completing the reaction. The study concluded that sandbox seeds and their shells are promising feedstock for cheap and sustainable biodiesel production.

Effect of Different Fertilizer Levels on Growth and Yield of Linseed (Linum usitatissimum L.) under Guava (Psidium guajava L.) Based Agroforestry System

The study was conducted during 2021-2022 during the Rabi season in Mirzapur district, Uttar Pradesh (Vindhyan region) at the agroforestry system of Rajiv Gandhi South Campus, Department of Agronomy, Banaras Hindu University. This research aimed to analyze different levels of NPK on the growth parameters, yield attributes, and yield of linseed under guava based Agroforestry system. The experiment was laid out in a randomized block design with nine treatments. Results indicated that increasing NPK levels positively impacted linseed growth parameters and yield attributes. The highest NPK application (60-60-50 kg ha-1) resulted in the most favorable outcomes. Economic analysis revealed that higher NPK concentrations led to increased gross returns, net returns, and benefit-cost ratios. Based on the findings, it is recommended to apply 60 kg N ha-1, 30 kg P ha-1, and 25 kg K ha-1 for optimal growth and yield of linseed under the guava-based Agroforestry system, leading to maximum net returns.

Assessing the Impact of Nitrogen Fertilization, Variety Selection, Year and Their Interaction on Wheat Yield and Yield Components

This five-year study (2016–2021) in Morocco’s Mediterranean climate investigated the effect of nitrogen fertilization and genotypic selection on wheat yield and associated components. Utilizing a split-plot design, the study assessed five wheat genotypes—’Faraj’, ‘Luiza’, ‘Itri’, ‘Karim’ and ‘Nassira’—under three nitrogen application rates (120, 60 and 0 kg/ha) across thirty plots with two replicates. Interactions between nitrogen and year showed marked significance in yield (p = 0.001), biomass (p = 0.002), TKW (p = 0.003) and Spk/m2 (p = 0.001), underscoring the variability in optimal nitrogen application rates across different years. Additionally, significant interactions between variety and year were observed for biomass (p = 0.001) and G/m2 (p = 0.001), indicating variability in the performance of different varieties across years. The ‘Itri’ genotype showed the highest yield in 2017, while ‘Luiza’ was pre-eminent in 2018, with ‘Itri’ producing the most biomass. ‘Faraj’ demonstrated consistent superiority in yield and biomass during 2019 and 2020. Our integrated principal component analysis and quadratic models elucidated that an intermediate nitrogen rate of 60 kg/ha (N2) was particularly advantageous for the ‘Faraj’ and ‘Karim’ genotypes. These findings highlight the substantial impact of informed nitrogen level adjustment and genotypic selection on yield optimization.

Improving cyclodextrin yield via retarding retrogradation of debranched starches during the preparation of cyclodextrin with cyclodextrin glycosyltransferase and pullulanase

Improving substrate utilization is crucial for industrial conversion of starch. The introduction of pullulanase in cyclodextrin (CD) production has improved substrate utilization. However, complete utilization of debranched starches has not been achieved, mainly due to the retrogradation of debranched starches and the inhibitory effect of CDs on pullulanase during the catalytic reaction. This study aimed to establish an efficient CD preparation system by regulating the substrate concentration and reaction temperature. A Bacillus thermoleovorans pullulanase (BtPul) was selected for investigation of its interaction with CDs through inhibition pattern assays, fluorescence spectroscopy, and molecular docking. Results clarified that CDs inhibited BtPul, with α-CD showing the highest inhibition, followed by β-CD and γ-CD. γ-CD inhibited BtPul through a mixed mode of competitive and noncompetitive inhibition, while the other CDs inhibited BtPul competitively. When pullulan was used as the substrate, increasing the substrate concentration weakened the inhibitory effect of CDs to some degree, while changes in reaction temperature only had a minor contribution. When BtPul and β-CGTase collaboratively converted 30% (w/v) starch substrate, an increase in reaction temperature improved the conversion rate of β-CD from 67.6% to 86.8%. Optimization of substrate concentration showed that high concentration starch substrate had an adverse effect on CDs yield due to retrogradation. The optimal yields of α-CD and β-CD produced by BtPul and α-/β-CGTases were 55.7% and 90.3%, respectively. This study provides a reliable method and reference for the efficient conversion of starch into CDs.

Biogas Production Optimization in the Anaerobic Codigestion Process: A Critical Review on Process Parameters Modeling and Simulation Tools

Many operational parameters, either discretely or collectively, can influence the biodegradation performance towards enhancing biogas yield and quality. Among the operating parameters, organic loading rate (OLR), inoculum-substrate ratio, and carbon-nitrogen ratio (C/N) are the most critical parameters in the optimization and enhancement of biogas yield. Optimization of the biogas production processes depends on the ability of anaerobic microorganisms to respond to variations in operational parameters such as pH, redox potential, and intermediate products to enhance the biogas yield. This review article focuses on the role of process parameters, kinetic models, artificial intelligence, Aspen Plus (AP), and anaerobic digestion model no. 1 (ADM1) in optimizing biogas yield via an anaerobic codigestion (AcoD) process. The review showed that biomaterials codigestion upgraded biogas yield to the extent of 400%, and organic removal efficiency reached up to 90% compared to a single substrate. In addition, the current work has verified that the kinetic model is the most effective tool for signifying that the hydrolysis phase is the rate-limiting step, whereas AP is the most effective tool in the design and optimization of the AcoD process parameters. The reviewed kinetic and AI models show strong correlation values ranging from 0.931 to 0.9991 and 0.8700 to 0.9998, respectively. The AcoD system involves complex chemical reactions, but AP might have limitations in representing such complex chemical processes with nonideal behavior and complicated reaction mechanisms. The design and optimization of AcoD with reliable input parameters are highly limited or nonexistent. The AcoD process design with AP opens fresh research opportunities, including improved efficiency, finding appropriate retention time, and saving time, as well as finding the optimum biogas yield. This review article gives an insightful understanding of AcoD process parameter optimization and valuable strategies for policy development enhancing sustainability in the biogas sector.

Regional Prediction of Crop Yield Success Rate in the Philippines using Geographic Trend Analysis Algorithm

Agriculture holds an important role in the economy of the Philippines by ensuring the food security of domestic products. It involves about 40 % of Filipino workers and it contributes an average of 20 percent to the Gross Domestic Product. Crop prediction in the Philippine’s agriculture is a big problem. At the present time, farmers are having a difficult time in choosing the right crops due to unnatural climate changes, soil type, rainfall, and other environmental factors. These can affect the economic life of farmers and can make them less familiar in forecasting future crops. This project aims to guide the farmers for sowing the reasonable crops by using geographic trend analysis algorithm. The findings from this study demonstrate the potential of the Geographic Trend Analysis Algorithm as a powerful tool for regional crop yield prediction. The success rate of each region will always equate to 100% in context with the set optimal yield prediction where the crop with highest percentage appears to be the dominant one. Irrigated palay (rice) demonstrates a greater rate of success across diverse Philippine regions when contrasted with rainfed or non-irrigated palay, as well as white and yellow corn. Additionally, the methodology employed by the researchers sets the groundwork for upcoming investigations in the domain of agricultural data analytics and geographic information science. This paves the way for a data-centered and sustainable strategy toward crop production in the Philippines.

Deep Learning Algorithms for IoT Based Crop Yield Optimization

Precision agriculture, with its objectives of optimizing crop yields, decreasing resource waste, and enhancing overall farm management, has emerged as a revolutionary technology in modern agricultural practices. The advent of deep learning techniques and the Internet of Things (IoT) has brought about a paradigm shift in monitoring, decision-making, and predictive analysis within the agriculture industry. This review paper investigates the relationship between deep learning, the (IoT), and agriculture, with an emphasis on how these three domains might work together to optimize crop yields through intelligent decision-making. The integration of deep learning techniques with (IoT) technology for precision agriculture is thoroughly analyzed in this study, covering recent developments, obstacles, and possible solutions. The paper investigates the role of deep learning algorithms in analyzing the vast amounts of data generated by IoT devices in agriculture. It scrutinizes various deep learning models such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their variants applied for crop disease detection, yield prediction, weed identification, and other crucial tasks. Furthermore, this review critically examines the integration of IoT-generated data with deep learning models, highlighting the synergistic benefits in enhancing agricultural decision-making, resource allocation, and predictive analytics. This review underscores the pivotal role of IoT and deep learning techniques in revolutionizing precision agriculture. It emphasizes the need for interdisciplinary collaboration among agronomists, data scientists, and engineers to harness the full potential of these technologies for sustainable and efficient farming practices.

One-pot catalytic conversion of sugars to methyl lactate over acid-base bifunctional Sn/MgO catalysts

Alkyl lactates represent such green added-value chemicals that commonly used as biodegradable green solvents, detergents, pharmaceutical intermediates et al. Catalytic conversion of carbohydrates to methyl lactate (MLA) is a representative way for high-value utilization of biomass and the key lies in the development of highly efficient catalysts. In methanol, strong acid or alkaline catalysts are usually used under high temperature and high pressure, suffering from problems such as low selectivity, high cost or contamination of environment. This study aims to develop an acid-base bifunctional heterogeneous catalyst for the one-pot conversion of sugars to MLA under mild conditions. Sn/Mg composite oxides was synthesized by a coprecipitation method and further modified by poly (vinyl imidazole) ([PVIM]) to tune the hydrophilicity. Effect of polymer and Sn amount, calcination temperature, reaction temperature, catalyst dosage, and substrate concentration were investigated. The acid-base properties were characterized by NH3-TPD, pyridine-FTIR and CO2-TPD analysis. It was found that the presence of medium acid sites and medium base sites played an important role to the cascade reactions of carbohydrates to MLA. An optimum MLA yield of 55.4% was achieved over 10[PVIM]-5Sn/MgO (0.05 g) with complete conversion of glucose (28 mM) at 140 ℃, 2 MPa N2 for 10 h. The reaction conditions are mild and no strong acid or strong base catalyst is required. Furthermore, a possible reaction mechanism was proposed that the introduction of [PVIM] effectively regulated the local microenvironment of active sites and the acid base synergism greatly promoted the retro-aldol condensation, dehydration and hydrogen transfer reactions during the conversion of glucose to MLA.

Evaluation of drying and extraction parameters for the extraction yield of watermelon (Citrullus lanatus (Thunb.)) rind using statistical design experiment

Watermelon rind contributes about 30% of overall watermelon mass and is considered the most underutilized resource as it is usually discarded as waste. Watermelon rind resources have great potential economic value in various industries. Thus, utilizing the rind could decrease the amount of biological waste in the environment. Therefore, this study aims to determine the optimal conditions in extracting oven and dehydrator drying watermelon rind using a sonicator extraction procedure. Watermelon rind samples were evaluated using a one-factor-at-a-time (OFAT) evaluation to identify the most significant factor for the sonicator extraction time (0.5-3 hrs), ethanol concentration (20-100%), solvent-tosolid ratio (10:1-50:1 v/w), and sample drying time (24-48 hrs) parameters. The highest yield obtained for the oven drying sample was at one hr extraction time (15%), 100% ethanol concentration (12.5%), 30:1 v/w ratio (12%), and 48 hrs drying (9%). Meanwhile, the extraction yield of dehydrator drying sample was optimized at one hr of extraction time with 10% yield 100% of ethanol concentration with 15.4% yield, 40:1 v/w of solvent ratio with 14.7% yield, and 48 hrs of drying with 8% yield. The optimum extract yield of dehydrator drying sample could be further applied for cosmeceutical application as it produced higher yield compared to oven drying sample.

Exploring the best nutrient management options for improving the maize yield for future climate change scenario with DSSAT crop simulation model in century old Permanent Manurial Experiment

Increasing the C sequestration potential and higher soil organic carbon stocks with the application of organic manures will reflect in the improvement of crop productivity. Long-term monitoring approach is essential to evaluate these impacts, especially given the escalating effects of climate change on agriculture. Recognizing this, a 112-year-long Permanent Manurial Experiment (PME) at Tamil Nadu Agricultural University, Coimbatore, India, investigates the influence of application of organic manures. Utilizing the DSSAT crop simulation model, the study assessed the impact of organic manure, specifically NPK + FYM (Farm Yard Manure), on maize yield over 25 years on a sandy-loam Alfisol. Data collected from the field experiment including crop growth parameters, management options, weather, and soil data were used for simulations. Results showed a 93.8% agreement between simulated and observed yields, endorsing NPK + FYM treatment with a 20% increase in grain yield by 2032 compared to using 100% NPK alone. Furthermore, the study explored future climate change scenarios’ impact on maize yield. It highlighted that NPK + FYM consistently outperformed other treatments, emphasizing its efficacy in increasing the yields under changing climatic conditions. This approach emerges as promising for enhancing carbon sequestration, elevating soil organic carbon stocks, and significantly improving crop productivity. In conclusion, adopting the NPK + FYM treatment is recommended to achieve optimal maize yield outcomes, surpassing the effects of using NPK or FYM independently. This research signifies the potential of combining organic manures with synthetic fertilizers in sustainable agriculture amid evolving climate challenges.

Effect of Integrated Nutrient Management on Growth, Yield and Quality of Potato (Solanum tuberosum L.)

A field experiment was conducted at Instructional farm, DCAAS College Rampur, Dehradun, Uttarakhand, during the Rabi season of 2022-2023 to evaluate the performance of potato under different integrated nutrient management (INM) options. The experiment was placed in randomised block design (RBD) with five nutrient management options. Various parameters related to plant growth, tuber formation, and tuber weight and yield were examined across different treatment conditions. The results revealed that T5 (Vermicompost + Urea + FYM + Neemcake), representing an integrated nutrient management approach, consistently exhibited the highest plant weight (23.633cm) at different growth stages (30 DAS, 60 DAS, 90 DAS), indicating a positive effect on plant growth. Additionally, T3 (Urea) displayed superior performance regarding the number of tubers in different weight categories (0-25g, 25-50g, 50-75g, and 75g), suggesting enhanced tuber formation. However, the most significant outcome was the consistent superiority of T5 in terms of tuber weight and yield. T5 consistently produced the highest weight of tubers in all weight categories and achieved the highest tuber yield per plot (9.243q h-1). These findings underscore the positive impact of integrated nutrient management practices on tuber weight and overall crop productivity in potatoes. It is important to note that specific details regarding the nutrient management practices used were not provided, necessitating further research to identify the particular combination and types of nutrients employed in T5. Overall, this study emphasizes the importance of implementing integrated nutrient management strategies to enhance the growth and yield of potato crops, encouraging further investigation into the optimization of plant growth and tuber yield through nutrient management practices.

Preparation of CaO@CeO2 Solid Base Catalysts Used for Biodiesel Production

The study investigated the use of CeO2 extracted from monazite with calcium oxide (CaO) as a solid catalyst for biodiesel production. The wet impregnation method was used to produce CaO@CeO2 mixed-oxide catalysts with 0–50 wt.% CaO. X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) surface area analysis, thermogravimetric analysis (TGA), and a Fourier transform infrared spectrometer (FTIR) was used to characterize the catalysts. In order to determine the optimal preparation conditions, the effect of different CaO compositions on the performance of CaO@CeO2 mixed-oxide catalysts was examined. The catalytic activity of the CaO@CeO2 catalyst for the transesterification reaction of palm oil to produce biodiesel was studied. The results show that the optimum yield of biodiesel can reach 97% fatty acid methyl ester over the 30CaO@CeO2 catalyst at the reaction conditions of 5 wt.% catalysts, methanol-to-oil molar ratio of 9:1, with a reaction temperature of 65 °C within 30 min. The results show that the high catalytic activity and stability of the CaO@CeO2 catalyst make it a promising candidate for industrial-scale biodiesel production. Further study is needed to improve the stability and efficiency of catalysts in transesterification reactions to achieve a high FAME yield using long-life-span catalysts. Moreover, it is necessary to investigate the economic feasibility of this process for application in large-scale biodiesel production.

Performance of Climate Smart Rice (var. CR DHAN 801): A Case Study from Western Undulating Zone of Odisha, India

This research paper presents a detailed case study conducted in Khairbhadi village of Kalahandi district as a part of the NICRA Project undertaken by Krishi Vigyan Kendra, Kalahandi (OUAT). The study evaluates the performance of the climate-smart rice variety CR DHAN 801 under drought conditions, which is crucial for ensuring food security in regions prone to water scarcity. To assess its effectiveness, the study employed a randomized block design, comparing CR DHAN 801 with two other rice varieties, namely MTU-1001 and Jamuna. The results obtained from the study indicated that CR DHAN 801 consistently outperformed the other two varieties across multiple parameters. This superiority is evident in growth parameters, yield attributes, economic viability, and resilience to water scarcity. CR DHAN 801 exhibited robust growth characteristics, optimal yield potential, and economic viability, making it a promising choice for cultivation in drought-prone regions. These findings underscore the significance of CR DHAN 801 as a resilient climate-smart variety highlighting its potential to contribute significantly to agricultural sustainability and resilience in areas facing water scarcity challenges.

Enhancing faba bean (Vicia faba L.) productivity through establishing the area-specific fertilizer rate recommendation in southwest Ethiopia.

The aim of this study is to establish area-specific NPSB (18.9% N, 37.7% P2O5, 6.95% S, and 0.1% B) fertilizer rate recommendations for the optimal grain yield of faba bean. The field experiment was conducted in two locations in the 2021 and 2022 cropping seasons using a randomized complete block design with three replications. The nine treatments included 0, 25, 50, 75, 100, 125, 150, 175, and 200 kg ha-1 NPSB fertilizer rates. An economic analysis was conducted for grain yield using the International Maize and Wheat Improvement Center procedure. The analysis of variance results showed that blended fertilizer significantly (p < 0.01) affected plant height, number of pods per plant, number of seeds per plant, hundred seeds weight, biomass yield, grain yield (GY), and harvest index. The combined location mean result showed that applying a 125 kg ha-1 NPSB rate produced the highest GY (4857.2 kg ha-1). The result of economic analysis demonstrated that applying a 125 kg ha-1 NPSB rate earned the highest net benefits (212824.0 ETB ha-1) and marginal rate of return (3653.43%). Therefore, a 125 kg ha-1 NPSB fertilizer rate is recommended for high yield and profitability of faba bean production in the study area and other similar soil types.

Optimization of pectin yield extracted from coffee Arabica pulp using response surface methodology

Pectin was extracted from coffee pulp using 0.1 M H2SO4. The Box Behnken Design based Response surface methodology was applied to optimize pectin yield. The impact of extraction time (45–75 min), temperature (80–100 °C), solid to liquid ratio (SLR) (1:20, 1:27.5, and 1:35), and pH (1.5, 2, and 2.5) on pectin yield were studied. Under optimal extraction conditions (84 °C, 75 min, SLR of 1:20 and pH: 1.5), physical, chemical, structural and antioxidant properties of pectin were examined. The results of the physicochemical analysis are: acetyl value: 1.10 ± 0.05 %, equivalent weight: 1429 ± 54 g/mol, anhydrouronic acid: 57.1 ± 0.9 %, degree of esterification: 78.5 ± 1.8 %, moisture content: 8.5 ± 1.5 % and ash content: 4.3 ± 0.9 %. FTIR analysis indicated the (-OH) peak of pectin was lower and shifted left compared to treated and untreated coffee pulp powder. SEM analysis shows a smoother surface, whereas XRD shows a less amorphous structure of pectin. The total phenolic and flavonoid content of coffee pulp pectin was found to be 26.7 μg Gallic Acid Equivalent/mg and 0.8957 μg Quercetin Equivalent/mg, respectively. Antioxidant analysis showed significant antioxidant properties (IC50 = 642.31 ± 30.43 μg/mL). The predicted and actual pectin yields at the optimal extraction condition were 14.39 and 13.7 %, respectively, with R2 = 0.95 that indicate the model can represent the experiment. Therefore, achieving a maximum pectin yield with improved antioxidant and other physicochemical qualities ensures that coffee pulp can potentially serve as a viable commercial source of pectin.

Comparative Study of Planting Time, Growth Regulator and Biofertilizer on Growth, Yield S and Quality of Strawberry Cv Chandler

Climate, growth promoting hormones and soil nutrition are all necessary conditions for the production of any crop. The primary job is also to determine the ideal planting period for optimum crop yield. In order to improve strawberry growth, yield, and quality parameters a field experiment was carried out to evaluate the comparative study of planting time, growth regulator and biofertilizer on growth, yield and quality of strawberry cv Chandler at Horticultural Research Center, Chauras Campus, H.N.B. Garhwal University, Srinagar Garhwal, Uttarakhand, India, during two growing seasons 2018-19 and 2019-20. The present experiment consists of three factors with a total of 08 treatments which was replicated thrice on strawberry cultivar Chandler at different planting time viz., 15th August, 5th September, 25th September and 15th October with the application of various GA3 concentration viz., no GA3 (without application), 50 ppm GA3, 75 ppm GA3, 100 ppm GA3 and with and without treatment with Azotobacter. The treatment under15th October planting time, 75 ppm GA3 concentration with Azotobacter was found most effective for most of the growth, yield and quality traits viz.,plant height (34.57 cm), leaf area (104.66 cm2), number of runners/plant (8.60), days taken to full blooming (202.00), fruit setting % (89.17), days taken to final harvest (214.44), fresh weight of fruit (15.93 g), fruit yield/plant (327.09 g), TSS (9.07 0Brix), vitamin C (67.70 mg/100g), sugar content (7.08%) and juice content (91.06%) whereas the minimum values for most of the characters was observed with 15th August planting time and without application of GA3 and Azotobacter treatment.

Multi-nutrient fertilization-based analysis of fruit quality and mineral element composition during fruit development in Merlot wine grapevine1

Mineral elements play a crucial role in plant growth and development. Ensuring the proper supply of these elements in soil and maintaining an optimum range within plants is necessary for achieving optimal fruit yield and quality. Unfortunately, the application of NPKCaMg fertilizers to fruit trees is often either insufficient or excessive, leading to both environmental degradation and reduced fruit yield and quality. To assess the impact of different fertilizers on the biological-related traits of grape fruit and its response to nutritional elements, Merlot grapevines were subjected to multi-nutrient fertilization over four consecutive growing seasons from 2018 to 2021 in Penglai District, Yantai, China. Principal component analysis revealed that T11 treatment, consisting of N3P3K1Ca2Mg4, was the most suitable fertilizer type and application design for this experiment. The application of T11 resulted in a significant decrease (24.29%–35.20%) in fertilizer usage, and it resulted in an increase in several important traits such as 100 grain weight (HGW), number of seeds (SN), total soluble solids (TSS), total seed phenols (SP), seed flavanols (SFI), and seed tannins (ST) by 3.28%–12.84%, 3.76%–20.03%, 1.11%–14.95%, 2.16%–23.69%, 11.00%–32.78%, 1.07%–23.35%, respectively, compared to T14 (N4P2K3Ca1Mg4), T16 (N4P4K1Ca3Mg2), T13 (N4P1K4Ca2Mg3), and T15 (N4P3K2Ca4Mg1) treatments. Flowering and fruiting behavior exhibited a considerable demand for NPK, with a higher requirement for K and B during fruit growth and development compared to the other mineral elements. Excessive K in soil was found to enhance the competitive inhibition of Ca uptake by Merlot grapevines. The optimum ranges of mineral element content for total peel phenols (PP), peel flavanols (PFI), total peel flavonoids (PFD), total seed phenols (SP), and seed tannins (ST) were primarily influenced by grape variety and nutritional analysis method. In conclusion, the careful selection of NPKCaMg fertilizer and its meticulous application to soil at an optimum range of mineral elements are critical for grapevine growth and development.