Journal of Agricultural Science and Technology
Volume:27 Issue: 3, May 2025

This study applies Artificial Neural Networks (ANNs) to assess the impact of climate factors on the collaborative development of agriculture and logistics in Zhejiang, China. The ANN model investigates how average temperature and rainfall from 2017-2022 influence crop yield, water usage, energy demand, logistics efficiency, and economic growth at yearly and seasonal scales. By training the neural network using temperature and rainfall data obtained from ten weather stations, alongside output indicators sourced from statistical yearbooks, the ANN demonstrates exceptional precision, yielding an average R2 value of 0.9725 when compared to real-world outputs through linear regression analysis. Notably, the study reveals climate-induced variations in outputs, with peaks observed in crop yield, water consumption, energy usage, and economic growth during warmer summers that surpass historical norms by 1-2°C. Furthermore, the presence of subpar rainfall ranging from 20-30 mm also exerts an influence on these patterns. Seasonal forecasts underscore discernible reactions to climatic factors, especially during the spring and summer seasons. The findings underscore the intricate relationship between environmental and economic factors, indicating progress in agricultural practices, with vulnerability to short-term climate fluctuations. The study emphasizes the necessity of adapting supply management to address increased water demands and transitioning to clean energy sources due to rising energy consumption. Moreover, optimizing logistics requires strategic seasonal infrastructure planning.

Oil, as a primary source of energy, has a significant impact on promoting economic activities. Oil provides considerable part of the government's revenue sources. The price of oil has always fluctuated over the years due to various reasons including political, social, and economic developments in different countries. Since the price of oil affects different sectors of the economy, including agriculture, through the government budget and the revenue sources of the government, this study investigated the effect of OPEC oil price fluctuations on the value added of the agricultural sector from 1990 to 2019. The Generalized Autoregressive Score (GAS) Model estimated these fluctuations, while the Nonlinear Autoregressive Distributed Lag (NARDL) method estimated the long-term relationships. In addition to OPEC oil price fluctuations, variables such as the consumer price index, employment in the agricultural sector, and the trade openness degree were examined in the model. The results showed a negative effect of OPEC oil price fluctuations on the agricultural sector's value added. Furthermore, the trade openness had a positive effect on the agricultural value added in the long term. Results indicate that oil income is one of the most important issues that decline agricultural sector's value added, and the government should control this negative relation to develop agriculture as a vital part of the economy.

International collaboration is the key element to expand the horizons of knowledge and technology and to solve sustainability problems. To plan and implement this issue as effectively as possible, this study analyzed the lived experiences of agricultural students about the benefits and challenges of international research collaboration. This applied research used a mixed-method approach in two steps. First, an interview was done with PhD-agriculture students at the University of Tehran, who had published at least one article with international co-authorship in an international journal. Interviews were continued with 19 participants until the saturation point was reached. Interviews were transcribed and analyzed using the six stages of thematic analysis of Clarke and Braun (2006) and by conducting MAXQDA software. Secondly, a questionnaire was developed and conducted to investigate the importance of each of the items from the same 19 students who participated in the interview step. In this step, descriptive statistics were done by using SPSS software/ver23. Percentage, mean, and standard deviation were calculated for descriptive analysis. The findings showed that the international research collaboration had 24 benefit codes in the four dimensions of communication, scientific-research, academic, and personal-professional. On the other hand, 17 challenge codes were categorized into three groups of personal, motivational, and attitudinal group; managing the research and publication process; and cultural, technical, and economic group. Based on the means of benefits and challenges of students’ international research collaboration, the first ranks were “academic” with a mean of 4.06, and “personal, motivational, attitudinal” with a mean of 4.28 for benefits and challenges, respectively. According to the findings, building teamwork skills in higher education is recommended as it can positively promote students’ collaboration with others for research projects. This original and innovative study has theoretical and practical implications and value. The results are beneficial for universities to make decisions and plan activities that enhance students’ international research collaboration.

Livelihood diversification is the key to a sustainable rural economy. The study aimed to assess livelihood diversity, determinants, and constraints among the scheduled caste families in Beraberia village of North 24 Parganas, West Bengal, to plan a foolproof developmental program. Simple random sampling was followed to select a sample size of 108 from the study area. The Simpson livelihood index formula was used to assess the level of livelihood diversification, and the Tobit model was used to find the determinants of the livelihood diversity index. A preferential ranking technique was followed to analyze the constraints in livelihood diversification. The most common livelihood activity in the study area was agriculture, with an income contribution of 60.72%. Around 66% of the households had a medium to high livelihood diversity index. The Tobit regression model result showed that income, economic motivation, and access to credit were the significant determinants of livelihood diversification in the study area. At the same time, the family dependency ratio negatively influenced the Diversification index. Further, the constraint analysis in livelihood diversification revealed that lack of capital (Rank Based Quotient, RBQ 0.77) and livelihood assets (0.75) were significant impediments to livelihood diversification. The study suggests that government bodies must prioritize credit access and capacity building among Scheduled Caste (SC) families in rural areas to create more profitable and sustainable livelihoods among the weaker sections of the society.

Drastically concerned about no longer continuation of instructors to use the computerized Learning Management System (CLMS) in the post COVID-19, the ministerial and academic authorities in Iran are inclined to figure out about the determinants of instructors’ continuation of making use of the CLMS and how to incorporate the CLMS into the face-to-face education. Therefore, this research aimed to analyze drivers of agricultural instructors’ continuation of using CLMS. The instructors’ learning patterns as a knowledge gap, the present causal study surveyed 102 faculty members of two universities in Northwest Iran. To establish a theoretical framework, Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and the Vermunt’s Theory of Learning Model (VTLM) were used, and the items of the questionnaire were designed accordingly. The results revealed that the model had a good fit with the data set, the Perceived Usefulness (PU) of the CLMS had an impact on the attitude towards the CLMS and intention to continue using the CLMS (Behavioral Intention: BI). The Application-Oriented Learning Pattern (AOLP) affects the Perceived Behavioral Control (PBC) positively. Other predictor variables that directly impinge upon instructors’ BI to continue applying the CLMS include attitude, Perceived Usefulness (PU), AOLP, and Perceived Student Readiness (PSR). The estimated multiple correlation coefficients for the PBC, attitude, and BI were 0.17, 0.51, and 0.46, respectively. The results of the research can be useful and effective for agricultural higher education decision makers in using and replacing CLMS in specific situations instead of face-to-face education.

This study conducted an assessment to gauge the impact of reducing agricultural tariffs across diverse scenarios on both food security and macroeconomic variables in Afghanistan. Utilizing a computable general equilibrium model and Afghanistan's social accounting matrix data, the study simulated reductions in tariffs at 80%, 60%, 40%, 20%, and a complete removal (100%) of tariffs (full liberalization). The findings unveiled a progressive uptick in imports and household consumption of key staples like cereals, fruits, vegetables, and livestock. Crucially, this surge in household purchasing power spurred a heightened demand for food items, consequently, bolstering food security and contributing positively to the overall health of the households and society. Therefore, advocating for targeted initiatives aimed at eliminating tariffs on agricultural products emerges as an imperative step, given their tangible impact on enhancing food security and uplifting societal well-being.

Designing the flexible investment strategies for maximizing returns under spatial variation and considering uncertainty in beef cattle investment decision-making are vital. Therefore, the objectives of the study were (i) To explore the real options and its values spatially for beef cattle investments in Turkey, and (ii) To evaluate the adequacy of government support for beef cattle investment spatially. Research data were collected from randomly selected 385 beef cattle farms by using questionnaires. The valuation of real options was assessed by using Binomial Valuation, Black-Scholes Method and Monte Carlo simulation. Tornado diagram was used for exploring sensitivity of decision variables for beef cattle investment. The results of the research showed that the classical Net Present Value (NPV) value was -200.82 thousand US $. The NPV values of the options of wait, expand, and input-output change for the beef cattle investment were US $102.37 thousand, 43.87 thousand, and 24.50 thousand, respectively. The research findings also showed that the value of real options and adequacy of government subsidies varied spatially. Based on the resuts of the sensitivity analysis, the most important variables affecting the investor's decision are carcass meat price, yield rate, capacity utilization rate, and fattening feed price, respectively. The research suggests that policy makers should consider the spatial distribution of investment subsidies and policies to the specific needs of different regions to increase efficiency of investment support policy.

This study evaluated the interactive impacts of water temperature and feeding rate on digestive enzymes, intestine histology, growth and stress-related genes, and cultivable intestinal microbiota of Asian seabass (Lates calcarifer). For this purpose, 180 fish (85.0±3.0 g) were reared at three different temperatures (20, 27, and 33°C) and two feeding rates (apparent satiation and 2.5% of biomass) with three replications for 6 weeks. The results revealed no significant differences among different treatments regarding the activity of digestive enzymes (P˃ 0.05) of fish reared under different temperatures and feeding rates. The length, width, and thickness of intestinal villi were unaffected by different temperatures and feeding rates (P˃ 0.05). In addition, no variations were found in the total aerobic bacterial count of fish gut from different experimental groups (P˃ 0.05). At the molecular level, IGF-I and HSP70 coding genes were found to be highly expressed in experimental treatments (P< 0.05). To conclude, the present study showed that temperatures between 27 to 33°C were more optimal for Asian seabass, and the different temperatures and feeding rates did not affect the digestive enzymes, intestine histology, and gut microbiota of juvenile Asian seabass after 6 weeks.

Organic acids remarkably affect the microbial control, stability, and organoleptic characteristics (flavor, color and aroma) of beverages. This study focuses on the determination of organic acids, including oxalic, citric, tartaric, malic, succinic, lactic, fumaric, acetic, propionic, and gallic acid, in 100 commercial malt beverages from different brands (five Iranian and five various imported brands) and flavored variants (classic, pomegranate, peach, tropical and lemon). In addition, the contents of total phenols, total flavonoids, ascorbic acid, and free amino acids were measured to assess the overall composition. Liquid Chromatography (LC) was employed to develop a method for analyzing the organic acids, while spectrophotometric techniques were used for quantifying other bioactive compounds. The results revealed significant variations in the organic acid profiles, with succinic acid being the most abundant, while tartaric acid was absent in all samples. Chemometrics technique (PCA method) was applied to classify the results. The results show that PCA can classify the malt drinks based on the additive values with a very high precision. To improve the quality control of malt beverages, some extra assessments, like organic acids and free amino nitrogen determination, should be considered for Iranian National Standard.

The present study aimed to develop orange pomace tablets as an additive with nutritional value. Orange pomace powder was converted into tablets by the drying method under the effect of compression force, diameter die, and relaxation force changes. Some of the physicochemical properties (e.g., density, penetration resistance, tensile strength, stability in water, total phenol content, antioxidant capacity, and ascorbic acid) were investigated. The tableting process was optimized by central composite design. The Kawakita and Lüdde model with R2= 0.995 was used to describe the compressibility behavior of orange pomace powder. The effect of diameter die on the minimum tension of deformation changes was insignificant. The results proved that the changes in the value of the active ingredients were insignificant when the orange was dried, ground to powder, and converted to a tablet. Also, the effect of diameter dies changes on all of the responses was significant at 0.01, while the effect of compression force was insignificant just for penetration resistance. Effect of the relaxation force on the mechanical properties was significant (at level of 0.5 for penetration resistance and 0.01 for tensile strength), and on the density and stability in water was insignificant. Finally, the optimum point for tableting from orange pomace was suggested at the compression force of 8.6 kN, diameter die of 10 mm, and relaxation force of 1.14 kN for 1.13×10-3 g mm-3 of density, 111 N of penetration resistance, 52.4 MPa of tensile strength, and 51 g.s dl-1 of stability in water.

Phenylketonuria (PKU) is a genetic disorder necessitating a low-protein and phenylalanine diet. This study aimed to explore the feasibility of producing a low-protein pasta using potato and tapioca starches. The pasta formulation substituted semolina flour with a blend of potato and tapioca starches. Date kernel fiber and xanthan gum were incorporated as prebiotic compounds and texture enhancers, respectively. Physicochemical (moisture, fat, total ash, protein, phenylalanine, cooking loss, cooking time, color indexes, and hardness) and sensory properties (texture, flavor, color, and overall acceptability) were evaluated and compared against the control sample (based on semolina flour). The results demonstrated no significant alteration in moisture and fat content upon substitution, but a significant decrease in ash and protein content (P< 0.05). Consequently, phenylalanine levels decreased from 530.58 mg 100 g-1 in the control sample to 24.49-26.60 mg 100 g-1 in the pasta. Replacing flour with starches increased cooking loss, reduced cooking time, and diminished pasta hardness compared to the control (P< 0.05). The pasta exhibited higher L* and lower a* and b* values than the control. Sensory evaluation revealed that the pasta containing 35% potato starch and 40% tapioca starch attained the highest scores (T5), indicating its favorable acceptability. Overall, this study suggests that the combination of potato and tapioca starches, along with date kernel fiber and xanthan gum (T5), enables the production of low-protein pasta suitable for PKU patients.

Pumpkin (Cucurbita pepo L.) seeds are popular for their dietary and health benefits. However, there are limited data on the pathway between phytochemical and nutritional values of pumpkin seeds. For this purpose, the seeds of some Turkish pumpkin genotypes (NVS-1, NVS-2, KNY, KYS-1, KYS-2, BRS, EDR, and KRK) were analyzed for their amino acids, organic acids, fatty acids, and mineral content. The wide variation between seeds in organic acids (KYS-2, 8.105 ng µL-1; KRK, 1.939 ng µL-1) and amino acids (KYS-2, 32.99 nmol µL-1; KNY, 15.65 nmol µL-1) content was observed. C18:2n6 and C18:1n9 were the most predominant fatty acids in the seeds, whereas C16:1n7 was the least abundant. Considering the mineral contents, seeds were relatively rich in potassium (2560.3-6697.5 mg kg-1), phosphorus (529.8-1120.9 mg kg-1), and magnesium (426- 1124.5 mg kg-1). Moreover, the path diagram of phytochemical properties, nutritional value, and fatty acids of pumpkin seeds was determined. Consequently, the seeds of pumpkin cultivars were examined to find the best potential for a high nutritional value and contribution to the food industry.

Sustainable improvements in agricultural production and productivity necessitate efficient resource utilization and relay intercropping to improve crop yield and land productivity while using fewer inputs. Thus, in a 3-year field trial, different cucurbit vegetable crops were tested to see if they were suitable for relay intercropping with castor (Ricinus communis L.). These treatments encompassed various intercropping strategies involving castor, each paired with a different cucurbits such as bitter gourd (Momordica charantia), ridge gourd (Luffa acutangula), snake gourd (Trichsanthus cucumerina), bottle gourd (Legenaria siceraria), coccinia (Trichsanthus dioica), and cucumber (Cucumis sativus). The results showed that the castor and cucumber relay intercropping systems produced the highest castor equivalent yield (1,701 kg ha-1), followed by castor and ridge gourd (1,596 kg ha-1). Among all the cucurbit intercropping systems, the castor+cucumber relay system had the highest productivity (4.66 kg ha-1 d-1), profitability (4.07 $ ha-1 d-1), and relative economic efficiency (198.5%). The best moisture-use efficiency was achieved by castor and bitter gourd relay intercropping (6.58 kg/ha/mm), followed by castor and bottle gourd relay intercropping (6.35 kg ha-1 mm-1). There was a higher net return for relay intercropping of castor and cucumber ($ 1,483.9 ha-1), followed by castor and ridge gourd ($ 1,446.2 ha-1). Sole castor produced 1312 kg ha-1, despite its low monetary returns of $ 501.6 ha-1. It has been found that relay intercropping between castor and ridge gourd (3.29), followed by castor and bitter gourd (3.29), produces the highest benefit-cost ratio. As a result, the relay intercropping system, which determines the competitive interaction and productivity of castor and cucurbits, can provide the greatest benefits.

The effect of climate factors on the population changes and damage of Peach Twig Borer (PTB), Anarsia lineatella Zeller., was studied during 2007-2017 in Saman Orchards, Iran. Time series data of climate and pest population were subjected to the Mann-Kendall trend analysis. Seasonal flight of the pest was studied using pheromone traps from May to October. The percentage of infested twigs was calculated during May and September, while the percentage of infested fruits was determined twice a month from July to September. Results showed increasing trends in the mean temperature of annual, winter and autumn seasons (Kendall's statistics were 0.63, 0.49 and 0.42, respectively). Moreover, there were significant increasing trends in annual mean minimum, mean maximum, and absolute minimum temperatures (0.53, 0.63 and 0.46, respectively). The number of annual and January frost days (-0.55 and -0.51, respectively) and mean relative humidity of Jun, July, August, September and October showed decreasing trend. PTB population and damage showed significant and increasing trends during the studied years. According to stepwise regression analysis, the percentage of relative humidity, mean annual minimum temperature and mean annual temperature were the most statistically significant variables influencing the percentage of infested branches (r= 0.94, r2= 0.88, F(3,6)= 14.40, P= 0.004) and pest population (r= 0.98, r2=0.96, F(4, 5)= 3.18, P= 0.001). The pest population and damage will increase under the studied climate change scenarios (A1F, A1T, A1B, A2, B1 and B2) in the future, which is more significant in A1F than others.

The present research was conducted to evaluate the efficacy of six different entomopathogenic fungi and bacterial formulation against the third-instar grubs of a subterranean biennial white grub species, Lepidiota mansueta. All treatments proved effective, recording over 55% mortality of white grubs compared to the untreated control at 30 Days After Treatment (DAT). However, the highest cumulative mortality (76%) was observed in Beauveria bassiana (KR855715), followed by 72% in Beauveria brongniartii (BbUASB16) and 70.67% in Bio-Bt (Bacillus thuringiensis) treated grubs. Metarhizium anisopliae-based formulation (Bio-Meta) exhibited the lowest mortality rate (58.67%). Overall, B. bassiana (KR855715) and B. brongniartii (BbUASB16) demonstrated higher virulence towards L. mansueta grubs, indicating their potential as biological control agents against these pests. The LT50 values varied from 12.15 to 23.05 days when L. mansueta grubs were treated with different entomopathogenic treatments. In case of KR855715 strain, the LT50 value recorded was 12.15 days (FL 11.15-13.11), which was the lowest, and in Bio-Meta, the LT50 recorded was 23.05 days (FL 19.24-30.33), which was the highest. In conclusion, as chemical pesticides are not always the best option for controlling scarabs, entomopathogenic fungus can be incorporated into Integrated Pest Management (IPM) strategies as biological control agents. This is especially useful for managing populations of early-season white grubs. Therefore, to keep the pest population in an environmentally balanced level and to provide long-term control for the grubs, these tested entomopathogens may serve as possible biocontrol agents against L. mansueta grubs.

Potassium (K) mitigates the effect of high temperature on canola, especially during its later growth stages when sowing of canola is delayed. To explore the effect of K on high temperature tolerance and canola production, a field experiment (2019–2021) was conducted. The experiment had two sowing dates (October 15 and November 1) and four K treatments, i.e. control, soil application (50 kg K ha-1), soil application+0.25% K foliar spray at pre- and post-flowering stages, and soil application+0.50% K foliar spray at pre and post-flowering stages. Application of 50 kg K ha-1 as soil application along with 0.50% K-foliar sprays resulted in higher production of biochemicals (superoxide dismutase, peroxidase, catalase, and total soluble sugars) besides net photosynthetic rate and stomatal conductance along with less malondialdehyde production and relative cell injury in crops sown on November 1st than untreated plants. Moreover, it also enhanced chlorophyll florescence and chlorophyll (a and b) contents of late-sown crop. Plants sown on November 1st and received 50 kg K ha-1 as soil application along with 0.50% K foliar spray also gave a higher yield and economic returns than the control. Therefore, it is suggested to supply 50 kg K ha-1 at sowing and a foliar spray of 0.50% K at the pre- and post-flowering stages to canola sown late in the season to achieve optimal and economical yield levels.