Important Agricultural Products Research Articles

Design, construction and field testing of a manually feeding semiautomatic sugarcane dud chipper

Sugarcane is the main sugar crop, and sugar is an important agricultural product in Egypt. There are many problems with the technology used in the current planting method of sugarcane, which has a great impact on the planting quality of sugarcane, which have a series of problems, such as low cutting efficiency and poor quality. Therefore, the aim of the current study was to design, construct, and field testing of a semiautomatic sugarcane bud chipper assisted with pivot knives for cutting sugarcane buds and germinating them in plastic trays inside a greenhouse until they reached an average length of 35 cm, and then planting them in the field. In the field tests five cutting speeds (35, 40, 45, 50, and 56 rpm. (Revolution Per minute), three cutting knives (1.5, 2.0, and 2.5 mm) were used for cutting sugarcane stalks with four different diameters (1.32, 1.82, 2.43, and 2.68 cm). The obtained results showed that the values of the damage index and invisible losses were within acceptable limits (ranging between − 1.0 and 0.0) for all the variables under the test. Still, the lowest damage index and invisible losses were recorded with the buds that were cut with a knife of 1.5 mm thickness and cutting speeds less than 50 rpm. The skipping rate increases with the increase in cutting speed and stalk diameter, ranging between 0.0 to 13%. The maximum machine productivity was 110 Buds per minute at a cutting speed of 35 rpm and stalk diameter of 1.32 cm. The paper's findings have important application values for promoting the designing and development of sugarcane bud chipper and sugarcane planting technology in the future.

Analysis of Factors Affecting the Innovation Level of Agricultural Operators

In this research, it is aimed to determine the factors affecting the innovation level of agricultural enterprises. Konya province was chosen as the research area because it is one of the important agricultural production centres in Türkiye. Stratified random sampling method was used within the scope of the study. A total of 268 agricultural enterprise owners were interviewed face to face and survey data were compiled. Multiple regression model was applied in the analysis of the factors affecting the perception of innovations by the operator. In this research, considering the characteristics of the data collected by the questionnaire, the linear regression model, which uses functional forms in regression models, was used. In the study, innovation index was taken as the dependent variable in the linear regression model. Independent variables were determined as education, experience, number of parcels, amount of land, active capital, amount of land, agricultural income, following innovations, receiving training on agricultural issues, participating in agricultural activities, following events related to agriculture on social media and cooperation with institutions. As a result of the model, a positive relationship was determined between education, experience, number of parcels, amount of land, active capital, amount of land, agricultural income, following innovations, receiving training on agriculture-related issues, participating in agriculture-related activities, following agriculture-related events on social media and cooperation with institutions and innovation index.

Identifying the abilities of biostimulants to improve vegetable production compared with conventional fertilizer

Vegetables are important agricultural products with numerous health benefits. Excessive chemical fertilization to meet the food challenge has resulted in environmental and soil health hazards. Considering this aspect, the current study was conducted with the aim to introduce biostimulants as an alternative to chemical fertilizers to improve soil quality, crop quality, and yield. In the first experiment, the response of radish was noted against the application of glycine (GLY), aspartic acid (ASP), lysine (LYS), vitamin B complex (VBC), and chemical fertilizers (CF). The biostimulants were sourced from Sigma Aldrich and Martin Dow Market Ltd. The results indicated that ASP has significantly improved the phenolic contents in shoot (1.01%) and root (12.23%) compared with CF. Additionally, total protein was significantly increased in shoot with GLY (251.81%) and in root with ASP (57.06%). Shoot ascorbic acid contents were significantly improved with ASP (179.90%), VBC (159.91%), and LYS (139.92%). Plant fresh and dry weight was improved with VBC (478.31%) and ASP (364.73%). The N and P concentrations in radish root were higher in VBC (25.93%) and LYS (100%). Soil organic matter was improved ASP (61.51%), followed by VBC (60.13%). Soil available P concentration was also enhanced with LYS (40.43%), ASP (31.20%), and VBC (23.19%). The second experiment was focused on identifying the response of turnip crop against the following treatments: chemical fertilizers (CF), Isabion® (ISA), 25% CF + LYS + GLY (CLG), 25% CF + ASP + GLY (CAG), and 25% CF + ASP + LYS (CAL). The biostimulants were sourced from Sigma Aldrich Syngenta, Pakistan. The results denoted that CAL and ISA significantly improved the phenolic contents in turnip shoot and root. The ascorbic acid in turnip shoot was improved with CAL (19.27%), CAG (18.13%), ISA (17.68%), and in root with CLG (26.96%). The P concentration in turnip shoot was significantly higher in ISA (19.25%), CLG (16.85%), and CAG (12.26%). Soil total N was improved in all treatments. ISA improved the available P concentration, whereas CF (67.87 mg kg−1) followed by ISA (65.93 mg kg−1) improved the soil available K. Both studies conclude that biostimulants capable of improving vegetable quality.

Extracts with antifungal activity against Botrytis cinerea from potato industry waste

Potato tuber (Solanum tuberosum L.) is the fourth most important agricultural product after wheat, rice, and maize. Fresh potatoes or processed potato products generate large amount of by-products, such as peel, leaves, and stems. In peel and leaf potato, organic acids, amino acids, phenolic acids, flavonoids, iridoids, oxylipins, glycoalkaloids among other compounds have been identified. In this work, potato leaves were used to extract compounds with antifungal activity against the phytophatogenic fungus Botrytis cinerea. Solvents with different polarities were used to extract bioactive compounds from potato leaves. The purification of bioactive compounds from leaf extracts from S. tuberosum was performed in various chromatographic steps, obtaining a bioactive fraction with at least two compounds. Based on the spectroscopic and thin-layer chromatographic data analysis, it can be suggested that this active fraction would have a terpenoid and an aromatic compound. This fraction inhibited the mycelial growth of B. cinerea with an ED50 of 4.3 mg L−1. The unpurified extracts showed only pro-oxidant activity; however, the bioactive fraction did not show pro-oxidant or antioxidant effects. The results of this work suggest that potato by products can be used in the production of biofungicides to control to B. cinerea.

Green technology innovation, trade deficit and carbon emission transfer in agriculture under the new “dual circulation” development pattern of China

Under the new development pattern of domestic and international “dual circulation” in China, studying the relationship among green technology innovation, agricultural trade deficit (ATD) and carbon emission transfer embodied in agricultural trade (ATCT) becomes crucial for achieving coordinated and unified high-quality economic development and efficient environmental protection. Based on this, the paper uses environmental input–output model, “two-stage” decoupling and recoupling model, panel vector auto-regressive model, spatial econometric model and “rolling” Grey-BP neural network prediction model to explore present status of ATD, ATCT and their relationship, driving role of green technology innovation, as well as whether that relationship will be improving in the future. The results reveal the following: (1) China's ATD and ATCT show an increasing trend year by year, and their inter-provincial differences are gradually significant over time. The overall relationship between ATD and ATCT does not display ideally, which makes it necessary to quickly transform that relationship into reasonable and ideal state. (2) Green technology innovation has significant positive “U-shaped” and inverted “U-shaped” local effects on ATD and ATCT respectively, with a reasonable range of ATD reduction while ATCT increase valuing from 0 to 0.290, and has significant positive “U-shaped” spatial spillover effect on both without any reasonable range. The short-term effect of green technology innovation on coordinated promotion between ATD and ATCT is superior to the long-term one. (3) Green technology innovation has a significant regional heterogeneity. Regional differences must be taken into consideration seriously, and the measures adapted to local conditions are crucial. The role of fundamental and progressive green technology innovation has heterogeneity, which means that targeted development and utilization of green technology products are important. (4) Regardless of the time horizon, the relationship between ATD and ATCT will improve, which can provide a key step for coordinated development of economy and environment in agricultural trade. Therefore, in order for China to implement and promote further opening-up, reduce agricultural trade dependence, ensure food security and important agricultural product supply, as well as achieve the unity of high-quality economic development and ecological efficient protection, it is necessary to reasonably reverse trade deficit and increase carbon emission transfer in agriculture.

Short-Term Forecasting of Pork Price Based on The ARIMA Model

China's large population requires a large and diverse amount of food, of which pork is one of the important agricultural products related to the national economy and people's livelihood. Based on the pork price data from 2010 to July 2023, this paper adopts the ARIMA time series model to forecast the pork price in the short term from August 2023 to February 2024 in order to provide a powerful reference for the macroeconomic management of the country. After testing, the ARIMA model has a certain guiding and reference value for predicting the high and low pork prices in the short term, which can provide a decision-making basis for the macroeconomic management of the country.

Innovative measurement, trade-off-synergy relationship and influencing factors for agricultural net carbon emissions and effective supply of agricultural products in China

Sensitive zone of global climate change has been formed in China, and it has become a hot topic how can agriculture ensure food security and the supply of important agricultural products while achieving the “Dual Carbon” goal in the country. Based on such background, this paper uses the IPCC carbon emission calculation method, environmental input-output model and economic-water-carbon coefficient method to measure agricultural net carbon emissions, adopts bivariate spatial auto-correlation analysis and SYS-GMM to explore separately the relationship between agricultural net carbon emissions and effective supply of agricultural products, as well as the carbon reduction effect, growth effect and reasonable range of green technology innovation. The results show that: (1) China's agricultural net carbon emissions reveal a spatial distribution of “higher in the east than in the west than in the center” and a temporal characteristic of increasing year by year; China's effective supply of agricultural products shows an increasing trend and a spatial distribution of “higher in the east than in the center than in the west” in 2006–2012 and “higher in the east than in the west than in the center” in 2013–2020. (2) In 2006, 2010, 2015 and 2020, the number of provinces that belong to low-low agglomeration trade-off zone, low-high agglomeration synergy zone, non-significant zone, high-low agglomeration non-trade-off-synergy zone and high-high agglomeration trade-off zone averagely accounted for 12.500 %, 30.000 %, 26.667 %, 9.167 % and 21.667 % of the totality, respectively. (3) The carbon reduction and production growth effects of green technology innovation both show an inverted “U-shape”, and green technology innovation is conducive to both reducing agricultural net carbon emissions and improving supply of agricultural products when it is within a reasonable range of greater than 0.930. (4) Green technology innovation not only has significant spatial and temporal heterogeneity impact, but also exhibits a differential effect on productive agricultural carbon emissions, agricultural trade carbon emissions, agricultural carbon sinks, total output of agricultural products and agricultural net imports in international trade. Therefore, it is proposed that China should establish and improve green technology innovation incubation platforms, guide all participants to ensure the investment and application of green technology products within a reasonable range, formulate and implement regional differential policies and plan in accordance with local conditions, drive ultimately coordinated promotion of agricultural carbon emission reduction and product supply guarantee and lay an important foundation for achieving high-quality economic development and efficient ecological protection.

Transcriptomic Data Analysis Using the Galaxy Platform: Coffee (Coffea arabica L.) Flowers as Example.

Coffee, an important agricultural product for tropical producing countries, is facing challenges due to climate change, including periods of drought, irregular rain distribution, and high temperatures. These changes result in plant water stress, leading to significant losses in coffee productivity and quality. Understanding the processes that affect coffee flowering is crucial for improving productivity and quality. In this chapter, we describe a protocol for transcriptome analysis using available Internet software, mainly in the Galaxy Platform, using RNA-Seq data from flowers collected from different parts of the coffee tree. The methods presented in this chapter provide a comprehensive protocol for transcriptome analysis of differentially expressed genes from flowers of coffee plant. This knowledge can be utilized in coffee genetic improvement programs, particularly in the selection of cultivars that are tolerant to water deficit.

Selecting reasonable soil moisture-maintaining measures to improve the soil physicochemical properties and achieve high yield and quality of purple garlic in the China Hexi Corridor oasis agricultural area.

Agricultural plastic film, as an important agricultural production material in the China Hexi Corridor oasis agricultural area, is widely used in the intensive production process of purple garlic, which plays an important role in increasing yield, improving quality, ensuring supply, etc. However, the difference in decomposition characteristics between ordinary plastic film and degradable plastic film may affect soil moisture and temperature, thereby affecting soil biochemical properties. Therefore, we conducted a study to solve this problem. Specifically, in the Minle area of the Hexi Corridor, we selected 10 moisture-maintaining measures of ordinary transparent plastic film, transparent oxo-biodegradable plastic film (50-, 80-, and 110-day induction period), ordinary black plastic film, black oxo-biodegradable plastic film (50-, 80-, and 110-day induction period), wheat straw, and aubergine-super absorbent polymers and used the traditional open field without super absorbent polymers as a control. To analyze the effects of different moisture-maintaining measures on soil quality, garlic yield and quality, and water-fertilizer productivity in purple garlic farmland, and conduct a comprehensive evaluation of moisture-maintaining measures using principal component analysis. The results showed that all the moisture-maintaining measures could increase garlic yield, improve bulb quality and water-fertilizer productivity, improve the soil hydrothermal conditions, maintain soil fertility, increase the microbial quantity, and improve enzyme activity. Overall, transparent plastic film mulching was superior to black plastic film mulching, straw mulching, and A-SAP, with 110-day transparent oxo-biodegradable plastic film mulching being the most effective, and was not significantly different from the ordinary transparent plastic film. Compared with other moisture-maintaining measures, the yield, water productivity, irrigation water productivity, and nitrogen fertilizer partial factor productivity of purple garlic were significantly increased by 13.33% to 119.77%, 13.81% to 126.77%, 13.41% to 119.95%, and 13.33% to 119.76%, respectively. Meanwhile, the contents of allicin, soluble sugar, soluble protein, crude fiber, and amino acid content were increased by 1.44% to 14.66%, 4.64% to 36.46%, 0.38% to 28.27%, 1.89% to 26.29%, and 0.38% to 3.74%, and, due to the prolongation of oxo-biodegradable plastic film induction period, the soil microbial community changes from "fungi type" to "bacterium type," reducing the occurrence of soil diseases and improving soil quality. On the basis of the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, the soil quality was evaluated, and the yield, quality, and water productivity of garlic were comprehensively evaluated under each moisture-maintaining measure using principal component analysis. It was determined that the best soil quality and better bulb quality as well as higher garlic yield and water productivity were obtained when using the 110-day induction period transparent oxo-biodegradable plastic film. It can be used as a more reasonable moisture-maintaining measure and technical reference for the purple garlic industry in the China Hexi Corridor oasis agricultural area, which can ensure the improvement of quality and stabilization of yield and also solve the risk of environmental pollution caused by plastic film mulching at the source.

First Report of Vacuiphoma oculihominis Causing Fruit Rot on Navel Orange (Citrus sinensis) in China.

Newhall navel orange [Citrus sinensis (L.) Osbeck] is an economically important agricultural product in China. In February 2022, a rare lesion symptom was observed on Newhall navel oranges that were harvested from an orchard Ganzhou city, Jiangxi province, China (25.53° N, 114.79° E) and stored for 90 days (18±2℃, 80 to 90% RH) at the Jiangxi Key Laboratory for Postharvest Technology and Non-destructive Testing of Fruits and Vegetables (28.68° N, 115.85° E). Approximately 2% (15/750) of the oranges exhibited symptoms, with normal appearance but ink-black flesh and juice, yellowish lesions on edges of the symptoms, and no unusual odor. To isolate the pathogen, three 5 × 5 mm pieces of symptomatic tissue from a diseased orange were disinfected in 75% ethanol for 30 s, rinsed three times with sterile water, and inoculated on potato dextrose agar (PDA) at 25±1℃ and a 12:12 h photoperiod for 7 days. A pure isolate named ND-hsp was obtained. The colony was light yellow center with pale edge on the top and brown on the bottom. Conidia and pycnidia were observed on PDA medium after 2 months. Conidia were long oval, no septa, 2.9 × 3.4 μm (n = 50), and pycnidia were solitary, 39.4 × 43.9 μm (n = 20), with one or no orifice, brown to dark brown. The morphological characteristics of ND-hsp strain on PDA, oatmeal agar and malt extract agar were similar to those of the Didymellaceae (Aveskamp et al. 2010). Ulteriorly, the genomic DNA of the ND-hsp isolate was extracted from its mycelia using a fungal genomic DNA extraction kit (Solarbio, Beijing, China) for subsequent phylogenetic analyses. Four primer sets, LR0R (Rehner and Samuels 1994) /LR7 (Vilgalys and Hester 1990), V9G (Hoog and Gerrits 1998) /ITS4 (White et al. 1990), Btub2Fd/Btub4Rd (Woudenberg et al. 2009) and RPB2-5F2 (Sung et al. 2007)/RPB2-7cR (Liu et al. 1999) were used to amplify the corresponding DNA fragments of large subunit ribosomal RNA (LSU), internal transcribed spacer region (ITS), beta-tubulin gene (TUB2) and RNA polymerase Ⅱ second largest subunit (RPB2), respectively. The obtained sequences were assigned GenBank accession numbers and showed 99 to 100% identity with their counterparts of Vacuiphoma oculihominis UTHSC DI16-308. A phylogenetic tree was constructed in MEGA 7.0 using the concatenated sequences, placing the isolate within the V. oculihominis clade by 100% bootstrap support. Pathogenicity experiments were performed in triplicate. Ten Newhall navel oranges were surface sterilized with 75% ethanol and inoculated with 15μL of a spore suspension (2×106 spores/ml) into a 3 mm-diameter wound on the equator. The control group received sterile water instead of the spore suspension. Treated and control oranges were incubated at 25±1 ℃ and about 90% relative humidity for 20 days. All oranges were cut longitudinally or transversely through the inoculated wound and examined internally. The oranges inoculated with ND-hsp exhibited ink-black flesh and juice symptoms consistent with the initial oranges. The control oranges remained asymptomatic. Under the Koch's rule, V. oculihominis was reisolated from diseased oranges and kept in Collaborative Innovation Center of Postharvest Key Technology and Quality Safety of Fruits and Vegetables in Jiangxi Province. GenBank database analysis confirms that V. oculihominis has been found in human eye secretions and decayed trees. This is the first report of V. oculihominis as a pathogen on navel oranges in China. Our findings contribute to understanding of citrus fruit pathogens.

Construction of Mathematical Start-Up Business Index Formulation for Swiftlet Ranching Industry in Malaysia

An important agricultural product exported by Malaysia is swiftlet nests. Due to its high demand many entrepreneurs venture in this industry. Hence with the bioactive ingredients and dietary values are significant in support the manufacture of medicines in EBN. However, there are a lot of entrepreneurs who unable to fulfill the request of EBN production and failed in this industry. To prevent failure in the birds' nest swiftlet ranching industry, a mathematical modelling formulation should be developed. Thus, the purpose of the research is to construct a general formulation of the start-up business index equation for the swiftlet ranching industry in Malaysia. Experts interviewed found that there were eight factors of starting a business that mattered. Based on the findings, the weightage of the start-up business factors has been used in constructing the general formulation of start-up business index function of the swiftlet ranching industry in Malaysia. Hence, we will develop the system of start-up business factors in the swiftlet birds nest ranching industry using the general formulation of the start-up business index equation.

Influence on Physical and Mechanical Properties of Concrete Using Crushed Hazelnut Shell

Concrete production requires a significant amount of natural resources, with aggregates comprising between 55% and 80% of the total volume. However, the over-exploitation of natural aggregates has led to the exploration of alternative materials for use in concrete production. In this study, crushed hazelnut shells were investigated as a partial replacement for fine aggregate, addressing the problem of natural resource depletion and offering a second use for this important agricultural waste product available in Chile. Hazelnut shells were incorporated in percentages of 2.5%, 5%, and 10% by weight of sand for water/cement ratios of 0.4 and 0.5. The compressive strength at 7 and 28 days and bending strength at 28 days were determined, alongside physical properties such as the workability, temperature, air content, fresh density, and hardened density of the concrete. Our findings showed that replacing 2.5% of the fine aggregate with hazelnut shells led to a higher compressive strength at 28 days, exceeding the strength of the standard specimens by 9.5%, whereas replacing 5% of the fine aggregate led to the highest bending strength, exceeding the strength of the standard specimens by 3.5%. Moreover, the 0.4 w/c ratio consistently led to better results for both compressive and bending strength, with fewer and lower reductions in mechanical strength compared to the standard mixture. Our results suggest that concrete mixes with hazelnut shells as a replacement for fine aggregate at a percentage of up to 2.5% can be used in construction systems with a compression strength lower than 17 MPa, and mixtures with up to 10% hazelnut shell replacement can be used in structures with tensile bending stress requirements lower than 6 MPa. Overall, the use of hazelnut shells as a partial replacement for fine aggregate in concrete production presents an environmentally friendly and cost-effective solution for the construction industry.

Effectiveness of Some Environmentally Friendly Products on Hazelnut Powdery Mildew Caused by Erysiphe corylacearum

Objective: Powdery mildew disease caused by Erysiphe corylacearum is one of the main diseases affecting the yield and quality of hazelnut (Corylus avellana L.), one of the most important agricultural products of Türkiye. The study was conducted in Giresun in 2017 to determine the effect of some environmentally fiendly products (one biological fungicide, one fungicides containing plant extract and one plant activator) against the disease.
 Materials and Methods: As environmentally fiendly products against to disease, commercial products including AQ 10 (Ampelomyces quisqualis M-10 isolate), Regalia (Reynoutria spp. extract) and ISR 2000 (Lactobacillus acidophilus fermentation product) were used. For comparison Quadris Maxx (Azoxystrobin 200 g/l+Difenoconazole 125 g/l), a chemical fungicide known to be effective against this disease, was also used in the study. A total of five spraying applications beginning at the fruit setting time, prior to appearance of disease symptoms were performed. Disease severity values on hazelnut leaves and fruits were calculated according to the Townsend-Heuberger formula using the 0-4 scale. The efficacy of fungicides was determined using Abbott’s formula. 
 Results: The effectiveness of AQ 10 (Ampelomyces quisqualis M-10 isolate) was 21.07% on leaves and 21.29% on clusters; for Regalia (Reynoutria spp. extract) 19.13% and 28.09% anf for ISR 2000 (Lactobacillus acidophilus fermentation product) 19.23% and 10.80% on leaves and fruits respectively. Regarding chemical fungicide, Quadris Maxx (Azoxystrobin 200 g/l+Difenoconazole 125 g/l), the effectiveness was 91.98% on leaves and 73.63% on clusters.
 Conclusion: The chemical fungicide Quadris Maxx (Azoxystrobin 200 g/l+Difenoconazole 125 g/l), used in this study provided sufficient efficacy for the disease control, while the efficacy of environmentally friendly products used was found to be quite low. However, it is very important to use of environmentally friendly products for the disease control and the further studies should be conducted.

Corn Disease Detection Using Transfer Learning

Detecting plant disease is a complicated yet important task to enable sustainable production in agriculture. Especially, early and on-field disease detection provides an opportunity to producers to take necessary precautions before it causes dramatic losses. Corn is one of the most important agricultural products for many countries around the world. It constitutes the main nutrient intake for large populations. This study examines and analyzes the applicability of the pretrained models in corn disease detection. A number of well-known pretrained models including Xception, ResNet50, VGG16, EfficientNetB0, MobileNet and InceptionV3 have been employed for this purpose. SMOTE is employed to solve the imbalanced data and resulting bias problem, which is a common problem in plant disease dataset. The study results indicate that SMOTE provides a good solution to the imbalanced data problem and MobileNet, VGG16 and Xception can be used as base models to develop AI applications to detect corn diseases.

Performance Analysis of Deep Transfer Learning Models for the Automated Detection of Cotton Plant Diseases

Cotton is one of the most important agricultural products and is closely linked to the economic development of Pakistan. However, the cotton plant is susceptible to bacterial and viral diseases that can quickly spread and damage plants and ultimately affect the cotton yield. The automated and early detection of affected plants can significantly reduce the potential spread of the disease. This paper presents the implementation and performance analysis of bacterial blight and curl virus disease detection in cotton crops through deep learning techniques. The automated disease detection is performed through transfer learning of six pre-trained deep learning models, namely DenseNet121, DenseNet169, MobileNetV2, ResNet50V2, VGG16, and VGG19. A total of 1362 images of local agricultural fields and 1292 images from online resources were used to train and validate the models. Image augmentation techniques were performed to increase the dataset diversity and size. Transfer learning was implemented for different image resolutions ranging from 32×32 to 256×256 pixels. Performance metrics such as accuracy, precision, recall, F1 Score, and prediction time were evaluated for each implemented model. The results indicate higher accuracy, up to 96%, for DenseNet169 and ResNet50V2 models when trained on the 256×256 pixels image dataset. The lowest accuracy, 52%, was obtained by the MobileNetV2 model when trained on low-resolution, 32×32, images. The confusion matrix analysis indicates the true-positive prediction rates higher than 91% for fresh leaves, 87% for bacterial blight, and 76% for curl virus detection for all implemented models when trained and tested on an image dataset of 128×128 pixels or higher resolution.

Vertical flow wetlands as the core for the sustainable treatment of coffee wastewater in small communities in Colombia: preliminary results of the treatment of coffee wastewater in rural areas by vertical flow wetlands.

Coffee is one of the most important agricultural products in Colombia. To date, small-scale Colombian coffee growers have developed this activity with a simple infrastructure and random use of water that generates harmful by-products to the water resource mainly in the stage of separation of the mucilage. The coffee mucilage wastewater (CMW) is composed of high organic loads and its impact on water sources is due to its high load of nutrients such as nitrogen (N), phosphorus (P), and chemical oxygen demand (COD) values of over 25,000 mg/L. However, there is no consensus on what treatment can be used, especially whether it is accessible to coffee producers. Thus , the aim of this study consisted of assessing the performance of the combination of a carbon filter (CF) as pretreatment and vertical flow wetland (VFW) as a Natural-based Solution (NbS). The results show a reduction of more than 85% of COD, 96% of total solids, and UV254 close to 94%. It was remarkable that both treatments are appropriate for waters with a high concentration of solids. Finally, it can be concluded that CF + VFW is a feasible technology to treat the coffee wastewater from small communities of coffee producers.

Research on the impact of internet use on fertilizer and pesticide inputs: Empirical evidence from China

Fertilizers and pesticides are important agricultural production materials. Excessive use of fertilizers and pesticides can cause negative impacts such as decline in the quality of farm products and damage to the ecological environment. Increasing the efficiency of fertilizers and pesticides is an important step to accelerate the green transformation of agriculture. Using data from the 2015 China Household Finance Survey, this paper analyzes the impacts of Internet use on fertilizers and pesticides by farmers, and the mechanism behind the action with the help of the propensity score matching method and the instrumental variable method. The findings are: (1) Farmers who use the Internet have greater inputs of fertilizers and pesticides compared to farmers who do not use the Internet. (2) Farmers who do not use the Internet would have their inputs of fertilizers and pesticides increased by 21.9% and 47.7%, respectively, if they had used the Internet under the counterfactual hypothesis. (3) In the heterogeneity analysis, Internet use plays a positive and significant role in the inputs of fertilizer and pesticide in the eastern part of China, and Internet use has greater impact on pesticide inputs than on fertilizer in central and western regions. (4) Internet use has a positive and significant effect on fertilizer and pesticide inputs in both lower scale and higher scale operations, and a positive but not significant effect in moderate-scale operations.

Ecological Risk Assessment and Source Identification of Heavy Metals in Soils from Shiyang River Watershed in Northwest China.

Shiyang River Watershed is an important ecological barrier and agricultural production area in Northwest China, and the study of soil heavy metal content, distribution, and sources is important for agricultural product safety, pollution control, and ecosystem health. In this paper, 140 soil samples were collected from 28 stations to assess the level of heavy metal (Arsenic (As), Copper (Cu), Lead (Pb), Cadmium (Cd), Chromium (Cr), Mercury (Hg), Nickel (Ni), Zinc (Zn)) contamination, pollutant sources and influencing factors of soil in Shiyang River Watershed through determination of the metal contents and statistical analysis. The results indicated that the soils in the study area are typical saline soils in arid zones. The enrichment factors (EF) of As, Cr, Cu, Ni, Zn, and Pb indicate no contamination, and the EFs of Cd and Hg suggested minor contamination. Although the concentrations of Cd and Hg in soil are lower than others, they are more biotoxic and exhibit a moderate-high ecological risk. The index of geoaccumulation (Igeo) values reflect that most of the stations, especially the three groups of samples from depths of 10-20 cm, 20-40 cm, and 40-80 cm, are below the contamination threshold for all heavy metals. The chemical speciation of heavy metals, principal component analysis, and correlation analysis showed that Cr, Cu, Pb, Cd, Ni, and Zn mainly come from the natural accumulation upon weathering of soil-forming matrices. Hg and As mainly come from anthropogenic contributions. The effect of agricultural crop cultivation on soil heavy metal contamination is mainly through farm irrigation and crop-soil interactions, which accelerate the release of heavy metals through the weathering of soil-forming parent material and irrigation, which transports the heavy metals below the surface. The results of this study can provide a scientific basis for the involved authorities to formulate reasonable policies on environmental protection and pollution control.

CPD-CCNN: classification of pepper disease using a concatenation of convolutional neural network models

Agricultural products are vital to the sustainability of the economies of developing countries. Most developing countries’ economies such as Ethiopia heavily rely on agriculture. On a global scale, the pepper crop is one of the most important agricultural products in terms of human food security. However, it is susceptible to a variety of diseases which include blight leaf disease, gray leaf spot, common rust, fruit rot disease, powdery mildew symptoms on pepper leaf, and other related diseases that are all common today. Currently, more than 34 different pepper diseases have been discovered, resulting in a 33% average yield loss in pepper cultivation. Conventionally, farmers detect the disease using visual observation but this has its own demerits as it is usually not accurate and usually time consuming. In the past, a number of researchers have presented various methods for classifying pepper plant disease, especially using image processing and deep learning techniques. However, earlier studies have shown that binary classification requires improvement as some classes were more challenging to identify than others. In this study, we propose a concatenated neural network of the extracted features of VGG16 and AlexNet networks to develop a pepper disease classification model using fully connected layers. The development of the proposed concatenated CNN model includes steps such as dataset collection, image preprocessing, noise removal, segmentation, feature extraction, and classification. Finally, the proposed concatenated CNN model was evaluated, providing a training classification accuracy of 100%, validation accuracy of 97.29%, and testing accuracy of 95.82%. In general, it can be concluded from the findings of the study that the proposed concatenated model is suitable for identifying pepper leaf and fruit diseases from digital images of pepper.

Synthesis and insecticide evaluation of some new oxopropylthiourea compounds as insect growth regulators against the cotton leafworm, Spodoptera littoralis

In this project we aim to share in increasing the production of the most important non-food agricultural product i.e. cotton via protection of it is plant. The usage of safe alternatives to the pesticides has become crucial due to several serious issues associated with the use of insecticides. Therefore, the families of new eco-friendly organic compounds that contain manly oxopropylthiourea scaffold will synthesis in their pure state by using green procedures. This compounds includes (i) poly functional substituted oxopropylthiourea, (ii) dihydroquinoline carboxylic acid, In second category, the structure of this compounds which may be related to the most famous insect growth regulators insecticides, will confirmed by elemental and modern spectroscopic analyses (such as IR, UV, 1HNMR and 13CNMR). In the final category, the synthesized compounds was checked toward the second & forth instar larvae of cotton leafworm, Spodoptera littoralis. The present data proved that values of LC50 of the most effected synthesized compound 8 was 2.412 ppm in which LC50 for commercial lufenuron was 2.295 ppm. Component 8 may be particularly effective due to the presence of fluorophenyl, cyanoacetamide, and carboxalic acid groups in their chemical makeup. In an additional effort to slightly improve insecticidal compounds, evaluation of the latent effects of the examined components on a number of biological parameters, such as adult longevity, pupal weight, proportion of normal, deformed pupae, & adult emergency, fecundity, & egg hatchability, was carried out.