Search results for: crop filling

Authors: Miroslav Dumbrovsky

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The paper deals with positive impacts of land consolidation on decreasing soil degradation with the main emphasis on soil and water conservation in the landscape. The importance of land degradation is very high because of its impact on crop productivity and many other adverse effects. Soil degradation through soil erosion is causing losses in crop productivity and quality of the environment, through decreasing quality of soil and water (especially water resources). Negative effects of conventional farming practices are increased water erosion, as well as crusting and compaction of the topsoil and subsoil. Soil erosion caused by water destructs the soil’s structure, reduces crop productivity due to deterioration in soil physical and chemical properties such as infiltration rate, water holding capacity, loss of nutrients needed for crop production, and loss of soil carbon. Recently, a new process of complex land consolidation in the Czech Republic has provided a unique opportunity for improving the quality of the environment and sustainability of the crop production by means a better soil and water conservation. The present process of the complex land consolidation is not only a reallocation of plots, but this system consists of a new layout of plots within a certain territory, aimed at establishing the integrated land-use economic units, based on the needs of individual landowners and land users. On the other hand, the interests of the general public and the environmental protection have to be solved, too. From the general point of view, a large part of the Czech landscape shall be reconstructed in the course of complex land consolidation projects. These projects will be based on new integrated soil-economic units, spatially arranged in a designed multifunctional system of soil and water conservation measures, such as path network and a territorial system of ecological stability, according to structural changes in agriculture. This new approach will be the basis of a rational economic utilization of the region which will comply with the present ecological and aesthetic demands at present.

Keywords: soil degradation, land consolidation, soil erosion, soil conservation

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Authors: Aziz Larbi, Widad Sadok

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In Morocco, the mountainous regions extend over about 26% of the national territory where 30% of the total population live. They contain opportunities for agriculture, forestry, pastureland and mining. The production systems in these zones are characterised by crop diversification. However, these areas have become vulnerable to the effects of climate change. To understand these effects in relation to the population living in these areas, a study was carried out in the zone of Taliouine, in the Anti-Atlas. The vulnerability of crop productions to climate change was analysed and the different ways of adaptation adopted by farmers were identified. The work was done on saffron, the most profitable crop in the target area even though it requires much water. Our results show that the majority of the farmers surveyed had noticed variations in the climate of the region: irregularity of precipitation leading to a decrease in quantity and an uneven distribution throughout the year; rise in temperature; reduction in the cold period and less snow. These variations had impacts on the cropping system of saffron and its productivity. To cope with these effects, the farmers adopted various strategies: better management and use of water; diversification of agricultural activities; increase in the contribution of non-agricultural activities to their gross income; and seasonal migration.

Keywords: climate change, Taliouine, saffron, perceptions, adaptation strategies

Procedia PDF Downloads 36

Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

Procedia PDF Downloads 48

Authors: Jason West

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Low profitability in agriculture production along with increasing scrutiny over environmental effects is limiting food production at scale. In contrast, the mining sector offers access to resources including energy, water, transport and chemicals for food production at low marginal cost. Scalable agricultural production can benefit from the nexus of resources (water, energy, transport) offered by mining activity in remote locations. A decision support bioeconomic model for controlled environment vertical farms was used. Four submodels were used: crop structure, nutrient requirements, resource-crop integration, and economic. They escalate to a macro mathematical model. A demonstrable dynamic systems framework is needed to prove productive outcomes are feasible. We demonstrate a generalized bioeconomic macro model for controlled environment production systems in minesites using systems dynamics modeling methodology. Despite the complexity of bioeconomic modelling of resource-agricultural dynamic processes and interactions, the economic potential greater than general economic models would assume. Scalability of production as an input becomes a key success feature.

Keywords: crop production systems, mathematical model, mining, agriculture, dynamic systems

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Authors: E. Kharaishvili

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The paper shows the necessity of farm diversification in accordance with the current trends in agricultural sector of Georgia. The possibilities for the diversification and the corresponding economic policy are suggested. The causes that hinder diversification of farms are revealed, possibilities of diversification are suggested and the ability of increasing employment through diversification is proved. Index of harvest diversification is calculated based on the areas used for cereals and legumes, potatoes and vegetables and other food crops. Crop and livestock production indexes are analyzed, correlation between crop capacity index and value-added per one worker and one ha is studied. Based on the research farm diversification strategies and priorities of corresponding economic policy are presented. Based on the conclusions relevant recommendations are suggested.

Keywords: farm diversification, diversification index, agricultural development policy

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Authors: R. Sekula

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Epoxy composites are broadly used as an electrical insulation for the high voltage applications since only such materials can fulfill particular mechanical, thermal, and dielectric requirements. However, properties of the final product are strongly dependent on proper manufacturing process with minimized material failures, as too large shrinkage, voids and cracks. Therefore, application of proper materials (epoxy, hardener, and filler) and process parameters (mold temperature, filling time, filling velocity, initial temperature of internal parts, gelation time), as well as design and geometric parameters are essential features for final quality of the produced components. In this paper, an approach for three-dimensional modeling of all molding stages, namely filling, curing and post-curing is presented. The reactive molding simulation tool is based on a commercial CFD package, and include dedicated models describing viscosity and reaction kinetics that have been successfully implemented to simulate the reactive nature of the system with exothermic effect. Also a dedicated simulation procedure for stress and shrinkage calculations, as well as simulation results are presented in the paper. Second part of the paper is dedicated to recent developments on formulations of functional composites for electrical insulation applications, focusing on thermally conductive materials. Concepts based on filler modifications for epoxy electrical composites have been presented, including the results of the obtained properties. Finally, having in mind tough environmental regulations, in addition to current process and design aspects, an approach for product re-design has been presented focusing on replacement of epoxy material with the thermoplastic one. Such “design-for-recycling” method is one of new directions associated with development of new material and processing concepts of electrical products and brings a lot of additional research challenges. For that, one of the successful products has been presented to illustrate the presented methodology.

Keywords: curing, epoxy insulation, numerical simulations, recycling

Procedia PDF Downloads 253

Authors: Gobena D. Bayisa, A. Mekonen, Megersa O. Dinka, Tilahun H. Nebi, M. Boja

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Crop production in arid and semi-arid regions of Ethiopia is largely limited by water availability. Changing climate conditions and declining water resources increase the need for appropriate approaches to improve water use and find ways to increase production through reduced and more reliable water supply. In the years 2021/22 and 2022/23, a field experiment was conducted to evaluate the effect of limited irrigation water use on bread wheat (Triticum aestivum L.) production, water use efficiency, and financial benefits. Five irrigation treatments, i.e., full irrigation (100% ETc/ control), 85% ETc, 70% ETc, 55% ETc, and 40% ETc, were evaluated using a randomized complete block design (RCBD) with four replicates in the semi-arid climate condition of Awash basin of Ethiopia. Statistical analysis showed a significant effect of irrigation levels on wheat grain yield, water use efficiency, crop water response factor, economic profit, wheat grain quality, aboveground biomass, and yield index. The highest grain yield (5085 kg ha⁻¹) was obtained with 100% ETc irrigation (417.2 mm), and the lowest grain yield with 40% ETc (223.7 mm). Of the treatments, 70% ETc produced the higher wheat grain yield (4555 kg ha⁻¹), the highest water use efficiency (1.42 kg m⁻³), and the highest yield index (0.43). Using the saved water, wheat could be produced 23.4% more with a 70% ETc deficit than full irrigation on 1.38 ha of land, and it could get the highest profit (US$2563.9) and higher MRR (137%). The yield response factor and crop-water production function showed potential reductions associated with increased irrigation deficits. However, a 70% ETc deficit is optimal for increasing wheat grain yield, water use efficiency, and economic benefits of irrigated wheat production. The result indicates that deficit irrigation of wheat under the typical arid and semi-arid climatic conditions of the Awash Basin can be a viable irrigation management approach for enhancing water use efficiency while minimizing the decrease in crop yield could be considered effective.

Keywords: crop-water response factor, deficit irrigation, water use efficiency, wheat production

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Authors: Vijay Shankar

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In the era of water scarcity, effective use of water via irrigation requires good methods for determining crop water needs. Implementation of irrigation scheduling programs requires an accurate estimate of water use by the crop. Moisture depletion from the root zone represents the consequent crop evapotranspiration (ET). A numerical model for simulating soil water depletion in the root zone has been developed by taking into consideration soil physical properties, crop and climatic parameters. The governing differential equation for unsaturated flow of water in the soil is solved numerically using the fully implicit finite difference technique. The water uptake by plants is simulated by using three different sink functions. The non-linear model predictions are in good agreement with field data and thus it is possible to schedule irrigations more effectively. The present paper describes irrigation scheduling based on moisture depletion from the different layers of the root zone, obtained using different sink functions for three cash, oil and forage crops: cotton, safflower and barley, respectively. The soil is considered at a moisture level equal to field capacity prior to planting. Two soil moisture regimes are then imposed for irrigated treatment, one wherein irrigation is applied whenever soil moisture content is reduced to 50% of available soil water; and other wherein irrigation is applied whenever soil moisture content is reduced to 75% of available soil water. For both the soil moisture regimes it has been found that the model incorporating a non-linear sink function which provides best agreement of computed root zone moisture depletion with field data, is most effective in scheduling irrigations. Simulation runs with this moisture uptake function result in saving 27.3 to 45.5% & 18.7 to 37.5%, 12.5 to 25% % &16.7 to 33.3% and 16.7 to 33.3% & 20 to 40% irrigation water for cotton, safflower and barley respectively, under 50 & 75% moisture depletion regimes over other moisture uptake functions considered in the study. Simulation developed can be used for an optimized irrigation planning for different crops, choosing a suitable soil moisture regime depending upon the irrigation water availability and crop requirements.

Keywords: irrigation water, evapotranspiration, root uptake models, water scarcity

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Authors: Iyabode A. Kehinde, Joshua O. Oyekanmi, Jumoke T. Abimbola, Olajumoke E. Ayanda

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African yam bean (AYB), (Sphenostylis stenocarpa) is a leguminous crop that provides nutritionally rich seeds, tubers and leaves for human consumption. AYB potentials as an important food security crop is yet to be realized and thus classified as underutilized crop. Underutilization of the crop has been partly associated with scarce information on the incidence and characterization of fungal endophytes infecting vascular parts of AYB. Accurate and robust detection of these endophytic fungi is essential for diagnosis, modeling, surveillance and protection of germplasm (seed) health. This work aimed at isolating and identifying fungal endophytes associated with leaves, stems and roots of AYB in Ogun State, Nigeria. This study investigated both cultural and molecular properties of endophytic fungi in AYB for its characterization and diversity. Fungal endophytes were isolated and culturally identified. DNA extraction, PCR amplification using ITS primers and analyses of nucleotide sequences of ribosomal DNA fragments were conducted on selected isolates. BLAST analysis was conducted on consensus nucleotide sequences of 28 out of 30 isolates and results showed similar homology with genera of Rhizopus, Cunninghamella, Fusarium, Aspergillus, Penicillium, Alternaria, Diaporthe, Nigrospora, Purpureocillium, Corynespora, Magnaporthe, Macrophomina, Curvularia, Acrocalymma, Talaromyces and Simplicillium. Slight similarity was found with endophytes associated with soybean. Phylogenetic analysis by maximum likelihood method showed high diversity among the general. These organisms have high economic importance in crop improvement. For an instance, Purpureocillium lilacinum showed high potential in control of root rot caused by nematodes in tomatoes. Though some can be pathogens, but many of the fungal endophytes have beneficial attributes to plant in host health, uptake of nutrients, disease suppression, and host immunity.

Keywords: molecular characterization, African Yam Bean, fungal endophyte, plant parts

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Authors: R. S. Giraddi, C. M. Poleshi

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Organic cultivation of crops is gaining importance consumer awareness towards pesticide residue free foodstuffs is increasing globally. This is also because of high costs of synthetic fertilizers and pesticides, making the conventional farming non-remunerative. In India, organic manures (such as vermicompost) are an important input in organic agriculture.  Though vermicompost obtained through earthworm and microbe-mediated processes is known to comprise most of the crop nutrients, but they are in small amounts thus necessitating enrichment of nutrients so that crop nourishment is complete. Another characteristic of organic manures is that the pest infestations are kept under check due to induced resistance put up by the crop plants. In the present investigation, deoiled neem cake containing azadirachtin, copper ore tailings (COT), a source of micro-nutrients and microbial consortia were added for enrichment of vermicompost. Neem cake is a by-product obtained during the process of oil extraction from neem plant seeds. Three enriched vermicompost blends were prepared using vermicompost (at 70, 65 and 60%), deoiled neem cake (25, 30 and 35%), microbial consortia and COTwastes (5%). Enriched vermicompost was thoroughly mixed, moistened (25+5%), packed and incubated for 15 days at room temperature. In the crop response studies, the field trials on chili (Capsicum annum var. longum) and soybean, (Glycine max cv JS 335) were conducted during Kharif 2015 at the Main Agricultural Research Station, UAS, Dharwad-Karnataka, India. The vermicompost blend enriched with neem cake (known to possess higher amounts of nutrients) and vermicompost were applied to the crops and at two dosages and at two intervals of crop cycle (at sowing and 30 days after sowing) as per the treatment plan along with 50% recommended dose of fertilizer (RDF). 10 plants selected randomly in each plot were studied for pest density and plant damage. At maturity, crops were harvested, and the yields were recorded as per the treatments, and the data were analyzed using appropriate statistical tools and procedures. In the crops, chili and soybean, crop nourishment with neem enriched vermicompost reduced insect density and plant damage significantly compared to other treatments. These treatments registered as much yield (16.7 to 19.9 q/ha) as that realized in conventional chemical control (18.2 q/ha) in soybean, while 72 to 77 q/ha of green chili was harvested in the same treatments, being comparable to the chemical control (74 q/ha). The yield superiority of the treatments was of the order neem enriched vermicompost>conventional chemical control>neem cake>vermicompost>untreated control.  The significant features of the result are that it reduces use of inorganic manures by 50% and synthetic chemical insecticides by 100%.

Keywords: humic acid, azadirachtin, vermicompost, insect-pest

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Authors: A. H. Nanher, N. P. Singh, Shashidhar Yadav, Sachin Tyagi

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Agricultural production system is an outcome of a complex interaction of seed, soil, water and agro-chemicals (including fertilizers). Therefore, judicious management of all the inputs is essential for the sustainability of such a complex system. Precision agriculture gives farmers the ability to use crop inputs more effectively including fertilizers, pesticides, tillage and irrigation water. More effective use of inputs means greater crop yield and/or quality, without polluting the environment the focus on enhancing the productivity during the Green Revolution coupled with total disregard of proper management of inputs and without considering the ecological impacts, has resulted into environmental degradation. To evaluate a new approach for site-specific nutrient management (SSNM). Large variation in initial soil fertility characteristics and indigenous supply of N, P, and K was observed among Field- and season-specific NPK applications were calculated by accounting for the indigenous nutrient supply, yield targets, and nutrient demand as a function of the interactions between N, P, and K. Nitrogen applications were fine-tuned based on season-specific rules and field-specific monitoring of crop N status. The performance of SSNM did not differ significantly between high-yielding and low-yielding climatic seasons, but improved over time with larger benefits observed in the second year Future, strategies for nutrient management in intensive rice systems must become more site-specific and dynamic to manage spatially and temporally variable resources based on a quantitative understanding of the congruence between nutrient supply and crop demand. The SSNM concept has demonstrated promising agronomic and economic potential. It can be used for managing plant nutrients at any scale, i.e., ranging from a general recommendation for homogenous management of a larger domain to true management of between-field variability. Assessment of pest profiles in FFP and SSNM plots suggests that SSNM may also reduce pest incidence, particularly diseases that are often associated with excessive N use or unbalanced plant nutrition.

Keywords: nutrient, pesticide, crop, yield

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Authors: Luís Fernando Cusioli, Leticia Nishi, Lucas Bairros, Gabriel Xavier Jorge, Sandro Rogério Lautenschalager, Celso Varutu Nakamura, Rosângela Bergamasco

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Focusing on the elimination of nitrogen and phosphorus from sewage, the study proposes to face the challenges of eutrophication and to optimize the effectiveness of sewage treatment through biofilms and filling produced by a 3D printer, seeking to identify the most effective Polylactic Acid (PLA), Acrylonitrile Butadiene Styrene (ABS). The study also proposes to evaluate the nitrification process in a Submerged Aerated Biological Filter (FBAS) on a pilot plant scale, quantifying the removal of nitrogen and phosphorus. The experiment will consist of two distinct phases, namely, a bench stage and the implementation of a pilot plant. During the bench stage, samples will be collected at five points to characterize the microbiota. Samples will be collected, and the microbiota will be investigated using Fluorescence In Situ Hybridization (FISH), deepening the understanding of the performance of biofilms in the face of multiple variables. In this context, the study contributes to the search for effective solutions to mitigate eutrophication and, thus, strengthen initiatives to improve effluent treatment.

Keywords: eutrophication, sewage treatment, biofilms, nitrogen and phosphorus removal, 3d printer, environmental efficiency

Procedia PDF Downloads 52

Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: Rudolf Hrach, Stanislav Novak, Vera Hrachova

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Composite and nanocomposite films represent the class of promising materials and are often objects of the study due to their mechanical, electrical and other properties. The most interesting ones are probably the composite metal/dielectric structures consisting of a metal component embedded in an oxide or polymer matrix. Behaviour of composite films varies with the amount of the metal component inside what is called filling factor. The structures contain individual metal particles or nanoparticles completely insulated by the dielectric matrix for small filling factors and the films have more or less dielectric properties. The conductivity of the films increases with increasing filling factor and finally a transition into metallic state occurs. The behaviour of composite films near a percolation threshold, where the change of charge transport mechanism from a thermally-activated tunnelling between individual metal objects to an ohmic conductivity is observed, is especially important. Physical properties of composite films are given not only by the concentration of metal component but also by the spatial and size distributions of metal objects which are influenced by a technology used. In our contribution, a study of composite structures with the help of methods of computational physics was performed. The study consists of two parts: -Generation of simulated composite and nanocomposite films. The techniques based on hard-sphere or soft-sphere models as well as on atomic modelling are used here. Characterizations of prepared composite structures by image analysis of their sections or projections follow then. However, the analysis of various morphological methods must be performed as the standard algorithms based on the theory of mathematical morphology lose their sensitivity when applied to composite films. -The charge transport in the composites was studied by the kinetic Monte Carlo method as there is a close connection between structural and electric properties of composite and nanocomposite films. It was found that near the percolation threshold the paths of tunnel current forms so-called fuzzy clusters. The main aim of the present study was to establish the correlation between morphological properties of composites/nanocomposites and structures of conducting paths in them in the dependence on the technology of composite films.

Keywords: composite films, computer modelling, image analysis, nanocomposite films

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Authors: Nour Elhouda Abed, Bedj Mimi, Wahid Slimani, Mourad Atif, Abdelhakim Ouzzane, Hocine Irekti, Abdelkader Bekki

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The most frequent system of cereal production in Algeria is fallow-wheat. This is an extensive system that meets only the half needs some cereals and fodder demand. Resorption of fallow has become a strategic necessity to ensure food security in response to the instability of supply and the persistence of higher food prices on the world market. Despite several attempts to replace the fallow by crop cultures, choosing the best crop remains. Today, the agronomic and economic interests of legumes are demonstrated. However, their crop culture remains marginalized because of the weakness and instability of their performance. In the context of improving legumes and cereals crops as well as fallow resorption, we undertook to test, in the field, the effect of rhizobial inoculation of Phaseolus vulgaris in association with Zea Mays. We firstly studied the genetic diversity of rhizobial strains that nodulate P.vulgaris isolated from fifteen (15) different regions. ARDRA had shown 18 different genetic profiles. Symbiotic characterization highlighted a strain that highly significantly improved the fresh and dry weight of the host plant, in comparison to the negative control (un-inoculated) and the positive control (inoculated with the reference strain CIAT 899). In the field, the selected strain increased significantly the growth and yield of P.vulgaris and Zea Mays comparing to the non-inoculated control. However, the mix inoculation (selected strain+ Ciat 899) had not given the best parameters showing, thus, no synergy between the strains. These results indicate the replacing fallow by a crop legume in intercropping with cereals crops.

Keywords: fallow, intercropping, inoculation, legumes-cereals

Procedia PDF Downloads 339

Authors: Mahmood Iqbal, Khalid Nawab, Tachibana Satoshi

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Farmer Field School (FFS) is constantly aims to assist farmers to determine and learn about field ecology and integrated crop management. The study was conducted to examine the change in productivity of tomato crop in the study area; to determine increase in per acre yield of the crop, and find out reduction in per acre input cost. A study of tomato crop was conducted in ten villages namely Jabban, Bijligar Colony, Palonow, Heroshah, Zara Maira, Deghar Ghar, Sidra Jour, Anar Thangi, Miangano Korona and Wartair of district Malakand. From each village 15 respondents were selected randomly on the basis of identical allocation making sample size of 150 respondents. The research was based on primary as well as secondary data. Primary data was collected from farmers while secondary data were taken from Agriculture Extension Department Dargai, District Malakand. Interview schedule was planned and each farmer was interviewed personally. The study was based on comparison of cost, yield and income of tomato before and after FFS. Paired t-test and Statistical Package for Social Sciences (SPSS) was used for analysis; outcome of the study show that integrated pest management project has brought a positive change in the attitude of farmers of the project area through FFS approach. In district Malakand 66.0% of the respondents were between the age group of 31-50 years, 11.3% of respondents had primary level of education, 12.7% of middle level, 28.7% metric level, 3.3% of intermediate level and 2.0% of graduate level of education while 42.0% of respondents were illiterate and have no education. Average land holding size of farmers was 6.47 acres, cost of seed, crop protection from insect pest and crop protection from diseases was reduced by Rs. 210.67, Rs. 2584.43 and Rs. 3044.16 respectively, the cost of fertilizers and cost of farm yard manure was increased by Rs.1548.87 and Rs. 1151.40 respectively while tomato yield was increased by 1585.03 kg/acre from 7663.87 to 9248.90 kg/acre. The role of FFS initiate by integrated pest management project through department of agriculture extension for the development of agriculture was worth mentioning. It has brought enhancement in crop yield of tomato and their income through FFS approach. On the basis of results of the research studies, integrated pest management project should spread their developmental activities for maximum participation of the complete rural masses through participatory FFS approach.

Keywords: agriculture, Farmers field schools, extension education, tomato

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Authors: Li Guoyou, Zhang Tao, Ji Wenzhan, Huo Liang, Lin Xiqiang, Zhang Nan

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The three dimensional (3D) printing technology has undergone rapid development in the last few years and it is possible to print engineering structures. 3D printing buildings use wastes from constructions, industries and mine tailings as “ink”, and mix it with property improved materials, such as cement, fiber etc. This paper presents a study of the Thermodynamic performance of 3D printed walls using cement and steel slag powder. Analyses the thermal simulation regarding 3D printed walls and solid brick wall by the way of the hot-box methods and the infrared technology, and the results were contrasted with theoretical calculation. The results show that the excellent thermodynamic performance of 3D printed concrete wall made it suitable as the partial materials for self-thermal insulation walls in residential buildings. The thermodynamic performance of 3D printed concrete walls depended on the density of materials, distribution of holes, and the filling materials. Decreasing the density of materials, increasing the number of holes or replacing the filling materials with foamed concrete could improve its thermodynamic performance significantly. The average of heat transfer coefficient and thermal inertia index of 3D printed steel slag powder concrete wall all better than the traditional solid brick wall with a thickness of 240mm.

Keywords: concrete, 3D printed walls, thermodynamic performance, steel slag powder

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Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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Authors: Joanna Rybicka-Łada, Magda Kosmal, Anna Kuśnierz

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One of the main problems of the glass industry is the still high consumption of energy needed to produce glass mass, as well as the increase in prices, fuels, and raw materials. Therefore, comprehensive actions are taken to improve the entire production process. The key element of these activities, starting from filling the set to receiving the finished product, is the melting process, whose task is, among others, dissolving the components of the set, removing bubbles from the resulting melt, and obtaining a chemically homogeneous glass melt. This solution avoids dust formation during filling and is available on the market. This process consumes over 90% of the total energy needed in the production process. The processes occurring in the set during its conversion have a significant impact on the further stages and speed of the melting process and, thus, on its overall effectiveness. The speed of the reactions occurring and their course depend on the chemical nature of the raw materials, the degree of their fragmentation, thermal treatment as well as the form of the introduced set. An opportunity to minimize segregation and accelerate the conversion of glass sets may be the development of new technologies for preparing and dosing sets. The previously preferred traditional method of melting the set, based on mixing all glass raw materials together in loose form, can be replaced with a set in a thickened form. The aim of the project was to develop a glass set in a selectively or completely densified form and to examine the influence of set processing on the melting process and the properties of the glass.

Keywords: glass, melting process, glass set, raw materials

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Sanari Chalin Moriri, Kwabena Kingsley Ayisi, Alina Mofokeng

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Dryland smallholder farmers in South Africa are vulnerable to all kinds of risks, and it negatively affects crop productivity and profit. Pigeonpea is a leguminous and multipurpose crop that provides food, fodder, and wood for smallholder farmers. The majority of these farmers are still growing pigeonpea from traditional unimproved seeds, which comprise a mixture of genotypes. The objectives of the study were to identify the key risk factors that affect pigeonpea productivity and to develop management strategies on how to alleviate the risk factors in pigeonpea production. The study was conducted in two provinces (Limpopo and Mpumalanga) of South Africa in six municipalities during the 2020/2021 growing seasons. The non-probability sampling method using purposive and snowball sampling techniques were used to collect data from the farmers through a structured questionnaire. A total of 114 pigeonpea producers were interviewed individually using a questionnaire. Key stakeholders in each municipality were also identified, invited, and interviewed to verify the information given by farmers. Data collected were subjected to SPSS statistical software 25 version. The findings of the study were that majority of farmers affected by risk factors were women, subsistence, and old farmers resulted in low food production. Drought, unavailability of improved pigeonpea seeds for planting, access to information, and processing equipment were found to be the main risk factors contributing to low crop productivity in farmer’s fields. Above 80% of farmers lack knowledge on the improvement of the crop and also on the processing techniques to secure high prices during the crop off-season. Market availability, pricing, and incidence of pests and diseases were found to be minor risk factors which were triggered by the major risk factors. The minor risk factors can be corrected only if the major risk factors are first given the necessary attention. About 10% of the farmers found to use the crop as a mulch to reduce soil temperatures and to improve soil fertility. The study revealed that most of the farmers were unaware of its utilisation as fodder, much, medicinal, nitrogen fixation, and many more. The risk of frequent drought in dry areas of South Africa where farmers solely depend on rainfall poses a serious threat to crop productivity. The majority of these risk factors are caused by climate change due to unrealistic, low rainfall with extreme temperatures poses a threat to food security, water, and the environment. The use of drought-tolerant, multipurpose legume crops such as pigeonpea, access to new information, provision of processing equipment, and support from all stakeholders will help in addressing food security for smallholder farmers. Policies should be revisited to address the prevailing risk factors faced by farmers and involve them in addressing the risk factors. Awareness should be prioritized in promoting the crop to improve its production and commercialization in the dryland farming system of South Africa.

Keywords: management strategies, pigeonpea, risk factors, smallholder farmers

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

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Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

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Authors: Ezzat Abd El Lateef

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Agroforestry means combining the management of trees with productive agricultural activities, especially in semiarid regions where crop yield increases are limited in agroforestry systems due to the fertility and microclimate improvements and the large competitive effect of trees with crops for water and nutrients, in order to assess the effect of agroforestry of some field crops with citrus trees as an approach to establish biodiversity in fruit tree plantations. Three field crops, i.e., maize, soybean and sunflower, were inter-planted with seedless orange trees (4*4 m) or were planted as solid plantings. The results for the trees indicated a larger fruit yield was obtained when soybean and sunflowers were interplant with citrus. Statistically significant effects (P<0.05) were found for maize grain and biological yields, with increased yields when grown as solid planting. There were no differences in the yields of soya bean and sunflower, where the yields were very similar between the two cropping systems. It is evident from the trials that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Maize, unlike the other crops, was more sensitive to shade conditions under agroforestry practice and not preferred in the biodiversity system. The potential of agroforestry to improve or increase biodiversity is efficient as the understorey crops are usually C4 species, and the overstorey trees are invariably C3 species in agroforestry. Improvement in interplant species is most likely if the understorey crop is a C3 species, which are usually light saturated in the open, and partial shade may have little effect on assimilation or by a concurrent reduction in transpiration. It could be concluded that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Some field crops could be employed successfully, like soybean or sunflowers, while others like maize are sensitive to incorporate in agroforestry system.

Keywords: agroforestry, field crops, C3 and C4 plants, yield

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Authors: S. Boonlertnirun, R. Suvannasara, K. Boonlertnirun

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Hypoxia has negative effects on growth and crop yield, its severity is so varied depending on crop growth stages, duration of hypoxia and crop species. The objective was to evaluate the sensitive growth stage and the duration of hypoxia negatively affecting growth and yield of waxy corn. Pot experiment was conducted using a split plot in randomized complete block with 3 growth stages: V3 (3-4 true leaves), V7 (7-8 true leaves), and R1 (silking stage), and three hypoxic durations: 6, 9, and 12 days, in an open–ended outdoor greenhouse during January to March 2013. The results revealed that different growth stages had significantly (p < 0.5) different responses to hypoxia, seeing that the sensitive growth stage affecting plant height, yield and yield components was mostly detected in V7 growth stage whereas leaf greenness and days to silking were sensitive to hypoxia at R1 growth stage. Different hypoxic durations significantly affected the yield and yield components, hypoxic duration of twelve days showed the most negative effect greater than the others. In this present study, it can be concluded that waxy corn plants were waterlogged at V7 growth stage for twelve days had the most negative effect on yield and yield components.

Keywords: hypoxia duration, waxy corn, growth stage, Zea mays L.

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Authors: Shirin Ghatrehsamani

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Higher efficiency and lower environmental impact are the consequence of using advanced technology in farming. They also help to decrease yield variability by diminishing weather variability impact, optimizing nutrient and pest management as well as reducing competition from weeds. A better understanding of the pros and cons of applying technology and finding the main reason for preventing the utilization of the technology has a significant impact on developing technology adoption among farmers and producers in the digital agriculture era. The results from two surveys carried out in 2019 and 2021 were used to investigate whether the crop types had an impact on the willingness to utilize technology on the farms. The main focus of the questionnaire was on utilizing precision agriculture (PA) technologies among farmers in some parts of the united states. Collected data was analyzed to determine the practical application of various technologies. The survey results showed more similarities in the main reason not to use PA between the two crop types, but the present application of using technology in specialty crops is generally five times larger than in row crops. GPS receiver applications were reported similar for both types of crops. Lack of knowledge and high cost of data handling were cited as the main problems. The most significant difference was among using variable rate technology, which was 43% for specialty crops while was reported 0% for row crops. Pest scouting and mapping were commonly used for specialty crops, while they were rarely applied for row crops. Survey respondents found yield mapping, soil sampling map, and irrigation scheduling were more valuable for specialty crops than row crops in management decisions. About 50% of the respondents would like to share the PA data in both types of crops. Almost 50 % of respondents got their PA information from retailers in both categories, and as the second source, using extension agents were more common in specialty crops than row crops.

Keywords: precision agriculture, smart farming, digital agriculture, technology adoption

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Authors: Anis Eloud, Ben Salah Nahla, Sayed Chehaibi

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In order to improve and develop the Tunisian agriculture, the government has encouraged the introduction of modern technologies and has also promoted the adoption of innovative practices cultures. Indeed, the extensive use of mechanization can increase crop productivity but its inadequate application also has a negative impact on the ground caused by the phenomenon of compaction. Which will cause the loss of soil fertility and increased production costs. This problem is accentuated with increase the stress on contact wheel / ground. For this reason, the objective of this study is to simulate the footprint of the ground contact / tire two types of tractor after their passage. The method of this work is based on a simulation including passages from two different tractors on soil with similar characteristics. Simulation parameters were based on the choice of two tractors masses of 6500 kg and 4400 kg of soil and sandy loam in nature. The analysis was performed using specific software. The main results showed that the heaviest tractor caused a constraint wheel / rear floor exceeding 100 kPa. For cons, the second tractor has caused stress wheel / rear floor of 50 kPa. The comparison of the two results showed that 6500 kg tractor made a serious and excessive compaction which generated a negative impact on soil quality and crop yields.

Keywords: compaction, soil, resistance to penetration, crop yields

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Authors: Alefsi D. Sanchez-Reinoso, Leonardo Lombardini, Hermann Restrepo

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Colombian coffee is recognized worldwide for its mild flavor and aroma. Its cultivation generates a large amount of waste, such as fresh pulp, which leads to environmental, health, and economic problems. Obtaining biochar (BC) by pyrolysis of coffee pulp and its incorporation to the soil can be a complement to the crop mineral nutrition. The objective was to evaluate the effect of the application of BC obtained from coffee pulp on the physiology and agronomic performance of the Castillo variety coffee crop (Coffea arabica L.). The research was developed in field condition experiment, using a three-year-old commercial coffee crop, carried out in Tolima. Four doses of BC (0, 4, 8 and 16 t ha-1) and four levels of chemical fertilization (CF) (0%, 33%, 66% and 100% of the nutritional requirements) were evaluated. Three groups of variables were recorded during the experiment: i) physiological parameters such as Gas exchange, the maximum quantum yield of PSII (Fv/Fm), biomass, and water status were measured; ii) physical and chemical characteristics of the soil in a commercial coffee crop, and iii) physiochemical and sensorial parameters of roasted beans and coffee beverages. The results indicated that a positive effect was found in plants with 8 t ha-1 BC and fertilization levels of 66 and 100%. Also, a positive effect was observed in coffee trees treated with 8 t ha-1 BC and 100%. In addition, the application of 16 t ha-1 BC increased the soil pHand microbial respiration; reduced the apparent density and state of aggregation of the soil compared to 0 t ha-1 BC. Applications of 8 and 16 t ha-1 BC and 66%-100% chemical fertilization registered greater sensitivity to the aromatic compounds of roasted coffee beans in the electronic nose. Amendments of BC between 8 and 16 t ha-1 and CF between 66% and 100% increased the content of total soluble solids (TSS), reduced the pH, and increased the titratable acidity in beverages of roasted coffee beans. In conclusion, 8 t ha-1 BC of the coffee pulp can be an alternative to supplement the nutrition of coffee seedlings and trees. Applications between 8 and 16 t ha-1 BC support coffee soil management strategies and help the use of solid waste. BC as a complement to chemical fertilization showed a positive effect on the aromatic profile obtained for roasted coffee beans and cup quality attributes.

Keywords: crop yield, cup quality, mineral nutrition, pyrolysis, soil amendment

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Authors: Ákos Tótin

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In crop production the most modern hybrids are available for us, therefore the yield and yield stability is determined by the agro-technology. The purpose of the experiment is to adapt the modern agrotechnology to the new type of hybrids. The long-term experiment was set up in 2015-2016 on chernozem soil in the Hajdúság (eastern Hungary). The plots were set up in 75 thousand ha-1 plant density. We examined some mainly use hybrids of Hungary. The conducted studies are: germination dynamic, growing dynamic and the effect of annual weather for the yield. We use three different sowing date as early, average and late, and measure how many plant germinated during the germination process. In the experiment, we observed the germination dynamics in 6 hybrid in 4 replication. In each replication, we counted the germinated plants in 2m long 2 row wide area. Data will be shown in the average of the 6 hybrid and 4 replication. Growing dynamics were measured from the 10cm (4-6 leaf) plant highness. We measured 10 plants’ height in two weeks replication. The yield was measured buy a special plot harvester - the Sampo Rosenlew 2010 – what measured the weight of the harvested plot and also took a sample from it. We determined the water content of the samples for the water release dynamics. After it, we calculated the yield (t/ha) of each plot at 14% of moisture content to compare them. We evaluated the data using Microsoft Excel 2015. The annual weather in each crop year define the maize germination dynamics because the amount of heat is determinative for the plants. In cooler crop year the weather is prolonged the germination. At the 2015 crop year the weather was cold in the beginning what prolonged the first sowing germination. But the second and third sowing germinated faster. In the 2016 crop year the weather was much favorable for plants so the first sowing germinated faster than in the previous year. After it the weather cooled down, therefore the second and third sowing germinated slower than the last year. The statistical data analysis program determined that there is a significant difference between the early and late sowing date growing dynamics. In 2015 the first sowing date had the highest amount of yield. The second biggest yield was in the average sowing time. The late sowing date has lowest amount of yield.

Keywords: germination, maize, sowing date, yield

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Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

Procedia PDF Downloads 39