Search results for: subtropical agriculture

Authors: Samson Olusegun Apantaku, Adetayo K. Aromolaran, Giyatt Hammed

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The study assessed the use of participatory research methods among Federal University of Agriculture Abeokuta, Nigeria (FUNAAB) researchers. Simple random sampling technique was used to select one hundred and twenty respondents from the study area. Data were collected using a questionnaire. Data collected were subjected to descriptive and inferential statistical analyses. Results showed that 75.8% of the respondents were males while only 21.3% were female. The mean age of the respondents was 38.8 years and most (77.5%) of them were married. 15% of the respondents were in professorial cadre, 21.7% and 20% of the respondents were senior lecturers/fellow and lecturer/research fellow I&II respectively. The results further revealed that 93.3% of the respondents were aware of participatory research methods and 82.5% of the respondents have utilized it before. The average period of usage was 2.7 years and participation by consultation (86.7%) and interactive participation (76.7%) were mostly used. Most (94.2%) indicated that fund was the major hindrance to the use of participatory research methods. The result of correlation analysis showed that there was significant relationship between the years of research experience, designation post (status) of the respondents and usage of participatory research methods (r = 0.034, 0.031, p < 0.05). The study concluded that most of the researchers were aware of and used participatory research methods, which could influence the quality of their research or make it acceptable to the end users. It was recommended that more funds should be made available and accessible for participatory research. All researchers should be trained and encouraged to make use of participatory research methods in their research activities so as to achieve effective research and capacity building that could enhance adoption of technologies and increase agricultural production in the country. Farmers’ capacity to participate in agricultural research should also be enhanced.

Keywords: participatory research, participatory research methods, awareness, utilization

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Authors: Kriti Jain, Sucha Singh Gill

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Subsidies have been a major part of agricultural policies around the world, and more extensively since the green revolution in developing countries, for the sake of attaining higher agricultural productivity and achieving food security. But entrenched subsidies lead to distorted incentives and promote inefficiencies in the agricultural sector, threatening the viability of these very subsidies and sustainability of the agricultural production systems, posing a threat to the livelihood of farmers and laborers dependent on it. This paper analyzes the economic and ecological sustainability implications of prolonged input and output subsidies in agriculture by studying the case of Indian Punjab, an agriculturally developed state responsible for ensuring food security in the country when it was facing a major food crisis. The paper focuses specifically on the environmentally unsustainable cropping pattern changes as a result of Minimum Support Price (MSP) and assured procurement and on the resource use efficiency and cost implications of power subsidy for irrigation in Punjab. The study is based on an analysis of both secondary and primary data sources. Using secondary data, a time series analysis was done to capture the changes in Punjab’s cropping pattern, water table depth, fertilizer consumption, and electrification of agriculture. This has been done to examine the role of price and output support adopted to encourage the adoption of green revolution technology in changing the cropping structure of the state, resulting in increased input use intensities (especially groundwater and fertilizers), which harms the ecological balance and decreases factor productivity. Evaluation of electrification of Punjab agriculture helped evaluate the trend in electricity productivity of agriculture and how free power imposed further pressure on the extant agricultural ecosystem. Using data collected from a primary survey of 320 farmers in Punjab, the extent of wasteful application of groundwater irrigation, water productivity of output, electricity usage, and cost of irrigation driven electricity subsidy to the exchequer were estimated for the dominant cropping pattern amongst farmers. The main findings of the study revealed how because of a subsidy has driven agricultural framework, Punjab has lost area under agro climatically suitable and staple crops and moved towards a paddy-wheat cropping system, that is gnawing away the state’s natural resources like water table has been declining at a significant rate of 25 cms per year since 1975-76, and excessive and imbalanced fertilizer usage has led to declining soil fertility in the state. With electricity-driven tubewells as the major source of irrigation within a regime of free electricity and water-intensive crop cultivation, there is both wasteful application of irrigation water and electricity in the cultivation of paddy crops, burning an unproductive hole in the exchequer’s pocket. There is limited access to both agricultural extension services and water-conserving technology, along with policy imbalance, keeping farmers in an intensive and unsustainable production system. Punjab agriculture is witnessing diminishing returns to factor, which under the business-as-usual scenario, will soon enter the phase of negative returns to factor.

Keywords: cropping pattern, electrification, subsidy, sustainability

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Authors: M. Kamal Uddin, H. Mohd Dandan, Ame H. Alidin

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Germination and seedling growth of plant species are reduced in saline due to an external osmotic potential. An experiment was conducted at the laboratory, Faculty of Sustainable Agriculture, Universiti Malaysia Sabah, to compare the salt effect on seed germination and growth of weedy rice and cultivated rice. Seeds (10 in each) were placed in petri dishes. Five salinity levels 0 (distilled water), 4, 8, 12 and 16 dSm-1 (NaCl) were applied. The number of germinated seeds was recorded daily. The final germination percentage, germination index (GI), seedling vigour index (SVI) mean germination time (MGT), shoot and root dry weight were estimated. At highest salinity (16 dSm-1) germination percentage was higher (100%) in weedy rice awn and weedy rice compact. Lowest germination percentage was in MR219 and TQR-8 (50-60%). Mean germination time (MGT) was found higher in all weedy rice biotypes compared to cultivated rice. At highest salinity (16dSm-1) weedy rice open produced the highest MGT (9.92) followed by weedy rice compact (9.73) while lowest MGT was in MR219 (9.48). At highest salinity (16dSm-1) germination index was higher in weedy rice awn (11.71) and compact type (9.62). Lowest germination index was in MR219 (5.90) and TQR-8 (8.94). At the highest salinity (16 dSm−1), seedling vigor index was highest in weedy rice awn (6.06) followed by weedy rice compact (5.26); while lowest was in MR219 (2.11) followed by MR269 (3.82).On the basis of Germination index, seedling vigor index and growth related results it could be concluded that weedy rice awn, compact and open biotypes were more salt tolerant compared to other cultivated rice MR219, MR269, and TQR-8.

Keywords: germination, salinity, rice and weedy rice, sustainable agriculture

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

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Authors: V. P. Ramani, K. P. Patel, S. B. Patel

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It is necessary to dispose of generated industrial wastes in the proper way to overcome the further pollution for a safe environment. Waste can be used in agriculture for good quality higher food production. In order to evaluate the effect and rate of processed industrial biomass on yield, contents, uptake and soil status in maize, a field experiment was conducted during 2009 - 2011 at Anand on loamy sand soil for two years. The treatments of different levels of NPK i.e. 100% RD, 75% RD and 50% RD were kept to study the possibility of reduction in fertilizer application with the use of processed biomass (BM) in different proportion with FYM. (Where, RD= Recommended dose, FYM= Farm Yard Manure, BM= Processed Biomass.) The significantly highest grain yield of maize was recorded under the treatment of 75% NPK + BM application @ 10t ha-1. The higher (10t ha-1) and lower (5t ha-1) application rate of BM with full dose of NPK was found beneficial being at par with the treatment 75% NPK along with BM application @ 10t ha-1. There is saving of 25% recommended dose of NPK when combined with BM application @ 10.0t ha-1 or 50% saving of organics when applied with full dose (100%) of NPK. The highest straw yield (7734 kg ha-1) of maize on pooled basis was observed under the treatment of recommended dose of NPK along with FYM application at 7.5t ha-1 coupled with BM application at 2.5t ha-1. It was also observed that highest straw yield was at par under all the treatments except control and application of 100% recommended dose of NPK coupled with BM application at 7.5t ha-1. The Fe content of maize straw were found altered significantly due to different treatments on pooled basis and it was noticed that biomass application at 7.5t ha-1 along with recommended dose of NPK showed significant enhancement in Fe content of straw over other treatments. Among heavy metals, Co, Pb and Cr contents of grain were found significantly altered due to application of different treatments variably during the pooled. While, Ni content of maize grain was not altered significantly due to application of different organics. However, at higher rate of BM application i.e. of 10t ha-1, there was slight increase in heavy metal content of grain/ straw as well as DTPA heavy metals in soil; although the increase was not alarming Thus, the overall results indicated that the application of BM at 5t ha-1 along with full dose of NPK is beneficial to get higher yield of maize without affecting soil / plant health adversely. It also indicated that the 5t BM ha-1 could be utilized in place of 10t FYM ha-1 where FYM availability is scarce. The 10t BM ha-1 helps to reduce a load of chemical fertilizer up to 25 percent in agriculture. The lower use of agro-chemicals always favors safe environment. However, the continuous use of biomass needs periodical monitoring to check any buildup of heavy metals in soil/ plant over the years.

Keywords: alternate use of industrial waste, heavy metals, maize, processed industrial biomass

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Authors: MD Mashiur Rahman, Muhammad Arshadul Haque

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Emerging conservation agriculture (CA) is an option for improving soil health and maintaining environmental sustainability for intensive agriculture, especially in the tropical climate. Three years lengthy research experiment was performed in arid climate from 2018 to 2020 at research field of Bangladesh Agricultural Research Station (RARS)F, Jamalpur (soil texture belongs to Agro-Ecological Zone (AEZ)-8/9, 24˚56'11''N latitude and 89˚55'54''E longitude and an altitude of 16.46m) to evaluate the effect of CA approaches on energy use efficiency and a streamlined life cycle greenhouse gas (GHG) emission of wheat production. For this, the conservation tillage practices (strip tillage (ST) and minimum tillage (MT)) were adopted in comparison to the conventional farmers' tillage (CT), with retained a fixed level (30 cm) of residue retention. This study examined the relationship between energy consumption and life cycle greenhouse gas (GHG) emission of wheat cultivation in Jamalpur region of Bangladesh. Standard energy equivalents megajoules (MJ) were used to measure energy from different inputs and output, similarly, the global warming potential values for the 100-year timescale and a standard unit kilogram of carbon dioxide equivalent (kg CO₂eq) was used to estimate direct and indirect GHG emissions from the use of on-farm and off-farm inputs. Farm efficiency analysis tool (FEAT) was used to analyze GHG emission and its intensity. A non-parametric data envelopment (DEA) analysis was used to estimate the optimum energy requirement of wheat production. The results showed that the treatment combination having MT with optimum energy inputs is the best suit for cost-effective, sustainable CA practice in wheat cultivation without compromising with the yield during the dry season. A total of 22045.86 MJ ha⁻¹, 22158.82 MJ ha⁻¹, and 23656.63 MJ ha⁻¹ input energy for the practice of ST, MT, and CT was used in wheat production, and output energy was calculated as 158657.40 MJ ha⁻¹, 162070.55 MJ ha⁻¹, and 149501.58 MJ ha⁻¹, respectively; where energy use efficiency/net energy ratio was found to be 7.20, 7.31 and 6.32. Among these, MT is the most effective practice option taken into account in the wheat production process. The optimum energy requirement was found to be 18236.71 MJ ha⁻¹ demonstrating for the practice of MT that if recommendations are followed, 18.7% of input energy can be saved. The total greenhouse gas (GHG) emission was calculated to be 2288 kgCO₂eq ha⁻¹, 2293 kgCO₂eq ha⁻¹ and 2331 kgCO₂eq ha⁻¹, where GHG intensity is the ratio of kg CO₂eq emission per MJ of output energy produced was estimated to be 0.014 kg CO₂/MJ, 0.014 kg CO₂/MJ and 0.015 kg CO₂/MJ in wheat production. Therefore, CA approaches ST practice with 30 cm residue retention was the most effective GHG mitigation option when the net life cycle GHG emission was considered in wheat production in the silt clay loam soil of Bangladesh. In conclusion, the CA approaches being implemented for wheat production involving MT practice have the potential to mitigate global warming potential in Bangladesh to achieve soil carbon footprint, where the life cycle assessment approach needs to be applied to a more diverse range of wheat-based cropping systems.

Keywords: conservation agriculture and tillage, energy use efficiency, life cycle GHG, Bangladesh

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Authors: J. Bravo, F. Cabrera Suárez, B. Vega, L. Román, M. Martel, F. Acosta

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Ciguatera fish poisoning (CFP) is the most common non-bacterial intoxication in the world caused by ingestion of fish with bio-accumulated ciguatoxins (CTXs). It is typical in tropical and subtropical areas, mainly affecting the Caribbean Sea, Polynesia and other areas in the Pacific and Indian Oceans. Interest in Europe by the CFP is increasing in recent years as more and more cases in European hospitals are appearing, usually by people who have consumed ciguatoxin imported fish or have travelled to areas of risk for this poisoning. Since 2004 a series of poisonings raised the question of a possible occurrence of ciguatoxin in Europe, especially in the area of Macaronesia in the East Atlantic temperate zone. Furthermore, some studies have identified the presence of Gambierdiscus spp. in waters surrounding the Canary Islands and Madeira, a toxic dinoflagellate related to this poisoning. The toxin accumulates and concentrates through the food chain and affects to the end of the chain, the human consumer. Fish were collected from the Canary Islands waters and the toxin has been extracted and purified by using acetone and liquid/liquid partition in order to eliminate the excess of fatty acids that may interfere with the detection of the toxin. The fish extracts were inoculated in Neuroblastoma (neuro-2a) cells. After 24-h cell viability was used as an endpoint for cytotoxic effects measurement. Since 2011 our laboratory is collecting data for species such Seriola spp., Epinephelus spp., Makaira spp., Pomatomus spp., Xiphias spp., and Acantocybium spp., from all islands and including the sports fishing and professional activities, we obtained a 8% of fish that have ciguatoxin in their muscle. With these results, we conclude that the island where fishing and fish size affects the probability of catching a fish with the ciguatoxin.

Keywords: Canary Islands, ciguatera fish poisoning, ciguatoxin, Europe

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Authors: Mohammed Bnebaghdad, Feriel Betouche, Malika Semmani

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Image processing become more sophisticated over time due to technological advances, especially artificial intelligence (AI) technology. Currently, AI image processing is used in many areas, including surveillance, industry, science, and medicine. AI in medical image processing can help doctors diagnose diseases faster, with minimal mistakes, and with less effort. Among these diseases is malaria, which remains a major public health challenge in many parts of the world. It affects millions of people every year, particularly in tropical and subtropical regions. Early detection of malaria is essential to prevent serious complications and reduce the burden of the disease. In this paper, we propose and implement a scheme based on AI image processing to enhance malaria disease diagnosis through automated analysis of blood smear images. The scheme is based on the convolutional neural network (CNN) method. So, we have developed a model that classifies infected and uninfected single red cells using images available on Kaggle, as well as real blood smear images obtained from the Central Laboratory of Medical Biology EHS Laadi Flici (formerly El Kettar) in Algeria. The real images were segmented into individual cells using the watershed algorithm in order to match the images from the Kaagle dataset. The model was trained and tested, achieving an accuracy of 99% and 97% accuracy for new real images. This validates that the model performs well with new real images, although with slightly lower accuracy. Additionally, the model has been embedded in a Raspberry Pi4, and a graphical user interface (GUI) was developed to visualize the malaria diagnostic results and facilitate user interaction.

Keywords: medical image processing, malaria parasite, classification, CNN, artificial intelligence

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Authors: Dipak Subedi, Anil Giri, Christine Whitt, Tia McDonald

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This study aims to understand the impact of the pandemic on the overall economic well-being of the agricultural sector of the United States. The two key metrics used to examine the economic well-being are the bankruptcy rate of the U.S. farm operations and the operating profit margin. One of the primary reasons for farm operations (in the U.S.) to file for bankruptcy is continuous negative profit or a significant decrease in profit. The pandemic caused significant supply and demand shocks in the domestic market. Furthermore, the ongoing trade disruptions, especially with China, also impacted the prices of agricultural commodities. The significantly reduced demand for ethanol and closure of meat processing plants affected both livestock and crop producers. This study uses data from courts to examine the bankruptcy rate over time of U.S. farm operations. Preliminary results suggest there wasn’t an increase in farm operations filing for bankruptcy in 2020. This was most likely because of record high Government payments to producers in 2020. The Federal Government made direct payments of more than $45 billion in 2020. One commonly used economic metric to measure farm profitability is the operating profit margin (OPM). Operating profit margin measures profitability as a share of the total value of production and government payments. The Economic Research Service of the United States Department of Agriculture defines a farm operation to be in a) a high-risk zone if the OPM is less than 10 percent and b) a low-risk zone if the OPM is higher than 25 percent. For this study, OPM was calculated for small, medium, and large-scale farm operations using the data from the Agriculture Resource Management Survey (OPM). Results show that except for small family farms, the share of farms in high-risk zone decreased in 2020 compared to the most recent non-pandemic year, 2019. This was most likely due to higher commodity prices at the end of 2020 and record-high government payments. Further investigation suggests a lower share of smaller farm operations receiving lower average government payments resulting in a large share (over 70 percent) being in the critical zone. This study should be of interest to multiple stakeholders, including policymakers across the globe, as it shows the resilience of the U.S. agricultural system as well as (some) impact of government payments.

Keywords: U.S. farm sector, COVID-19, operating profit margin, farm bankruptcy, ag finance, government payments to the farm sector

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Authors: Tinomuvonga Manenji Zhou, Eubert Mahofa, Tatenda Crispen Madzokere

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The nanostructured formulation can increase fertilizer efficacy and uptake ratio of the soil nutrients in agriculture production and save fertilizer resources. Controlled release modes have properties of both release rate and release pattern of nutrients, for fertilizers that are soluble in water might be correctly controlled. Nanoparticles can reduce the rate at which fertilizer nutrients are in the soil by leaching. A slow release NPK-hydroxyapatite nano hybrid fertilizer was synthesized using exfoliated bentonite as filler material. A simple, scalable method was used to synthesize the nitrogen-phosphorus hydroxyapatite nano fertilizer, where calcium hydroxide, phosphoric acid, and urea were used as precursor material, followed by the incorporation of potassium through a liquid grinding method. The product obtained was an NPK-hydroxyapatite nano hybrid fertilizer. A quantitative analysis was done to determine the percentage of nitrogen, phosphorus, and potassium in the hybrid fertilizer. AAS was used to determine the percentage of potassium in the fertilizer. An accelerated water test was conducted to compare the nutrient release behavior of nutrients between the synthesized NPK-hydroxyapatite nano hybrid fertilizer and commercial NPK fertilizer. The rate of release of Nitrogen, phosphorus, and potassium was significantly lower in the synthesized NPK hydroxyapatite nano hybrid fertilizer than in the convectional NPK fertilizer. The synthesized fertilizer was characterized using XRD. NPK hydroxyapatite nano hybrid fertilizer encapsulated in exfoliated bentonite thus prepared can be used as an environmentally friendly fertilizer formulation which could be extended to solve one of the major problems faced in the global fertilization of low nitrogen, phosphorus, and potassium use efficiency in agriculture.

Keywords: NPK hydroxyapatite nano hybrid fertilizer, bentonite, encapsulation, low release

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Authors: Emilio Galdeano-Gómez, Ángeles Godoy-Durán, Juan C. Pérez-Mesa, Laura Piedra-Muñoz

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Eco-efficiency is receiving ever-increasing interest as an indicator of sustainability, as it links environmental and economic performances in productive activities. In agriculture, these indicators and their determinants prove relevant due to the close relationships in this activity between the use of natural resources, which is generally limited, and the provision of basic goods to society. In this context, various analyses have focused on eco-efficiency by considering individual family farms as the basic production unit. However, not only must the measure of efficiency be taken into account, but also the existence of a series of factors which constitute socio-economic, political-institutional, and environmental determinants. Said factors have been studied to a lesser extent in the literature. The present work analyzes eco-efficiency at a micro level, focusing on small-scale family farms as the main decision-making units in horticulture in southeast Spain, a sector which represents about 30% of the fresh vegetables produced in the country and about 20% of those consumed in Europe. The objectives of this study are a) to obtain a series of eco-efficiency indicators by estimating several pressure ratios and economic value added in farming, b) to analyze the influence of specific social, economic and environmental variables on the aforementioned eco-efficiency indicators. The present work applies the method of Data Envelopment Analysis (DEA), which calculates different combinations of environmental pressures (water usage, phytosanitary contamination, waste management, etc.) and aggregate economic value. In a second stage, an analysis is conducted on the influence of the socio-economic and environmental characteristics of family farms on the eco-efficiency indicators, as endogeneous variables, through the use of truncated regression and bootstrapping techniques, following Simar-Wilson methodology. The results reveal considerable inefficiency in aspects such as waste management, while there is relatively little inefficiency in water usage and nitrogen balance. On the other hand, characteristics, such as product specialization, the adoption of quality certifications and belonging to a cooperative do have a positive impact on eco-efficiency. These results are deemed to be of interest to agri-food systems structured on small-scale producers, and they may prove useful to policy-makers as regards managing public environmental programs in agriculture.

Keywords: data envelopment analysis, eco-efficiency, family farms, horticulture, socioeconomic features

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Authors: John Michael Russo

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Honeybees are important to our food system and continue to suffer from high rates of colony loss. Precision feed has brought many benefits to livestock cultivation and these should transfer to apiculture. However, apiculture has unique challenges. The objective of this research is to understand how principles of precision agriculture, applied to apiculture and feed specifically, might effectively improve state-of-the-art cultivation. The methodology surveys apicultural practice to build a model for assessment. First, a review of apicultural motivators is made. Feed method is then evaluated. Finally, precision feed methods are examined as accelerants with potential to advance the effectiveness of feed practice. Six important motivators emerge: colony loss, disease, climate change, site variance, operational costs, and competition. Feed practice itself is used to compensate for environmental variables. The research finds that the current state-of-the-art in apiculture feed focuses on critical challenges in the management of feed schedules which satisfy requirements of the bees, preserve potency, optimize environmental variables, and manage costs. Many of the challenges are most acute when feed is used to dispense medication. Technology such as RNA treatments have even more rigorous demands. Precision feed solutions focus on strategies which accommodate specific needs of individual livestock. A major component is data; they integrate precise data with methods that respond to individual needs. There is enormous opportunity for precision feed to improve apiculture through the integration of precision data with policies to translate data into optimized action in the apiary, particularly through automation.

Keywords: precision agriculture, precision feed, apiculture, honeybees

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Authors: Aminah Muchdar

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Efforts to increase soybean production have been pursued for years in Indonesia through the process of intensification and extensification. Increased production through intensification of increasing grain yield per hectare, among others includes the improvement of cultivation system such as the use of cultivars that have superior resistance to drought. Increased soybean production has been through the expansion of planting areas utilizing available idle dry land. However, one of the constraints faced in dryland agriculture was the limited water supply due to low intensity of rainfall that leads to low crop production. In order to ensure that soybeans are cultivated on dry land remains capable of high production, it is necessary to physiologically engineer the soybean with open stomata. The study was conducted in the greenhouse of Balai Penelitian Tanaman Serealia (BALITSEREAL) Maros, Sulawesi, Indonesia with a completely randomized block design h factorial pattern. The first factor was the water stress stadia while the second was the amount of sorbitol osmolit concentration application. Results indicated that there was an interaction between the plant height growth and number of leaves between the water clamping time and concentration of the osmolit sorbitol. The vegetative stage especially during flowering and pod formation was inhibited when the water was clamped, but by spraying osmolit sorbitol, soybean growth in terms of its height and number of leaves was enhanced. This study implies that the application of osmolit sorbitol may enhance the drought resistance of soybean growth. Future research suggested that more work should be done on the application of osmolit sorbital to other agriculture crops to increase their drought resistance in the drylands.

Keywords: DROUGHT, engineered physiology, osmolit sorbitol, soybean

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Authors: Mahbuba Kaneez Hasna

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Introductory Statement outlining the background: Little has been written about political ecology of urban gardening, such as a network of knowledge generation, technologies of food production and distribution, food consumption practices, and the regulation of ‘agricultural activities. For urban food gardens to sustain as a long-term food security enterprise, we will need to better understand the anthropological, ecological, political, and institutional factors influencing their development, management, and ongoing viability. Significance of the study: Dhaka as one of the fastest growing city. There are currently no studies regards to Bangladesh on how urban slum dwellerscope with the changing urban environment in the city, where they overcome challenges, and how they cope with the urban ecological cycle of food and vegetable production. It is also essential to understand the importance of their access to confined spaces in the slums they apply their indigenous knowledge. These relationships in nature are important factors in community and conservation ecology. Until now, there has been no significant published academic work on relationships between urban and environmental anthropology, urban planning, geography, ecology, and social anthropology with a focus on urban agriculture and how this contributes to the moral economies, indigenous knowledge, and government policies in order to improve the lives and livelihoods of slum dwellers surrounding parks and open spaces in Dhaka, Bangladesh. Methodology: it have applied participant observation, semi-structured questionnaire-based interviews, and focus group discussions to collect social data. Interviews were conducted with the urban agriculture practitioners who are slum dwellers who carry out their urban agriculture activities. Some of the interviews were conducted with non-government organisations (NGOs) and local and state government officials, using semi-structured interviews. Using these methods developed a clearer understanding of how green space cultivation, local economic self-reliance, and urban gardening are producing distinctive urban ecologies in Dhaka and their policy-implications on urban sustainability. Major findings of the study: The research provided an in-depth knowledge on the challenges that slum dwellers encounter in establishing and maintaining urban gardens, such as the economic development of the city, conflicting political agendas, and environmental constraints in areas within which gardening activities take place. The research investigated (i) How do slum dwellers perform gardening practices from rural areas to open spaces in the city? (ii) How do men and women’s ethno-botanical knowledge contribute to urban biodiversity; (iii) And how do slum dwellers navigate complex constellations of land use policy, competing political agendas, and conflicting land and water tenures to meet livelihood functions provided by their gardens. Concluding statement: Lack of infrastructure facilities such as water supply and sanitation, micro-drains and waste disposal areas, and poor access to basic health care services increase the misery of people in the slum areas. Lack of environmental health awareness information for farmers, such as the risks from the use of chemical pesticides in gardens and from grazing animals in contaminated fields or cropping and planting trees or vegetable in contaminated dumping grounds, can all cause high health risk to humans and their environment.

Keywords: gender, urban agriculture, ecosystem health, urban slum systems

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Authors: S. Benessam, T. H. Debieche, A. Drouiche, F. Zahi, S. Mahdid

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The intensive use of the chemical fertilizers and the pesticides in agriculture often produces a contamination of the groundwater by organic pollutants. The irrigation and/or rainwater transport the pollutants towards groundwater or water surface. Among these pollutants, one finds the nitrogen, often observed in the agricultural zones in the nitrate form. In order to understand the form and chemical mobility of nitrogen in groundwater, this study was conducted. A two-monthly monitoring of the parameters physicochemical and chemistry of water of the alluvial plain of Nil river (North-eastern Algerian) were carried out during the period from November 2013 to January 2015 as well as an in-situ investigation of the various chemical products used by the farmers. The results show a raise concentration of nitrates in the wells (depth < 20 m) of the plain, which the concentrations arrive at 50 mg/L (standard of potable water). On the other hand in drillings (depth > 20 m), one observes two behaviors. The first in the upstream part, where the aquifer is unconfined and the medium is oxidizing, one observes the weak nitrate concentrations, indicating its absorption by the ground during the infiltration of water towards the groundwater. The second in the central and downstream parts, where the groundwater is locally confined and the reducing medium, one observes an absence of nitrates and the appearance of nitrites and ammonium, indicating the reduction of nitrates. The projection of the analyses on diagrams Eh-pH of nitrogen has enabled to us to determine the intervals of variation of the nitrogen forms. This study also highlighted the effect of the rains, the pumping and the nature of the geological formations in the form and the mobility of nitrogen in the plain.

Keywords: groundwater, nitrogen, mobility, speciation

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Authors: Pradipta Chandra, Titas Bhattacharjee, Bhaskar Bhowmick

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The foundation of economy in India is primarily based on agriculture while this is the most neglected in the rural setting. More significantly, household women take part in agriculture with higher involvement. However, because of lower education of women they have limited access towards financial decisions, land ownership and technology but they have vital role towards the individual family level. There are limited studies on the institution-wise training barriers with the focus of gender disparity. The main purpose of this paper is to find out the factors of institution-wise training (non-formal education) barriers in technology transfer with the focus of participation of rural women in agriculture. For this study primary and secondary data were collected in the line of qualitative and quantitative approach. Qualitative data were collected by several field visits in the adjacent areas of Seva-Bharati, Seva Bharati Krishi Vigyan Kendra through semi-structured questionnaires. In the next level detailed field surveys were conducted with close-ended questionnaires scored on the seven-point Likert scale. Sample size was considered as 162. During the data collection the focus was to include women although some biasness from the end of respondents and interviewer might exist due to dissimilarity in observation, views etc. In addition to that the heterogeneity of sample is not very high although female participation is more than fifty percent. Data were analyzed using Exploratory Factor Analysis (EFA) technique with the outcome of three significant factors of training barriers in technology adoption by farmers: (a) Failure of technology transfer training (TTT) comprehension interprets that the technology takers, i.e., farmers can’t understand the technology either language barrier or way of demonstration exhibited by the experts/ trainers. (b) Failure of TTT customization, articulates that the training for individual farmer, gender crop or season-wise is not tailored. (c) Failure of TTT generalization conveys that absence of common training methods for individual trainers for specific crops is more prominent at the community level. The central finding is that the technology transfer training method can’t fulfill the need of the farmers under an economically challenged area. The impact of such study is very high in the area of dry lateritic and resource crunch area of Jangalmahal under Paschim Medinipur district, West Bengal and areas with similar socio-economy. Towards the policy level decision this research may help in framing digital agriculture for implementation of the appropriate information technology for the farming community, effective and timely investment by the government with the selection of beneficiary, formation of farmers club/ farm science club etc. The most important research implication of this study lies upon the contribution towards the knowledge diffusion mechanism of the agricultural sector in India. Farmers may overcome the barriers to achieve higher productivity through adoption of modern farm practices. Corporates will be interested in agro-sector through investment under corporate social responsibility (CSR). The research will help in framing public or industry policy and land use pattern. Consequently, a huge mass of rural farm-women will be empowered and farmer community will be benefitted.

Keywords: dry lateritic zone, institutional barriers, technology transfer in India, farm-women participation

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Authors: Jerzy Bański

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Central and Eastern European agriculture is characterized by large spatial variations in the structure of agricultural land and the structure of crops on arable land. In general, field crops predominate among the land used for agriculture. In the southern part of the study area, permanent crops have a relatively large share, which is due to favorable climatic conditions. Clear differences between the north and south of the region concern the structure of crop cultivation. In the north, the cultivation of cereals, mainly wheat, definitely prevails. In the south of the region, on the other hand, the structure of crops is more diverse, as more industrial crops are grown in addition to cereals. The primary cognitive objective of the study is to diagnose and identify the directions of changes in the structure of agricultural land use in the CEE region. Particular attention was paid to the spatial differentiation of this structure and its importance in its formation of various conditions. The analysis included the basic elements of the structure of agricultural land use and the structure of crops on arable land. The decrease in the area of arable land is characteristic of the entire region and is the result of the territorial growth of cities, the development of communications infrastructure (rail and road), and the increase in the rationality of crop production involving, among other things, the exclusion from the cultivation of land with the lowest agro-ecological values and their afforestation. It can be summarized that the directions of changes in the basic categories of agricultural land are related to agro-ecological conditions, which indicates an increase in the rationality of crop production. In countries with lower-quality of agricultural production space, the share of grassland generally increased, while in countries with favorable conditions -mainly soil- the share of arable land increased. As for the structure of field crops, the direction of its changes seems to be mainly due to economic and social reasons. Ownership changes shaping an unfavorable agrarian structure (fragmentation and fragmentation of arable fields) and the process of aging of the rural population resulted in the abandonment of resource- and labor-intensive crops. As a result, the importance of growing fruits and vegetables, and potatoes has declined. The structure of vegetable crops has been greatly influenced by the accession of Central and Eastern European countries to the European Union. This is primarily the increase in the importance of oil crops (rapeseed and sunflower) related to biofuel production. In the case of cereal crops, the main direction of change was the increase in the share of wheat at the expense of other cereal species.

Keywords: agriculture, land use, Central and Eastern Europe, crops, arable land

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Authors: Wei Wen Yang, Emily Chia Yu Su

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Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.

Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti

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Authors: Adedoyin Opeyemi Osokoya

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The study assesses the influence of social media on perceived learning outcome of agricultural science students in tertiary institutions in Oyo state, Nigeria. The four-stage sampling procedure was used to select participants. All students in the seven tertiary institutions that offer agriculture science as a course of study in Oyo State was the population. A university, a college of agriculture and a college of education were sampled, and a department from each was randomly selected. Twenty percent of the students’ population in the respective selected department gave a sample size of 165. Questionnaire was used to collect information on respondents’ personal characteristics and information related to access to social media. Data were analysed using descriptive statistics, chi-square, correlation, and multiple regression at the 0.05 confidence level. Age and household size were 21.13 ± 2.64 years and 6 ± 2.1 persons respectively. All respondents had access to social media, majority (86.1%) owned Android phone, 57.6% and 52.7% use social media for course work and entertainment respectively, while the commonly visited sites were WhatsApp, Facebook, Google, Opera mini. Over half (53.9%) had an unfavourable attitude towards the use of social media for learning; benefits of the use of social media for learning was high (56.4%). Removal of information barrier created by distance (x̄=1.58) was the most derived benefit, while inadequate power supply (x̄=2.36), was the most severe constraints. Age (β=0.23), sex (β=0.37), ownership of Android phone (β=-1.29), attitude (β=0.37), constraints (β =-0.26) and use of social media (β=0.23) were significant predictors of influence on perceived learning outcomes.

Keywords: use of social media, agricultural science students, undergraduates of tertiary institutions, Oyo State of Nigeria

Procedia PDF Downloads 140

Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

Procedia PDF Downloads 99

Authors: Guadalupe Pérez, Jorge Islas, Mirna Guevara, Raúl Suárez

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Jatropha curcas is a perennial oleaginous plant that is currently considered an energy crop with high potential as an environmentally sustainable biofuel. During the last decades, research in biofuels has grown in tropical and subtropical regions in Latin America. However, as far we know, there are no reports on the growth and yield patterns of Jatropha curcas under the specific agro climatic scenarios of the State of Morelos, Mexico. This study presents the results of 52 months monitoring of 10 toxic and non-toxic ecotypes of Jatropha curcas (E1M, E2M, E3M, E4M, E5M, E6O, E7O, E8O, E9C, E10C) in an experimental plantation with minimum watering and fertilization resources. The main objective is to identify the ecotypes with the highest potential as biodiesel raw material in the select region, by developing experimental information. Specifically, we monitored biophysical and growth parameters, including plant survival and seed production (at the end of month 52), to study the performance of each ecotype and to establish differences among the variables of morphological growth, net seed oil content, and toxicity. To analyze the morphological growth, a statistical approach to the biophysical parameters was used; the net seed oil content -80 to 192 kg/ha- was estimated with the first harvest; and the toxicity was evaluated by examining the phorbol ester concentration (µg/L) in the oil extracted from the seeds. The comparison and selection of ecotypes was performed through a methodology developed based on the normalization of results. We identified four outstanding ecotypes (E1M, E2M, E3M, and E4M) that can be used to establish Jatropha curcas as energy crops in the state of Morelos for feasible agro-industrial production of biodiesel and other products related to the use of biomass.

Keywords: biodiesel production, Jatropha curcas, seed oil content, toxic and non-toxic ecotypes

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Authors: Vasiliki Kolake, Christos Kavalaris, Sofia Megoudi, Maria Maxouri, Panagiotis A. Karas, Aris Kyparissis, Efi Levizou

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Conservation agriculture (CA), is a production system approach that can tackle the challenges of climate change mainly through facilitating carbon storage into the soil and increasing crop resilience. This is extremely important for the vulnerable Mediterranean agroecosystems, which already face adverse environmental conditions. The agronomic practices used in CA, i.e. permanent soil cover and no-tillage, result in reduced soil erosion and increased soil organic matter, preservation of water and improvement of quality and fertility of the soil in the long-term. Thus the functional characteristics and processes of the soil are considerably affected by the implementation of CA. The aim of the present work was to assess the effects of CA on soil nitrification potential and mycorrhizal colonization about the above-ground production in a wheat field. Two adjacent but independent field sites of 1.5ha each were used (Thessaly plain, Central Greece), comprising the no-till and conventional tillage treatments. The no-tillage site was covered by residues of the previous crop (cotton). Potential nitrification and the nitrate and ammonium content of the soil were measured at two different soil depths (3 and 15cm) at 20-days intervals throughout the growth period. Additionally, the leaf area index (LAI) was monitored at the same time-course. The mycorrhizal colonization was measured at the commencement and end of the experiment. At the final harvest, total yield and plant biomass were also recorded. The results indicate that wheat yield was considerably favored by CA practices, exhibiting a 42% increase compared to the conventional tillage treatment. The superior performance of the CA crop was also depicted in the above-ground plant biomass, where a 26% increase was recorded. LAI, which is considered a reliable growth index, did not show statistically significant differences between treatments throughout the growth period. On the contrary, significant differences were recorded in endomycorrhizal colonization one day before the final harvest, with CA plants exhibiting 20% colonization, while the conventional tillage plants hardly reached 1%. The on-going analyses of potential nitrification measurements, as well as nitrate and ammonium determination, will shed light on the effects of CA on key processes in the soil. These results will integrate the assessment of CA impact on certain below and above-ground processes during wheat cultivation under the Mediterranean climate.

Keywords: conservation agriculture, LAI, mycorrhizal colonization, potential nitrification, wheat, yield

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Authors: Innocent Pangapanga, Eric Mungatana

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Tropical cyclones–related floods (TCRFs) in Malawi have devastating effects on smallholder agriculture, thereby threatening the food security agenda, which is already constrained by poor agricultural innovations, low use of improved varieties, and unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have engineered and indigenously implemented sustainable landscape management (SLM) innovations to contain the adverse effects of TCRFs on farm productivity. This study, therefore, interrogated the efficacy of SLM adoption on farm productivity under varying TCRFs, while controlling for the potential selection bias and unobservable heterogeneity through the application of the Endogenous Switching Regression Model. In this study, we further investigated factors driving SLM adoption. Substantively, we found TCRFs reducing farm productivity by 31 percent, on the one hand, and influencing the adoption of SLM innovations by 27 percent, on the other hand. The study also observed that households that interacted SLM with TCRFs were more likely to enhance farm productivity by 24 percent than their counterparts. Interestingly, the study results further demonstrated that multiple adoptions of SLM-related innovations, including intercropping, agroforestry, and organic manure, enhanced farm productivity by 126 percent, suggesting promoting SLM adoption as a package to appropriately inform existing sustainable development goals’ agricultural productivity initiatives under intensifying TCRFs in the country.

Keywords: tropical cyclones–related floods, sustainable landscape management innovations, farm productivity, endogeneity, endogenous switching regression model, panel data, smallholder agriculture

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Bhaskar M. Murai, Neeraj Banchor, Ishveen Chabbra, Madhusudhan Nadgir, S. Vidhya

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Sol-gel technology combined with electronics and biochemistry helps to overcome the problems caused by mosquitoes by developing a portable, low-cost device which enables controlled release of trapped compound inside it. It is a wet-chemical technique which is used primarily for fabrication of silicate gel which is usually allowed to dry as per requirement. The outcome is solid rock hard material which is porous and has lots of applications in different fields. Taking porosity as a key factor, allethrin a naturally occurring synthetic compound with molecular mass 302.40 was entrapped inside the sol-gel matrix as a dopant. Allethrin is commonly used as an insecticide and is a key ingredient in commercially available mosquitoes repellent in Asian and subtropical countries. It has low toxicity for humans and birds, and are used in many household insecticides such as RAID as well as mosquito coils. They are however highly toxic to fish and bees. Insects subject to its exposure become paralyzed (nervous system effect) before dying. They are also used as an ultra-low volume spray for outdoor mosquito control. Therefore, there is a need for controlled release of allethrin in the environment. For controlled release of allethrin from sol-gel matrix, its (allethrin) we utilized temperature based controlled evaporation through porous sol-gel. Different types of fabric like cotton, Terri-cotton, polyester, surgical cap, knee-cap etc are studied and the best with maximum absorption capacity is selected to hold the sol-gel matrix with maximum quantity. For sol-gel coating 2 x 2cm cloth pieces are dipped in sol-gel solution for 10 minutes and by calculating the weight difference we concluded that Terri cotton is best suitable for our project. An electronic circuit with heating plate is developed in to test the controlled release of compound. An oscillatory circuit is used to produce the required heat.

Keywords: sol-gel, allethrin, TEOS, biochemistry

Procedia PDF Downloads 375

Authors: Toshifumi Hiramatsu, Satoshi Morita, Manuel Pencelli, Marta Niccolini, Matteo Ragaglia, Alfredo Argiolas

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Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Keywords: the agricultural robot, autonomous control, path-tracking control, tracked mobile robot

Procedia PDF Downloads 172

Authors: Rafeza Begum, Mohammad Mokhlesur Rahman, Safikul Moula, Rafiqul Islam

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Potassium (K) is crucial for healthy soil and plant growth. However, K fertilization is either disregarded or poorly underutilized in Bangladesh agriculture, despite the great demand for crops. This could eventually result in a significant depletion of the soil's potassium reserves, irreversible alteration of the minerals that contain potassium, and detrimental effects on crop productivity. Soil K mining in Bangladesh is a worrying problem, and we need to evaluate it thoroughly and find remedies. A pot culture experiment was conducted in the greenhouse of Bangladesh Institute of Nuclear Agriculture (BINA) using eleven soil series of Bangladesh in order to see the depletion behaviour of potassium (K) by continuous cropping using rice (var. Iratom-24) as the test crop. The soil series were Ranishankhail, Kaonia. Sonatala, Silmondi, Gopalpur, Ishurdi, Sara, Kongsha, Nunni, Lauta and Amnura on which four successive rice plants (45 days duration) were raised with (100 ppm K) or without addition of potassium. Nitrogen, phosphorus, sulfur and zinc were applied as basal to all pots. Potassium application resulted in higher dry matter yield, increased K concentration and uptake in all the soils compared with no K treatment; which gradually decreased in the subsequent harvests. Furthermore, plant takes up K not only from exchangeable pool but also from non-exchangeable sites and a minimum replenishment of K from the soil reserve was observed. Continuous cropping has resulted in the depletion of available K of the soil. The result indicated that in order to sustain higher crop yield under intensive cultivation, the addition of potash fertilizer is necessary.

Keywords: potassium, exchangeable pool, depletion behavior., Soil series

Procedia PDF Downloads 126

Authors: Medhat Tawfik, Ezzat Abd El Lateef, Bahr Amany, Mohamed Magda

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Applying organic farming systems in biosaline agriculture is unconventional approach for sustainable use of marginal soil and desert land for planting non-traditional halophytic crops such as Leptochloa fusca, Kochia indica, Sporobolus virginicus and Spartina patens. These plants are highly salt tolerant C4 halophytic forage plants grown well in coastal salt marsh. These halophytic plant will take important place in the farming system, especially in the coastal areas and salt-affected land. We can call it environmentally smart crops because they ensure food security, contribute to energy security, guarantee environmental sustainability, and mitigate the negative impacts of climate change. Organic Agriculture is the most important and widely practiced agro-ecological farming system. It is claimed to be the most sustainable approach and long term adaptation strategy. It promotes soil fertility and diversity at all levels and makes soils less susceptible to erosion. It is also reported to be climate change resilience farming systems as it promotes the proper management of soil, water, biodiversity and local knowledge and provides producers with ecologically sound management decisions. A field experiment was carried out at the Model Farm of National Research Centre, El Tour, South Sinai to study the impact of (Mycorrhiza 1kg/fed., charcoal 4 tons/fed., chicken manure 5 tons/fed., in addition to control treatment) on some growth characters, photosynthetic pigments content, and some physiological aspects i.e. prolind and soluble carbohydrates content, succulence and osmotic pressure values, as well as nutritive values i.e. Crude fat (CF), Acid detergent fiber (ADF), Neutral detergent fiber (NDF), Ether extract (EE) and Nitrogen-free extract (NFE) of five halophytic plant species (Leptochloa fusca, Kochia indica, Sporobolus virginicus and Spartina patens). Our results showed that organic fertilizer treatment enhanced all the previous character as compared with control with superiority to chicken manure over the other treatments.

Keywords: organic agriculture, halophytic plants, saline environment, water security

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Authors: Lilian Mbinya Muasa

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Climate change is inevitable and a global challenge with long term implications to the sustainable development of many countries today. The negative impacts of climate change are creating far reaching social, economic and environmental problems threatening lives and livelihoods of millions of people in the world. Developing countries especially sub-Saharan countries are more vulnerable to climate change due to their weak ecosystem, low adaptive capacity and high dependency on rain fed agriculture. Countries in Sub-Saharan Africa are more vulnerable to climate change impacts due to their weak adaptive capacity and over-reliance on rain fed agriculture. In Kenya, 78% of the rural communities are poor farmers who heavily rely on rain fed agriculture thus are directly affected by climate change impacts.Currently, many parts of Kenya are experiencing successive droughts which are contributing to persistently unstable and declining agricultural productivity especially in semi arid eastern Kenya. As a result, thousands of rural communities repeatedly experience food insecurity which plunge them to an ever over-reliance on relief food from the government and Non-Governmental Organization In addition, they have adopted poverty coping strategies to diversify their income, for instance, deforestation to burn charcoal, sand harvesting and overgrazing which instead contribute to environmental degradation.This research was conducted in Makueni County which is classified as one of the most food insecure counties in Kenya and experiencing acute environmental degradation. The study aimed at analyzing the adaptive capacity to climate change across farming households of Makueni County in Kenya by, 1) analyzing adaptive capacity to climate change and agricultural productivity across farming households, 2) identifying factors that contribute to differences in adaptive capacity across farming households, and 3) understanding the relationship between climate change, agricultural productivity and adaptive capacity. Analytical Hierarchy Process (AHP) was applied to determine adaptive capacity and Total Factor Productivity (TFP) to determine Agricultural productivity per household. Increase in frequency of prolonged droughts and scanty rainfall. Preliminary findings indicate a magnanimous decline in agricultural production in the last 10 years in Makueni County. In addition, there is an over reliance of households on indigenous knowledge which is no longer reliable because of the unpredictability nature of climate change impacts. These findings on adaptive capacity across farming households provide the first step of developing and implementing action-oriented climate change policies in Makueni County and Kenya.

Keywords: adaptive capacity, agricultural productivity, climate change, vulnerability

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Authors: Rogelio Omar Corona-Núñez, Alma Mendoza-Ponce

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The Tropical Dry Forest not only is one of the most important tropical ecosystems in terms of area, but also it is one of the most degraded ecosystems. However, little is known about the degradation impacts on carbon stocks, therefore in carbon emissions. There are different studies which explain its deforestation dynamics, but there is still a lack of understanding of how they correlate to carbon losses. Recently different authors have built current biomass maps for the tropics and Mexico. However, it is not clear how well they predict at the local scale, and how they can be used to estimate carbon emissions. This study quantifies the forest net carbon losses by comparing the potential carbon stocks and the different current biomass maps in the Southern Pacific coast in Oaxaca, Mexico. The results show important differences in the current biomass estimates with not a clear agreement. However, by the aggregation of the information, it is possible to infer the general patterns of biomass distribution and it can identify the driving forces of the carbon emissions. This study estimated that currently ~44% of the potential carbon stock estimated for the region is still present. A total of 6,764 GgC has been emitted due to deforestation and degradation of the forest at a rate of above ground biomass loss of 66.4 Mg ha-1. Which, ~62% of the total carbon emissions can be regarded as being due to forest degradation. Most of carbon losses were identified in places suitable for agriculture, close to rural areas and to roads while the lowest losses were accounted in places with high water stress and within the boundaries of the National Protected Area. Moreover, places not suitable for agriculture, but close to the coast showed carbon losses as a result of urban settlements.

Keywords: above ground biomass, deforestation, degradation, driving forces, tropical deciduous forest

Procedia PDF Downloads 183