The presence of symptoms of Fusariumsp was sought and noted in each farmer’s field. The presence of symptoms of Bunchy Top Banana Disease including plants that have turned into flowers. During focus group discussions, each agricultural practice was analyzed in a participatory manner with the farmers. Application modes of the practices have been detailed and then its deviation from organic farming practices is assessed using scores. A score of 1 means a small difference between the agricultural practice used and the practice of organic farming. The score 2 means an average difference while the score 3 means a high difference between the agricultural practice used and the practice of organic farming. The Generalized Linear Model distribution and logit link with the binomial family were carried out to determine the effects of agricultural practices and types of crop associations on the presence of the major pests and diseases of bananas and plantains.

The Generalized Linear Model distribution and logit link with the binomial family were also used to determine the relationship between the modes of production and acquisition of banana and plantain seedlings,vertical grow system the availability of different cultivars, means of farmer’s communication and localities. All the analyses were carried out in Rat the significant level of 5%.A total of 210 banana and plantains farmers were surveyed in the 4 zones of high production. Farmer’s surveyed age varied from 39 to 47 years old with a meanage of 42 years. The majority of farmers were men especially in the Plateau district where no female banana/plantain farmers were surveyed. The most important presence of women in bananas and plantains production was found in the Oueme district. Bananas and plantains farmers were generally monogamous with 31% as the highest rate of polygamy observed in the Atlantique district. The ethnic groups represented were Goun , Kotafon , Aizo and Fon . The majority of the farmers surveyed were Christians , anemists and very few Muslims . The Mono district followed by the Atlantique had lands available for agriculture especially for the production of bananas and plantains.

However, farmers of the Oueme and Plateau have more professional experiences. The latter were less associated in-cooperatives or groups of farmers for the bananas and plantains production. The majority of farmers in Mono , Oueme and Plateau have a good knowledge of organic banana production systems. Additionally, very few Atlantique farmers knew the organic banana production. All the farmers surveyed were motivated to convert their production systems into organic production systems and the majority of them were ready to pay the costs of the certification process for their organic products. The main activities of surveyed farmers were agriculture followed by animal breeding and food processing . In total, the availability of 26 cultivars of bananas and plantains has been identified as major cultivars in the production areas . The availability of these cultivars varied across time and production areas . In the Atlantique district, cultivars were highly available towards the end of the year. In Mono district, several cultivars were moderately available at the year starting and had become highly available throughout the year. In Oueme district,all cultivars were poorly available in the first half of the year and had become highly available in the second half of the year. Finally, in the Plateau district, a few cultivars that were poorly available at the year starting became highly available from April to May . Statistical analyzes revealed significant negative effects of agricultural practices on the presence of the major banana pests . The most frequent agricultural practices used to face this issue were crop association , mechanical destruction of diseased plants ,banana plantations in shallows , crop rotation , compost use , poultry manure use and herbicide use . Other agricultural practices were less frequently used by farmers. The use of biopesticides,trap plants, composts, crop rotation and crop association have significant negative effects on the presence of the banana weevil.

In the conversion to organic, the age of producers is another barrier. Table 3 shows that the probability of the conversion dropped substantially as producers become older. With the base group of 30 or young, the age group 31 60 has a probability of 20% lower in adopting organic farming, and the group 61 or older has a drop of 24%. It makes sense that the shorter planning horizons for older farmers offered less time to recapture investment costs and capture the long-term benefits. In addition, it was claimed that as one ages, the avoidance of risk becomes more important than expected future higher returns . The conversion to organic farming also demands the time and efforts to assimilate organic knowledge and methods, and likely expose farmers to lower yields and non-premium price in the transition period, and these surely weigh in on farmers decision on organic farming.The chance of conversion is 13% higher for farmers who had education of technical school or higher than farmers with just high-school diploma or lower. This conformed a previous claim that farmers with some college education had higher odds of adopting organic farming.

However, the impact of education was not observed in conventional farmers and those with mixed enterprises. The lack of observations on mixed enterprise group may be the root of the result. While some results of this study bear resemblances to previous studies, there are some noteworthy differences identified. The impact of off-farm job is one of them. Our model was not in supportive of the claim that there exists an inverse relationship between working off-farm and the adoption of organic farming because off-farm job reduce the availability of labor and hence impedes organic farming practices. On the contrary, dutch bucket hydroponic the impact of off-farm jobs in our model lead to an increased likelihood of organic conversion, which may reflect the influence of the enhanced risk tolerance due to extra income from off-farm jobs. The absence of off-farm job variable led to substantial changes in parameters of other variables in the model, so it, though less significant in statistics, was retained in the model. The further clarification hinges on the future studies with more observations and elaborated instruments related off-farm job. Analysis of the large survey in the Southern states came up with a few contributing factors in farmers’ choice of conversion to organic production. The pool of factors comprise barriers and stimuli, each of them have been discussed in detail in the previous section. In view of potential impacts and the efficient way of improve the adoption of organic farming, the four factors of risk aversion, the age of operators, and the size of farms, and marketing channels deserve further elaboration.

Organic farming is still at its early stage, there exist tremendous uncertainty in both production and marketing process. For most risk version farmers, an acceptable way to follow was doing by the top dog. Nevertheless the exemplars available at this stage are quite limited. A way to increase farmers’ expose to and know those successful front runners is to organize more workshops and training.Land grant universities and USDA agencies such as FSA and RMA could play a more active role in helping farmers overcome the risk barrier. The age of operators and its adverse impact certainly deserve multiple looks.From 2012 census data, about 62% of farmers were 55 or older, which was 17years older than the age of average American workers. Old operators was significant less likely to go organic. While it isn’t realistic to expect a change of age structure shortly, it makes sense to support young farmers in land requisition and in tax relief. Currently, the old operators’ ownership of expensive land and the existing subsidy programs give the elder an edge to stay in farming, which forms a hindrance of the conversion to organic farming. An urgent need is to have some stimulus mechanisms to expedite the influx of the young into farming business. The change of land tenures and government subsidy programs is needed to support the business of the young beginning farmers.

The same is true for the agricultural economist who wants to know if producers and consumers are responding positively to a new agricultural program; it is for this agricultural economist to spend hours and hours living with the farmers by observing and noticing, discreetly on the spot or preferably at home, anything that can constitute reliable indicators todescribe the reality studied. The few examples that have just been given do not exhaust all the research possibilities offered by one or other of the methodological approaches analyzed; they merely highlight the particular characteristics of the two categories of research .Qualitative research is therefore fundamentally based on the assumption that an internal understanding can be accessed, and this makes possible an understanding of human behavior superior to that provided by a surface study that involves quantitative methods. In addition, the qualitative method allows the researcher to closely glue the data and thereby develop, from the data themselves,explanatory patterns that are more analytical and better articulated on the reality.In qualitative research, the theory often occurs after the observation, from anextrapolation resulting from the events themselves.

The researcher does not start with models, theories, hypotheses, but rather a certain understanding of the interactions and everyday facts that will be examined against more general models or treatments. It is usually from an interpretation of the world through the perspective of the observed subjects that the meaning of reality is revealed when using a qualitative approach to research. But it is precisely on these points that there is opposition between the principles of quantitative methods and those of qualitative methods. Many economics researchers consider the quantitative approach insufficient to meet current needs. For them, research in economics should make more use of a methodological approach where there is communication and a deep understanding between the subjects observed and the subjects who observe .An analysis like the one just made can be interpreted, at first glance, as a plea for the qualitative method which, in itself, hydroponic gutter should be considered as the best way to reach the reality of the social world. that we want to study. In these epistemological arguments, we must rather see an incentive to stop doubting the seriousness of this approach. “Qualitative” researchers in agricultural economics are only beginning to make a dent in the unanimity often expressed in favor of the superiority of quantitative research methods. All this debate ultimately results only from the choice of the paradigm made by the researchers .

One may wonder whether we are in the process of undergoing, in the field of agricultural sciences, what Kuhn calls a scientific revolution. One fact remains: qualitative research is not close to supplanting quantitative research, but the first is emerging more and more so that the two approaches come together almost regularly. How to explain this change of situation almost spectacular? The answer can come again from Kuhn’s book. Indeed, for Kuhn, any scientific group eventually develops a paradigm of its own and, when this paradigm no longer meets the needs of the group of researchers who use it, it is replaced by a new paradigm. Since the term paradigm has been widely used in scientific circles for a few years, the meaning of this term needs to be clarified here. This is all the more justified because Master man has found in Kuhn’s work twenty-one different ways of using the word paradigm. According to Kuhn,the term paradigm can be used in two different senses. On the one hand, it represents the whole set of beliefs, recognized values and techniques that are common to members of a given group.On the other hand, it denotes an isolated element of this set: the solutions of concrete enigmas which, used as models or examples, can replace the explicit rules as bases of solution for the riddles that remain in the so-called normal science .

It is therefore important to remember that a paradigm is fundamentally a way of seeing the world, a general perspective, a way of breaking down the complex reality of the real universe. As such, paradigms are deeply present in the socialization of paradigm researchers as well as practitioners since they tell them what is important and reasonable to study.Moreover, paradigms are normative; they tell practitioners and researchers what they must do without the need for them to go through long existential or epistemological considerations. However, this aspect of the paradigm is at the same time its strength and its weakness. He is his strength because he makes action possible; it is its weakness because the very reason for the action is hidden in the postulates not put into question in the paradigm.Adherence to a particular paradigm rather than another predisposes the partisan of a paradigm to see the world and the events contained in it in a very different way.

Farming land was generally linked to excessive nutrients of surface water . Residential land use exerts a major effect on nutrients as well as alkali metals owing to animal and human excreta and the use of table salts, disinfectants, and food additives in daily life. Intensified fish breeding ponds posed serious threat to the surface water quality since a large portion of biogenic elements in the fodder was not utilized by fish. In addition,agri-chemicals like quick lime, calcium hypochlorite and potassium permanganate were used as disinfectants to prevent fish disease, which led to high levels of major metal cations .Many studies focus on the cycling of nutrients in ponds , whereas much less attention is paid to alkali metal and alkaline earth metal cations such as Ca2+, Mg2+, Na+ and K+. These metal cations are necessary to maintain the normal function of living organisms. For example,ebb flow table the ions of Mg2+ is involved in some enzyme-catalyzed reactions in the human body and also essential to chlorophyll synthesis in plants .

However, excessive contents of these cations in water bodies would have adverse impact on human health and ecosystem.For example, high levels of Na+ in soil tend to displace Ca2+ and Mg2+,which would reduce the soil permeability and consequently affect the growth and yield of crops .Ponds and reservoirs are widely distributed across southern China due to its abundant precipitation and agricultural demand,such as fish farming and paddy planting . To explore the impacts of land use and fish farming on the geo-chemical behaviors of alkali metals, we determined the concentrations of alkali metals of water bodies from 103 ponds under the influence of different land use and/or used for fish farming in southern China.The suitability of pond water for irrigation was finally assessed to the help farmers and policy-makers make related management strategies to better play valuable role of ponds. The head water watershed of Jinjing was selected as the study area in a hilly subtropical region of the Hunan Province, China. The annual precipitation in the study area ranges from 1200 to 1500 mm, and the elevation ranges from 56 m to 434.8 m.

The land use in the study area is dominated by three major types, namely forest, paddy fields, and tea plantations, which account for 58.5%,31.6%, and 4.3% of the total area, respectively. 5.6% of the remaining areas are waters and residential ones. In areas like this, agricultural products and aquaculture are generally the main sources of income for farmers. In the study area,there are approximately 2010 ponds with a density of 20 ponds per km2, and more than 60% of these are used for aquaculture . In our study, 103 ponds and reservoirs were randomly selected to observe the alkali metal contents of the pond water bodies. Quick lime and salt are commonly used as disinfectants in fishponds to prevent fish disease. Moreover, the feeding stuff is thought to be a major contributor to increase in nitrogen and phosphorus of fishponds.These kinds of fishing practice might affect the geo-chemical behavior of alkali metals. To study the influence of fishing practices on alkali elements, the correlation of alkali elements and different N and P components was presented in the context of forest land use with fish farming ponds vs. natural ponds.Precision farming aims to manage production inputs over many small management zones rather than on largezones. It is difficult to manage inputs at extremely fine scales, especially in the case of the tea irrigation system.

However, in real sense we expect site-specific irrigation approach to potentially improve the overall water management in comparison to irrigated farms of hundreds of acres. A critical element of the irrigation scheduling and management is the accurate estimation of irrigation supplies and its proper allocation for the irrigation of structures based on the actual planted areas. All irrigation scheduling procedures consist of monitoring indicators that determine the need for irrigation. The final decision depends on the irrigation criterion, strategy and goal.The amount of water applied is determined by using a criterion to determine irrigation need and a strategy to prescribe how much water to apply in any situation. The right amount of daily irrigation supply and monitoring at the right time within the discrete irrigation unit is essential to improve the irrigation water management of a scheme .Many computerized tools have been used for scheduling irrigation deliveries and improving the irrigation project management. One such tool is a Geographical Information System.Its use in irrigation management with their large volumes of spatially and temporally distributed data is most beneficial. The GIS capability to integrate spatial data from different sources, with diverse formats, structures, projections or resolution levels,constitute the main characteristics of these systems, thus providing needed aid for those models that incorporate information in which spatial data has a relevant role. This explained about the capability of GIS for decision-making.

Certification benefits LSH practices aggregating economic value to its products, overcoming potential yield loss in situations which there is a yield penalty of non-intensive agriculture and increasing profits in situation in which there is no yield loss due to organic/agroforestry management. By and large, there appears to be a misunderstanding over the definitions of food security and agricultural production in the land-use debate arena. Global, national and regional food security means that a given nation should maximize production of agricultural goods on a per capita basis. Household and individual food security also encompasses individual nutritional standards, including hygiene education, clean water and sanitation .LSP is based on the idea that intensification increase food production, while LSH suggests that non-intensive farming may be also productive. Early studies have found that average organic-non organic yield ratio for 26 crops is 0.9, although more than half of milk products and beans had ratios graters than 1.0. Badgley et al.compared yield trends among developing and developed countries to find that most food categories had yield ratios slightly <0.1 in developed countries, while developing ones had ratios >0.1.

In turn, Seufert et al.suggest that the overall yield of intensive methods is higher than that of the organics, although the organic/intensive yield ratio is again very context-dependent. For fruits, this ratio is very close to one as predicted by LSH. Perennials and legumes, as well as staple crops, such as maize and soybeans, account for ~0.9 organic/intensive yields .Family farming is by far the most common form of agriculture in the world. FAO estimates that there are at least 570 million farms worldwide and that over 90% of them are family farms. The vast majority of family farms are small and about 94% of farms worldwide have less than 5ha, vertical rack system and even a large part of those have less than 2 hectares. One of the primary constraints in quantitative assessments is that small farms are frequently not detectable from official records and statistics. It is thus difficult to accurately quantify their number, distribution, production capacity and contribution to food availability. Small farms are regarded to produce more per land area and negative farm size-productivity relationship is long known by agriculturalists as well . Among the advantages of small farming are the multiple crop benefits, better output composition ; higher irrigation efficiency due to small area and proximity agricultural land to farm steads; and labor quality and intensity .

Small farms may also use more input per agricultural land, and resource use is more efficient in small individual or family agricultural areas. Although many small farms are in fact more intensive than the large scale counterparts, LSH is generally associated to small subsistence agroecological methods, while LSP is described to agribusiness companies and large land owners. Therefore, size of farms is extremely important when it comes to economy livelihoods and food security.Of particular interest to LSP and LSH debate is the view of the agricultural landscape as a system with inputs,outputs and externalities. Thus comparing outputs in isolation is not enough to distinguish the efficiency of intensive and non-intensive agriculture production. In general, intensive agriculture is associated with larger inputs and slightly more outputs,ensuing negative externalities. In turn, agro ecological management have lower inputs and lower outputs and results in positive ecological externalities . The efficiency of an agro ecological system is thus frequently higher , whereas intensive agricultural management is generally lower. Therefore, not only production but also efficiency is important.Critical factors, such as water scarcity, economic and climate change risks, make efficiency, not productivity,central in managing the agricultural landscape system.

LSP often assumes that agriculture production/efficiency and food security are linearly correlated, a perspective often criticized by LSH . The increasing use of agricultural land for producing bio-fuels along with food scarcity, low health conditions for the poor, food waste and over consumption make the relationship between agricultural production and food security complexly non-linear. Hence, not only increasing yields per capita,but also food accessibility has to be tackled to secure food especially for the poor.Food waste has also a large impact on food security. Globally, around 30% of the food is wasted . Of this,40% is lost in post-harvest procedures in under-developed countries and 40% is lost by retailers and consumers in industrialized countries.Over consumption is another problem, entailing health issues as well as decreases in food availability for others.Obesity, although historically associated to wealthy nations, is becoming a problem worldwide. Additionally,the expansion of biofuels or biomass production consumes large tracts of lands that could be used for growing crops, further increasing food insecurity .Therefore, two basics gaps must be bridged to achieve individual and household food security: the potential and realized yield/efficiency gap and the production-individual food security gap.

The choice of the radius parameters proves to be dependent on the application.While the normal radius rn can usually simply be set to a value equal or greater than the resolution, the support radius r has to be adjusted to the special requirements. If the plant organs that are to be distinguished vary only on a small scale, like on the flower data set, this has to be reflected by a smaller choice of r.As expected, choosing an SVM as more sophisticated classification method makes the choice of the descriptor almost irrelevant, as all of them achieve very good results. But for an SVM, a gold standard has to be prepared and depending on the use case, this can be hard . Fortunately, even in the case of unsupervised classification FPFHs yield very good results.The evaluation on the representative sets shows a clear ranking for the SVM-based classification: FPFHs perform best, while the other descriptors all yield results similar to each other. In the case of the k-means clustering, we have on average the following ranking: FPFHs > PFHs > Spin Images > RoPS, SHOT.There are slight deviations, e.g., the Spin Images show the worst results of all descriptors on the Leaves data set, but reach almost the same quality of results as FPFHs on the Branch data set.

The same effect can be seen in the SVM results.This suggests that the resolution chosen for the Spin Images in this paper is better suited to distinguish between round and flat or cylindrical shapes than between flat and cylindrical shapes only.All in all and despite the exemplary character of the evaluation the results clearly suggest using FPFHs as descriptor of choice when compared with SHOT,RoPS and Spin Images.In applications like scan registration, both RoPS and SHOT descriptor were found to outperform PFHs and FPFHs. In contrast to that, we strive to classify the whole set of points and assign them to the corresponding plant organ.This means that the descriptor has to be able to generalize over different sizes of plant organs. Additionally, scans can not be expected to be perfect, as they have to be taken in the field and for a high number of plants. Parts of the plant can be occluded by other parts and holes in the data are possible. The descriptor has to be robust against these issues. The good performance of the FPFHs and PFHs in our application together with the worse performance of RoPS and SHOT descriptors therefore hints that FPFHs and PFHs seem to have the generality that makes them less suitable for applications where different points on a similar shaped surface have to be distinguished, but optimal for point classification in the context of precision farming.

Almost all of the pig can be used as food. There are many styles of farming: intensive commercial units, commercial free range enterprises. Although all these forms are in use today, intensive farms are the most popular due to their abilities to raise a large amount of pigs in a very cost-efficient manner. For example, only3% of UK pigs spend their entire lives outdoors .There are challenges facing in intensive pig farming. For instance, hogs in intensive farms tendto produce 23.5 piglets per year. Sow death rates have nearly doubled from 5.8%- 10.2% from 2013 to 2016 . Researchers and veterinarians are seeking ways with genetic manipulation positively impact the health of the hogs and benefit the hog business .China has the world’s largest herd and has been increasing its pig imports during its economic development. Chinese pig farming industry is growing and rapidly shifting to modernization through introducing the lean production concept and embracing the ICT .There are many efforts made for tackling the farming challenges for the increasing competition, farming cost, and guaranteeing hog health.The largest exporters of pigs are the United States, the European Union, and Canada.China’s pig farming is relatively limited in the use of new technology for a long time.

The State Council of the People’s Republic of China issued the suggestions on stabilizing pig farming and promoting its transformation and upgrading with the use of ICT, artificial intelligence and automation, and proposing to accelerate the modernization of pig farming systems in 2019 .A modern smart pig farming system should provide services for genetic manipulation, frozen sperm usage, mass production, precise feeding , remote diagnosis and treatment , daily weight gaining and cost control , performance management, talent training, smart pig farm construction,etc. For an advanced smart pig farming system, we realize that it’s better to make use of digitalization, infomatization and Internet of things to collect data on piglife cycle for pig industry. With those data to guide pig farming, a pig farm could achieve lean management with high production efficiency and quality.Realizing the challenges faced by pig farming and the opportunities given by the next generation artificial intelligence, we design an Industrial Internet Platform for Massive Pig Farming . The implementation verifies that the application of new technology such as the Industrial Internet really promotes pigfarming industry.

Some plant sources rich in compounds with antioxidant activity have been used in the feeding of layers, in the search for improved performance of birds and quality of eggs .found that the inclusion in the feed of 1% of herbs—oregano, rosemary or thyme —or 0.5% of turmeric can improve the productive performance of chickens, benefit the oxidativest ability of eggs and reduce the oxidation of yolk lipids during storage. Ginger has an antioxidant capacity that reduces oxidative stress, inhibiting carcinogenesis . Active ingredients such as tetrahydrocurcuminoids were found in turmeric, according to studies; curcumin, demethoxycurcumin,and bisdemethoxycutcumin have also been found in turmeric . Some studies have been carried out to find out the effects of curcumin on the performance of broilers and laying hens. The antioxidant effect of turmeric has already been reported in the case of broilers.

This effect is closely related to the increase of catalase, hepatic superoxide dismutase, and glutathione peroxidase enzymes . There were no significant differences in egg production and egg weight in egg quality. Contrary,indicated that egg production increased, but egg weight decreased insignificantly by addition of turmericrhizome powder to laying hen diets. According to the authors, turmeric might enhance digestive tract performance in laying hens resulting in the improvement of egg production.were able to observe that turmeric powder extract improved the production performance of Ac “Black bone” hens with better egg mass production and feed: egg conversion from 28 to 34 weeks of age and no change in egg mass.showed that turmeric powder affected egg production significantly, but not egg weight.indicated that production and mass of egg increased by addition of turmeric due to the fact that uterus media could have been improved and result in enhanced shell weight and thickness.Recent research has indicated that there are no differences in the internal quality of eggs from hens fed turmeric.However reported that albumen height and egg protein significantly increased by addition of turmeric.

According to , increase in albumen showed that active substances in turmeric powder stimulated the growth of the epithelial cells and tubulargl and cells in the magnum to synthesize and secrete albumen. At the sixth week, yolk color was lower about 4% in laying hens fed 0.5% turmeric compared with the control group. On the other hand,observed that yolk color increased significantly by the addition of 0.5% dietary turmeric powder. Dietary treatments contend 0.5% of turmeric do not significantly affect blood serum cholesterol, alanine aminotransferase,and aspartate aminotransferase levels.The intestinal mucosa is continuously growing and is affected not only by metabolic hormones, but also by other food-related factors, such as physical and chemical characteristics of nutrients and intestinal microbiot.In a study carried out to determine the effect of the herb mixture ,observed greater depth of crypts in birds that received the herb mixture composed of turmeric powder and fenugreek compared to birds that did not receive, indicating through the crypt depth the body’s attempt to recover the villus structure.

Studies with broilers have revealed that a lower vilo: crypt ratio may indicate the presence of destroyed villi and increased cell proliferation in crypts, resulting from attempts to restore damaged intestinal epithelium,in the occurrence of microbiological challenges in the intestine reported that turmeric in the feed is able to prevent intestinal colonization of inoculated bacteria, indicating that 1% turmeric is able to express its antimicrobial activities, promoting an imbalance in the population of bacteria components of the microbiot and especially against inoculated bacteria. Because of increased incretion of enzymes such as amylase,trypsin, chymotrypsin, and lipase, feed conversion ratio might be improved by turmeric-supplemented diets of laying hens . Moreover, the reason of feed intake increment might be due to turmeric special aroma.indicated that daily feed intake increased by addition of 100 and 200 mg/kg turmericrhizome extract to broilers; but daily feed intake decreased by addition of 300mg/kg. These differences are consistent with the results of and , who added 3% turmeric rhizome powder to laying hen diet. In another study ,feed intake and FCR were reduced by addition of 2% turmeric rhizome powder to laying hen diet. used turmeric powder as a food additive and found a significant increase in the percentage of edible parts, including 0.5%, 1.0% and 1.5% of turmeric powder in the diet, respectively. However, the highest percentage of cuts was 57% . The improvement in carcass weight and edible carcass weight in these experiments is attributed to the antioxidant activity of saffron, as it contains beneficial phytochemicals such as curcumin, AR-turmerones and curlone.

The technique of capacity building was employed to encourage farmers to become aware of TFT and learn how to use it. The technique results in continuous self-improvement, which is essential for farmers and their institutions in achieving a balance in economic, social, and environmental development goals.The main components of capacity building include farmer-centered development,participation of farmers, and a participatory learning forum or interactive learning .Farmer-centered development means not only improvement in farmer’s knowledge and capacity but also in their morale. TFT farmers assume a major role in decision making and managing their affairs while the GOs, NGOs and those in the private sector have supporting roles in providing guidance, comments,advice, and training. Interactive learning through “learning by doing”enhances building capacity of farmers to control their lives and businesses.

One of the most powerful techniques of improving farmer knowledge is demonstratingand convincing the farmers that they have knowledge that is useful and, if they use it correctly, they can change some of the critical factors of production.Consequently, not only the knowledge of TFT was given, but also many problems and challenges in rice production, especially issues related to seeds,insects, diseases, soil improvement, and strategic planning, were discussed and solutions found by the farmers. In 2007, Department of Agricultural Extension officially transferred TFT to farmers in the irrigated areas for rice production in Angthong, Chainat,Phra Nakhon Si Ayutthaya, and Nakhon Prathom provinces in the Central Plain.In recent years, TFT has thus been effectively disseminated through Soil Clinics in the rice producing provinces.In 2013, the first three Soil Clinics were established in Saraburi  and Suphanburi provinces in the Central Plain, and Khon Kaenprovince in the Northeast Region. This initial effort was possible with the supportof the Kyuma Fund .

In 2014, the Rotary Club of Bangkok Benjasiri supported the management team of Huay Kamin Soil Clinic to establish four Soil Clinics in Saraburi province.The leaders of those four Soil Clinics created a network named “LoomChao Phraya Pasak” to organize the TFT Service Day for farmers in their community.The results of this farmer network were 20 demonstration plots with a total area of 41 ha in Ban Lam sub-district, Wiharn Daeng district. The TFT reduced chemical fertilizer use by 51%, while the rice yield was increased 17%.During 2014-2015, National Research Council of Thailand  supported the Loom Chao Phraya Pasak Network in establishing another sixteen Soil Clinics—five Soil Clinics in Saraburi province, five Soil Clinics in Phra Nakhon SiAyutthaya province in the Central Plain, and six Soil Clinics in Chiang Rai province in the Northern Region. Every Soil Clinic organized the TFT Service Day for farmers in their community and nearby areas.In the crop year 2015, report from five farmers in each province revealed that TFT reduced chemical fertilizer use by 40% from 130 to 78 US $/ha with 14% increase in the rice yield from 4.71 to 5.38 ton/ha.

Impressively the cost of insecticides decreased79% from 95 to 20 US $/ha. Another farmer network, namely Kok IngLao Loomnamkum was created in Chiang Rai province. In 2015, the Lions Club of Bangkok Dusit supported the Loom Chao PhrayaPasak Network to establish a Soil Clinic at Nong Sai Khao sub-district, Ban Mee district, Lop Buri province in the Central Plain.In 2015, the Department of Agricultural Extension  agreed to implement the Soil Clinic concept as a national policy by supporting up to 882 Soil Clinics in every district throughout the country. The benefits of Soil Clinic have been achieved from the first year for some economic crops such as rice, maize,cassava, rubber and oil palm. DOAE reported a reduction of 26% of chemical lfertilizer use  while obtaining a remarkable 10% increase in crop yields from 2016 harvesting season.

This involved 17,640 farmers with planting area of 17,490 ha .During 2016-2017, the Rotary International, the Rotary Club of Toyohashi,Japan, and the Rotary Club of Bangkok Benjasiri supported the Loom ChaoPhraya Pasak and the Kok Ing Lao Loomnamkum Networks to organize a TFT Service Day with a total of 18 events in Saraburi, Suphanburi and Chiang Rai provinces, and in Nakhon Ratchasima province in the Northeast Region.There were about 3241 farmers with 1638 soil samples for analysis at the events.The Rachamongkol Rice Company Limited, an affiliation of Toyota Motor Thailand Corporation, supported farmer leaders in Plaeng Yao district, Chachoengsao province in the Eastern Region, and Phonsai Agricultural Cooperatives,Roiet province in the Northeast Region, to establish Soil Clinics in 2016 and 2017, respectively.

In modern conventional agriculture, increased productivity is achieved by implementing intensive crop techniques that require preliminary extractive and manufacturing activities that have a high impact on the environment. These impacts are triggered in the early stages of a farm’s productive activity when the inputs that are required are being produced and transported to the farm.The equivalent data for the organic farm describe the profile of a more environmentally friendly farming practice. Direct energy consumption on this farm was substantially lower than for any other group of rice producers in the sample. Its indirect energy consumption was more than 50% lower than its direct consumption. In contrast to conventional farms, it does not produce prior high-level environmental impacts. Its total energy consumption  was well below that of any other sub-sample , and its direct consumption was below the lowest rate of direct energy consumed by bomba rice producers .The organic farm not only consumed less energy in the final stage of agricultural production, but also in prior stages.

It is environmentally friendly in its dealings and requirements across the whole agribusiness cycle. As such, it provides a remarkable example that a sustainable, and at the same time highly profitable, farming system is feasible. However, according to results, it does not appear that a similar performance could be attained within the boundaries of conventional farming, where increased productivity requires increasing the use of chemical inputs and fossil fuels and, therefore, greater environmental damage.No economies of scope are to be found in this instance. On the contrary, there isan exponential relationship between productivity and environmental damage when we compare organic and conventional rice farms. These results are consistent with previous studies with other crops in terms of the increasing environmental damage caused by increasing the use of external inputs .GHG emissions per hectare were higher for the sub-sample of conventional farms with an above median economic performance, 7.17 and 5.61 tons of carbon dioxide per year per hectare  for gleva and bomba rice farms,respectively, than those with a lower economic performance , while they were substantially lower for the organicfarm.Therefore, our results suggest that the higher economic performance of rice farms is attained at the expense of greater air pollution.

Panel C provides data on the environmental impact needed to produce a physical unit of output and to obtain a monetary unit of income. As such, it relates the economic performance data in panel A to the environmental performance data in panel B.Overall, the data in panel C confirm previous results regarding the existence of a positive relationship between environmental performance and economic performance. While this relationship was strong with respect to energy consumption, it was weaker for GHG emissions.According to our results, the less productive gleva rice farms consumed 1.87MJ of total energy in producing one kilogram of rice, while the more productive farms required 2.03 MJ for one kilogram of output. The same increasing relationship is observed for bomba rice farms: the group of less productive farms needed 2.23 MJ, while the more upper productive required 2.77 MJ. Likewise,5.88 MJ was required to generate 1 € of income after wages in the less profitable group of gleva rice producers, while the more profitable group required 6.74 MJ.The same trend was found in conventional farms producing bomba rice .The results for GHG emissions are not conclusive. While gleva rice producers adhere to the aforementioned trend of increasing productivity resulting in a greater environmental impact: increasing emissions per kg of rice, as well as per€ of income, with increasing economic performance, the conventional bomba rice producers adhere to a declining trend: less productive farms require more emissions per kg of output , or per € of income  than their more productive counterparts .

It should perhaps be stressed that our results might be influenced by the fact that on rice farms the main emission is methane, which does not in factde pend so much on output as on the size and flooding cycles of the field. Emissionsof nitrous oxide and carbon dioxide were more closely related to productivity: high gleva economic performers released0.14 and 0.46 tCo2 per kg and per € of income after wages respectively compared to 0.10 and 0.32, respectively, in the case of low performers. The data in panel C also confirm our previous findings of panel A and B with respect to the organic farm. This farm required much less energy consumption per kilogram of output and per € of income than did their counterparts in the sample. Likewise, it produced lower field emissions than those of conventional farms per € of income . However, it produced more field emissions per kilogram of rice cropped,a fact that can be explained in terms of its lower productivity in physical units per UAA; nonetheless, it is more environmentally friendly when methane is excluded from the analysis.

The result of the study in Table 2 revealed that in operating sensor technology, the farmer needed the techniques that could enable him calculate vegetation index , drive ground-based mounted device, issue appropriate command to remote sensor, manipulate the Graphical User Interface of the sensor,monitor the crop yield, interpret data and make suggestions among others. The findings of the study were in conformity with the findings of that there is need to generate maps of the soil with its characteristics which included grid soil sampling , yield monitoring, and crop scouting. The author further found out that strategically positioned sensors collect data in the form of electronic computer databases which gives birth to the Geographic Information System for statistical analyses of data and determines variability of agricultural land with respect to its properties.

The findings of the study were also in line with the findings of that an effective method used to easily interpret remote sensing data is calculating vegetation indices.Shifting cultivation or slash-and-burn agriculture is a global agricultural practice that affects an estimated arable land area of 1500 million ha . It is the traditional method of upland rice cultivation in most parts of West Africa and in the humid and sub-humid tropics. This is a practice where a piece of forest is cleared and burnt for cultivation for a period of two to three years without fertilizer input and then leaving the land under natural fallow vegetation for a much longer period, usually greater than fifteen years, to restore soil fertility .At the onset of the cropping phase, when vegetation is burnt, almost all biomass carbon which is a potential source of soil organic carbon is lost as well as a significant amount of nutrients such as nitrogen and sulphur contained in the biomass.

During the cropping phase, inappropriate soil management practices could lead to accelerated depletion of soil organic matter and nutrients resulting in rapid depletion of soil fertility.During the fallow, the accumulation of biomass on the soil surface and its gradual decomposition does not only release nutrients but provide an energy source for the soil microbial populations and improvement of soil aggregate stability and structure, bulk density, infiltration capacity, cation exchange capacity, and soil organic matter. Also,nutrients are taken up from deeper layers by roots of trees and shrubs and returned to the top soil via litter fall and root senescence.Restoration of soil fertility by this means requires several years of fallow and has become inadequate in the face of increasing populations and food demand as well as competing alternative land uses. This has led to considerable reduction in the fallow period and the cultivation of marginal lands.In Sierra Leone, the uplands account for about 80% of the total arable land.

The bush fallow system is a very common farming practice on the uplands of Sierra Leone although it is also practiced in almost all agroeclogies. Upland rice farming system involves inter cropping rice with a variety of other crops such as cassava, maize, sorghum,sesame, pigeon pea, okra, garden egg, and other leafy vegetables. Rice normally occupies about 50% of the cropland. The limitation of this system as a sustainable farming practice is the increasing decline in the fallow period. Generally, the length of fallow period is reported to differ across the country with a mean of 8.8 years . In recent times, it is reported that the fallow period has dropped from the recommended period of ten or more years to about 5 years in rural areas and 3 – 4 years along major highways .Apart from the FAO/UNDP survey in 1979 which estimated an average fallow period of 8.8, there has been very little work done to update information on length of fallow period in different parts of the country. There is lack of information on the current extent of reduction in fallow period in different parts of the country particularly in the eastern region of Sierra Leone which is home to the remaining rainforest of the country.

The continued decline in the fallow period is a major threat to the persistence of the rain forest in the eastern region of Sierra Leone as farmers are tempted to slash-and burn the remaining forest for upland rice farming. An understanding of the extent of reduction in fallow period in the Eastern Region of Sierra Leone will throw light on the magnitude of the problem and inform policy makers and land use planners to enable them develop intervention strategies to counteract the negative impact of the practice.This study was therefore conducted to determine: 1) the extent of reduction of the fallow period in the Nongowa Chiefdom of Kenema District; 2) the causes of reduction in the fallow period; 3) farmers’ perception of the relevance of fallow period and the implications of reduction of fallow period on crop production. Sierra Leone is divided into four administrative blocks: the Provinces, the Districts, the Chiefdoms, and the Sections in decreasing sizes and administrative authority respectively.