Development of an autonomous early warning system for Bactrocera dorsalis (Hendel) outbreaks in remote fruit orchards

Developing an autonomous early warning system for detecting pest resurgence is an essential task to reduce the probabilities of massive Oriental fruit fly (Bactrocera dorsalis (Hendel)) outbreaks. By preventing pest outbreaks, farmers would be able to reduce their dependence on chemical pesticides. Chemical pesticide abuse often brings harmful consequences to human health and natural environments. Since an agroecological system can change at a fast rate due to the soil degradation and the environmental factors changes, the rise of pest density cannot be immediately detected by traditional methodologies. In this study, an autonomous early warning system, built upon the basis of wireless sensor networks and GSM networks, is presented to effectively capture long-term and up-to-the-minute natural environmental fluctuations in fruit farms. In addition, two machine learning techniques, self-organizing maps and support vector machines, are incorporated to perform adaptive learning and automatically issue a warning message to farmers and government officials via GSM networks when the population density of B. dorsalis significantly rises. The proposed system also provides sensor fault warning messages to system administrators when one or more faulty sensors give abnormal readings to the system. Then, farmers and government officials would be able to take precautionary actions in time before major pest outbreaks cause an extensive crop loss, as well as to schedule maintenance tasks to repair faulted devices. The experimental results indicate that the proposed early warning system is able to detect the incidents of possible pest outbreaks in a variety of seasonal conditions with sensitivity, specificity, accuracy, and precision around 98%, 100%, 100%, and 100%, respectively, as well as to transmit the early warning messages to farmers and government officials via Short Message Service using the GSM network. The proposed early warning system can be easily adopted in different fruit farms without extra efforts from farmers and government officials since it is built based on machine learning techniques, and the warning messages are delivered to their mobile phones as text messages. The proposed early warning system also shows great potential to assist farmers to update their pest control operations in the fruit farms, and help government officials to improve farming systems.     

应用寄生蜂和不育雄虫防控田间橘小实蝇

食品安全已成为当今社会广受关注的问题.尽管国内的一些学者就阿里山潜蝇茧蜂[Fopius arisanus(Sonan)]和橘小实蝇SIT技术分别开展了不同程度的研究,然而关于应用该蜂和不育雄虫对橘小实蝇[Bactrocera dorsalis (Hendel)]进行田间联合防治的研究还未见相关报道.为此,为探讨天敌昆虫和雄性不育技术对橘小实蝇的田间综合治理(IPM)技术,开展了阿里山潜蝇茧蜂和橘小实蝇不育雄虫的田间释放试验:首先应用性引诱剂降低田间野生雄虫数量;而后,释放橘小实蝇不育雄虫,进一步降低田间橘小实蝇种群数量;最后,释放阿里山潜蝇茧蜂对田间残余的橘小实蝇卵进行追踪寄生,以达到持续控制的目的.通过监测整个防控期田间橘小实蝇的种群数量以及果实受害率和防治效果作为评价指标评价该防治方法的综合防治效果.结果表明:应用阿里山潜蝇茧蜂、橘小实蝇不育雄虫并配合引诱剂的综合措施对橘小实蝇的种群数量有明显控制作用,田间总体防治效果可达90％左右.此外,提出完善橘小实蝇田间防控措施的建议,并提出该研究的不足以及有待进一步开展研究的方向.     

Precisely forecasting population dynamics of agricultural pests based on an interval type-2 fuzzy logic system: case study for oriental fruit flies and the tobacco cutworms

Traditional pest control approaches rely mostly on the experience of farmers, which may not be effective due to lack of scientific information regarding the environment where crops grow. Farmers can initiate a more effective integrated pest management program when precise and quantified results of forecasting pest population outbreaks are provided. Previous studies generally utilize long-term data to predict pest populations, but such a prediction approach might not be useful for farmers who grow fruit and vegetables with shorter life cycles. This paper therefore proposes an interval type-2 fuzzy logic system (IT2FLS) with short-term data to forecast the population dynamics of the oriental fruit fly (OFF, Bactrocera dorsalis (Hendel)) and the tobacco cutworm (TC, Spodoptera litura (Fabricius)). Two automatic monitoring systems are used to collect the data of the population dynamics of OFFs and TCs and the environmental parameters in farming areas. A univariate fuzzy time series forecasting model with difference-based intervals (UFTSFM_DI) and a bivariate fuzzy time series forecasting model with difference-based intervals (BFTSFM_DI) are developed, and integrated into the proposed IT2FLS. It is found that the BFTSFM_DI model yields better performances of forecasting OFF and TC populations when the atmospheric temperature data are employed. With the forecasting results, farmers will have a better understanding of the population dynamics of the OFF and TC in farming areas, so they can take proper measures, such as bagging their fruits and spraying pesticides, before pest outbreaks occur.

     

A comparison of two IPM training strategies in China: The importance of concepts of the rice ecosystem for sustainable insect pest management

Our study in China of two Integrated Pest Management (IPM) training programs for farmers shows that one is more effective than the other in reducing pesticide applications as well as in imparting to farmers an understanding of the rice ecosystem. The two training programs are based upon two different paradigms of IPM. This article uses a triangulated method of measuring concept attainment among farmer trainees in China as one measure of the effectiveness of training. Concepts of insect ecology brought about by training, as well as persistence of concepts one year after training, are measured. This information is compared to farmer data on pesticide applications and yields in order to determine the comparative effectiveness of two models of IPM farmer training in Sichuan Province. Results indicate that the Farmer Field School (FFS) model of training, based upon a new Ecology-Based IPM paradigm, is more effective than the 3 Pests 3 Diseases (3P3D) model based upon an older Economic Threshold IPM paradigm. Crop yield results and pesticide applications by farmers after training are also used to indicate which of these paradigms of insect pest control is more effective, hence scientifically accurate.     

Participatory research in integrated pest management: Lessons from the IPM CRSP

Integrated pest management has emerged as an important means of managing agricultural pests. Since the mid-1980s, the emphasis in IPM has shifted toward biologically-intensive and participatory research and extension approaches. Finding better means for solving pest problems is high on the agenda for most farmers, and farmers often have significant pest management knowledge and interest in IPM experimentation. This paper describes an approach to participatory IPM research that is being implemented by the IPM Collaborative Research Support Program (IPM CSRP). The approach emphasizes on-farm research with an extrapolation domain beyond the single farm, and in some cases beyond the local region or country. It considers many factors beyond the farm and research station that influence the generation and adoption of IPM technologies and strategies. It emphasizes linkages among farmers, scientists, consumers, bankers, marketers/processors, and policy makers in IPM research priority setting, conduct, and evaluation. The interdisciplinary approach described in the paper is illustrated with a case study from the Philippines. Lessons and conclusions draw on its recent application in other sites as well.     

Local agro-ecological knowledge and its relationship to farmers’ pest management decision making in rural Honduras

Integrated pest management (IPM) has been widely promoted in the developing world, but in many regions its adoption rates have been variable. Experience has shown that to ensure IPM adoption, the complexities of local agro-production systems and context-specific folk knowledge need to be appreciated. Our research explored the linkages between farmer knowledge, pest management decision making, and ecological attributes of subsistence maize agriculture. We report a case study from four rural communities in the highlands of southeast Honduras. Communities were typified by their agro-environments, IPM training history, and levels of infestation by a key maize pest, the fall armyworm (Spodoptera frugiperda Smith). Although variable, infestation levels generally did not justify pest management intervention. Consequently, crop losses from this pest were considered of low importance and most farmers proceeded in a rational fashion by refraining from action in their fields. Farmers attributed the low degree of pest infestation predominantly to abiotic causal factors (rainfall, temperature). The role of natural enemies in controlling this pest (i.e., biological control) was deemed of low importance by farmers; nevertheless, a broad array of such organisms was mentioned by farmers as operating in their maize crop. Farmers’ knowledge of natural enemies only partially matched scientific knowledge and was associated with the ecological features of their respective field settings. Local knowledge about natural enemies was mainly restricted to abundant and easily observable predatory species. Farmers who were knowledgeable about biological control were also familiar with a larger variety of pest management alternatives than uninformed farmers. Management options covered a wide range of curative techniques, including conservation biological control. Farmers who relied on insecticides to manage pest outbreaks knew less about biological control and pesticide alternatives. In contrast, farmers who received IPM training mentioned more types of natural enemies and were familiar with a broader range of alternative pest management tactics. Our research suggests that IPM training modifies local knowledge to better fit its environmental context. This paper provides insights in the environmental context of local agro-ecological knowledge and its linkage with pest management decision making. It also constitutes a basis for modifying IPM extension programs to deliver locality-specific technologies while strengthening the local knowledge base. Kris A. G. Wyckhuys is a Belgian bio-science engineer and entomologist currently employed as postdoctoral researcher at the University of Minnesota. For his PhD research at Purdue University he quantified social and ecological contributions to farmers’ adoption of insect pest management technologies in Honduran subsistence maize. He has a keen interest in the ecological facets of IPM and biological control, as well as in technological innovation in smallholder production systems, ethno-entomology and traditional pest management. Robert J. O’Neil is a Professor of Entomology specializing in biological control, predator–prey dynamics, and implementing biological control in IPM systems. His current work focuses on the ecology and management of the soybean aphid, Aphis glycines Matsumura, an invasive pest of soybeans in North America.     

A review of recent sensing technologies to detect invertebrates on crops

Precision agriculture needs integrated pest management (IPM), for which detection and identification of target invertebrate species is a prerequisite. Researchers have been developing various technologies to detect pests more efficiently and accurately. However, these existing sensing technologies still have limitations for effective infield applications. This review paper aims to explore the relative technologies and find a sensing method that has potential to detect and identify common invertebrates on crops, such as butterflies, locusts, snails and slugs. It was found that there are two main research branches for invertebrate detection and identification: acoustic sensing and machine vision system (MVS). Acoustic sensing is suitable for detecting and identifying pests in soil, stored grains and wood, while usually acoustic sensors need to be attached to samples for inspection, which causes difficulties for efficient infield applications. MVS has the potential to provide a more effective and flexible way to detect and identify invertebrates on crops. In recent work with MVS, the technologies of invertebrate identification have been intensively studied, however, infield detection is relatively weak. This review points out the current research gaps and then discusses the potential research directions.     

Invasion,expansion, and control of Bactrocera dorsalis (Hendel) in China

The Oriental fruit fly, Bactrocera dorsalis (Hendel), is among the most destructive fruit/vegetable-eating agricultural pests in the word, particularly in Asian countries such as China. Because of its widespread distribution, invasive ability, pest status, and economic losses to fruit and vegetable crops, this insect species is viewed as an organism warranting severe quarantine restrictions by many countries in the world. To understand the characteristics and potential for expansion of this pest, this article assembled current knowledge on the occurrence and comprehensive control of the Oriental fruit fly in China concerning the following key aspects: invasion and expansion process, biological and ecological characteristics, dynamic monitoring, chemical ecology, function of symbionts, mechanism of insecticide resistance, control index, and comprehensive control and countermeasures. Some suggestions for the further control and study of this pest are also proposed.     

Economics of autonomous equipment for arable farms

By collecting more data at a higher resolution and by creating the capacity to implement detailed crop management, autonomous crop equipment has the potential to revolutionise precision agriculture (PA), but unless farmers find autonomous equipment profitable it is unlikely to be widely adopted. The objective of this study was to identify the potential economic implications of autonomous crop equipment for arable agriculture using a grain-oilseed farm in the United Kingdom as an example. The study is possible because the Hands Free Hectare (HFH) demonstration project at Harper Adams University has produced grain with autonomous equipment since 2017. That practical experience showed the technical feasibility of autonomous grain production and provides parameters for farm-level linear programming (LP) to estimate farm management opportunities when autonomous equipment is available. The study shows that arable crop production with autonomous equipment is technically and economically feasible, allowing medium size farms to approach minimum per unit production cost levels. The ability to achieve minimum production costs at relatively modest farm size means that the pressure to “get big or get out” will diminish. Costs of production that are internationally competitive will mean reduced need for government subsidies and greater independence for farmers. The ability of autonomous equipment to achieve minimum production costs even on small, irregularly shaped fields will improve environmental performance of crop agriculture by reducing pressure to remove hedges, fell infield trees and enlarge fields.

     

Participation,empowerment, and farmer evaluations: A comparative analysis of IPM technology generation in Nicaragua

The heated debate over the limited impact of integrated pest management (IPM) in Central American agriculture suggests that we need to investigate the mechanisms of IPM technology generation. CATIE/MAG-IPM Nicaragua initiated a comparative study of two prototypic models with tomato farmers in the Sébaco Valley, in 1990–91. I created two ideal types from the literature: the scientist-led and farmer-led models. Each model was represented by three different communities. The study focused on the: 1) technology generation process, 2) IPM technologies and farmer opinion of IPM, 3) forms of participation and empowerment by farmers and scientists, and 4) institutionalization of the two models. The investigation methodology consisted of intensive pre- and post-program interviews, participant observation, and statistical analysis of experimental insect and production variables. This paper focuses on farmer participation, empowerment, and evaluation of the two models. In the farmer-led model, farmer participation was greater than in the scientist-led model in number of farmers and farm units involved. They achieved five forms of influence, and six out of eight levels of empowerment in the farmer-led model. In the scientistled model, farmers achieved two forms of influence and two out of eight levels of empowerment. Farmer evaluations were varied and complex. In general, farmers in the scientist-led model encouraged CATIE/MAG-IPM to host more meetings and expand farmer involvement. In the farmer-led model the farmers enjoyed the biological information, new technologies, and discussion. They suggested changes for future meetings.     

Timing of precision agriculture technology adoption in US cotton production

The timing of technology adoption is influenced by profitability and farmer ability to bear risk. Innovators are typically more risk tolerant than laggards. Understanding the factors influencing early adoption of precision agriculture (PA) technologies by cotton farmers is important for anticipating technology diffusion over time. The factors influencing the timing of grid soil sampling (GSS), yield monitoring (YMR) and remote sensing (RMS) adoption by cotton producers was evaluated using multivariate censored regression. Data for cotton farmers in 12 states were obtained from a survey conducted in 2009. The factors hypothesized to influence the timing of adoption included farm characteristics, operator characteristics, PA information sources, adoption of other PA technologies, and farm location. The results suggest that different factors influenced when cotton farmers adopted GSS, YMR and RMS after these technologies became commercially available. For example, land ownership was associated with the timing of GSS adoption, but not YMR or RMS adoption; farmer age was correlated with the timing of GSS and YMR adoption, but not RMS adoption; and obtaining PA information from consultants affected the timing of GSS and RMS adoption, but not YMR adoption. The only factors correlated with the early adoption of all three technologies were beliefs that PA would improve environmental quality and the adoption of at least one other PA technology. Thus, the potential for improved environmental quality appears to be a strong adoption motivator across PA technologies, as is the earlier adoption of other PA technologies. This research may be useful for farmers, researchers, Extension personnel, machinery manufacturers, PA information providers and agricultural retailers to anticipate the future adoption of new and emerging PA technologies.     

Farm and Operator Characteristics Affecting the Awareness and Adoption of Precision Agriculture Technologies in the US

Precision agriculture (PA) technologies have been commercially available since the early 1990s. However, not only has the pace of adoption in the US been relatively modest but a surprisingly large number of producers are not familiar with these technologies. Using farm level survey data, this study quantifies the role that awareness plays in the decision to adopt PA technology and allows us to explore the potential for public or private information programs to affect the diffusion of PA. PA adoption and awareness are modeled as jointly determined dichotomous variables and their determinants are estimated using a two-stage (i.e. instrumental variable) logistic specification. The first-stage logit model indicated that operator education and computer literacy, full-time farming, and farm size positively affected the probability of PA awareness while the effect of age was negative. Grain and oilseed farms (i.e. corn, soybean, and small grains) and specialty crop farms (i.e. fruits, vegetables, and nuts) as well as farms located in the Heartland and Northern Great Plains regions were most likely to be aware of PA technologies. The second-stage PA adoption logit model, which included an instrumental variable to account for the endogeneity of awareness, revealed that farm size, full-time farming, and computer literacy positively influenced the likelihood of PA adoption. Grain and oilseed farms were the most likely types of farms to adopt PA as were farms in the Heartland region. Awareness, as defined in this study, was not found to be limiting the adoption of PA, suggesting that farmers for whom the technology is profitable are already aware of the technology and that a sector-wide public or private initiative to disseminate PA information would not likely have a major impact on PA diffusion.     

Can public GAP standards reduce agricultural pesticide use? The case of fruit and vegetable farming in northern Thailand

In response to the chronic overuse and misuse of pesticides in agriculture, governments in Southeast Asia have sought to improve food safety by introducing public standards of good agricultural practices (GAP). Using quantitative farm-level data from an intensive horticultural production system in northern Thailand, we test if fruit and vegetable producers who follow the public GAP standard use fewer and less hazardous pesticides than producers who do not adhere to the standard. The results show that this is not the case. By drawing on qualitative data from expert interviews and an action research project with local litchi (“lychee”) producers we explain the underlying reasons for the absence of significant differences. The qualitative evidence points at poor implementation of farm auditing related to a program expansion that was too rapid, at a lack of understanding among farmers about the logic of the control points in the standard, and at a lack of alternatives given to farmers to manage their pest problems. We argue that by focusing on the testing of farm produce for pesticide residues, the public GAP program is paying too much attention to the consequences rather than the root cause of the pesticide problem; it needs to balance this by making a greater effort to change on-farm practices.     

Farm to school programs: exploring the role of regionally-based food distributors in alternative agrifood networks

Farm to school programs are at the vanguard of efforts to create an alternative agrifood system in the United States. Regionally-based, mid-tier food distributors may play an important role in harnessing the potential of farm to school programs to create viable market opportunities for small- and mid-size family farmers, while bringing more locally grown fresh food to school cafeterias. This paper focuses on the perspectives of food distributors. Our findings suggest that the food distributors profiled have the potential to help institutionalize farm to school programs. Notably, their relationships with farmers may be a critical element in expanding the scale and scope of local school food procurement. Their ability to catalyze local school food procurement however, is limited by the structural context in which farm to school programs operate. Specifically, the oppositional school year and agriculture production cycle, and tight food service budget constraints disembed and limit the potential of farm to school programs to decrease the “marketness” of school food procurement and to shift it from a process based largely on price to one that is more territorially embedded. As farm to school programs continue to gain support, regionally-based food distributors that have the meaningful relationships necessary to re-embed the school food service market back into the larger society may be critical to enabling advocates to achieve their goals.     

Do farmers care about climate change? Evidence from five major grain producing areas of China

Using a logistic model, this paper empirically investigated farmers' perception of climate change and its determinants based on a field survey of 1 350 rural households across five major grain producing provinces in China. The results show: i) There is an apparent difference in perception levels for long-term temperature and precipitation changes. Specifically, 57.4% of farmers perceived the long-term temperature change correctly, but only 29.7% of farmers perceived the long-term precipitation change correctly; ii) The factors influencing the farmers' perceptions are almost completely different between precipitation and temperature, the former are mostly agriculture related, while latter are mostly non-agriculture related, except for farm size; and iii) Farmers are not expected to pay more attention to long-term precipitation changes over the crop growing seasons, because less than 30% of farmers can correctly perceive long-term precipitation change. Therefore, to improve the accuracy of farmers' perceptions of climate change, the government is recommended to: i) enhance education and training programs; ii) speed up land transfer and expand household land farm size; iii) develop farmer cooperative organizations; iv) invest more in agricultural infrastructure, specifically in major grain producing regions; and v) improve the agricultural environment and increase farming income.     

我国实施IPM的影响因素及对策

在分析影响我国有害生物综合治理(Integrated pest management,IPM)实施的各种问题,如农户对IPM技术的需求、IPM推广服务体系、IPM应用基础理论及技术研究、农药市场和社会环境等问题的基础上,提出了相应的对策.认为IPM不仅是一个应用生物学、生态学问题,其实施过程涉及社会各相关领域,为了全面推进IPM在生产中的应用,必须进一步加强IPM应用基础理论的研究,开发符合IPM要求的新技术,完善推广服务体系,加强农药生产、销售与使用的管理,创造有利于IPM实施的社会环境等.     

What determines irrigation efficiency when farmers face extreme weather events? A field survey of the major wheat producing regions in China

Water availability is a major constraint on grain production in China, therefore, improving irrigation efficiency is particularly important when agriculture faces extreme weather events. This paper first calculates irrigation efficiency with a translog stochastic frontier production function and then investigates what happens when extreme weather events occur via a Tobit model. The estimated results reveal several important features of irrigation practices: i) irrigation efficiency is lower when extreme weather events occur; ii) large variations in irrigation efficiency occur across irrigation facilities; iii) the farm plots exhibit an extreme distribution across efficiency levels; and iv) water-saving techniques, technology adoption, and the maintenance of farmers’ economic resilience are major determinants of irrigation efficiency. Based on these results we propose the following recommendations: i) farmers should balance crop yield and water use; undertake relevant training programs and adopt water-saving techniques; ii) local governments and researchers should help farmers to find the optimal level of irrigation water use based on their own circumstances and provide better water-saving techniques and training programs rather than simply encouraging farmers to invest in irrigation facilities in the most extreme weather years; and iii) the income level of farm households should be increased so as to improve their resilience to natural disasters.     

Motivations behind farmers’ pesticide use in Bangladesh rice farming

This paper addresses the motivations behind farmers’ pesticide use in two regions of Bangladesh. The paper considers farmers’ knowledge of arthropods and their perceptions about pests and pest damage, and identifies why many farmers do not use recommended pest management practices. We propose that using the novel approach of classifying farmers according to their motivations and constraints rather than observed pesticide use can improve training approaches and increase farmers’ uptake and retention of more appropriate integrated pest management technologies. Elizabeth J. Z. Robinson divides her time between Tanzania and the UK and is a research associate with the Centre for the Study of African Economies at the University of Oxford in the UK. She is an economist specializing in agriculture, natural resources, and the environment. She has over ten years of experience undertaking applied research in South Asia and sub-Saharan Africa as a fellow and lecturer in the Economics Department at the University of Oxford; at the Natural Resources Institute at the University of Greenwich in the UK; and with the World Bank and Rockefeller Foundation in the US. Sumona Rani Das is an agriculture economist who has been working for eight years with a non-government organization in Bangladesh named PROSHIKA. She is involved with monitoring and evaluation of PROSHIKA’s ongoing activities in agriculture, and is working as a team leader with an agriculture network to promote sustainable agriculture. She has special responsibility for motivation, training, project management, and documentation of different programs. Tim B. C. Chancellor is a crop protection specialist and currently is the leader of the Natural Resources Institute’s Plant, Animal and Human Health Group at the University of Greenwich in the UK. He has 17 years research and consultancy experience in vector ecology and in pest and disease management. Other skills include project management, monitoring and evaluation, and public-private partnerships. He is also Adviser to the UK government’s Department for International Development (DFID) Crop Protection Programme. His commodity experience includes rice, banana, groundnut and vegetables.     

Resilience and vulnerability in US farm policy: parsing the payment limitation debate

Since the New Deal era, the commodity title has been the major farm support program in US farm bills. Commodity programs have encouraged farmers to pursue specialized, monocultural, and input intensive production strategies that are increasingly viewed as unsustainable. Yet commodity programs remain politically resilient. As revealed in the farm payment limitation debate in the 2007 farm bill reauthorization process, political support for commodity programs is maintained through policy elasticity adaptations that combine new with old policy rationales. The recent extension of farm program support to producers of commodities that have not received benefits in the past poses a potential threat to existing commodity programs, as this legislation has institutionalized competition within production agriculture over the allocation and design of subsidies. This paper argues for renewed attention to the policy support mechanisms that undergird the conventional agrifood system in order to better understand alternative agrifood system possibilities and constraints.