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Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

The purpose of this paper is to investigate the determinants and impacts of outsourcing pest and disease management on rice production in China.

A multinomial endogenous treatment effects model which accounts for selection bias was used.

The results show that outsourcing decisions are driven mainly by the size of the farm, the age of the household head and other household characteristics. Further, the authors find that outsourcing labor for pest and disease control has no significant effect on pest control cost and rice yields, though it reduces the number of pesticide applications. Conversely, outsourcing of professional services can increase rice yields by 4.1 percent, and at the same time it increases pest and disease control costs by 50.6 percent. However, it is found that outsourcing of professional services exerts no significant impact on the farm profitability.

This study suggests that households with large farm size are more likely to outsource professional services and, therefore, service providers and governments should target those farmers to provide incentives and create greater awareness of the benefits from the outsourcing of professional services. Moreover, the increase in yields along with the government subsidy justifies the outsourcing of professional services by farmers. However, service providers and policy makers have a lot of leeway to come up with cheaper methods for pest and disease management in rice production.

This study is the first attempt to simultaneously evaluate the determinants and impacts of outsourcing pest and disease management on rice production in China.

To review the literatures, and to consider the latest results regarding the formation of tin pest in lead‐free solders and interconnections.

Previous work, over almost a century, on tin pest formation in tin and its alloy has been critically analysed. Samples of the new generation of lead‐free solders, which have experienced long term storage at −18 and −40°C, have been examined.

Tin pest has been observed in bulk samples of tin −0.5 (wt%) copper solder after exposure at −18°C although not at −40°C. Other lead‐free alloys (Sn‐3.5Ag, Sn‐3.8Cu‐0.7Cu and Sn‐Zn‐Bi) have been immune to date. Large‐scale model joints exhibit tin pest but actual joints may be resistant due to the limited free solder surface available and the constraint of intermetallic compounds and components.

The possibility of tin pest formation in joints remains. It seems that impurities are essential protection against it, but for long term applications there is no certainty that tin pest and joint deterioration will never occur.

The paper considers the various factors that may affect tin pest formation and demonstrates its existence in one of the more popular new lead‐free alloys.

This study aims to identify the most relevant causal factors and the feedback loops of the dynamics between Tuta absoluta incidence in tomato crops and farmers' reactions to the problem. The authors seek to develop a conceptual model based on farmers' know-how to address crop damage by T. absoluta at a local and regional levels in order to determine how to confront this problem in the tomato-growing region of Sáchica, Colombia.

Community-Based System Dynamics (CBSD) is a participatory research methodology in which a group of stakeholders identifies relevant variables and the cause-effect relations among them which are then arranged into a causal loop diagram. The authors implemented this methodology in a workshop, focused on the farmers' insights related to the pest situation at the local and regional level, to achieve a causal loop diagram that explained pest dynamics and their potential management.

The relevant factors for the presence of T. absoluta, seen in the causal loop diagram, vary regionally and locally. At the local level, the pest impacts tomato production, farmers' well-being and their cash flow, while at the regional level, it affects market dynamics and environment and promotes regional coordination among farmers. Farmers propose product innocuity as a key regional objective. They also proposed establishing a planting calendar and census of greenhouses to control the pest throughout the region and the tomato supply.

First, the synthesized model could not be validated with the farmers due to the COVID 19 epidemic. However, the authors held sessions with experts to analyze each result. Second, decision-makers from the local government did not participate in the workshop. Nevertheless, the approach of the workshop was aimed at understanding the mental models of the farmers since they are the ones who decide how pests are managed. Finally, even though farmers showed interest in projects aimed at proposing area-wide, long-term and wide pest control strategies, there is a risk that they will not adopt the proposed changes, due to risk aversion.

CBSD has not been applied to agricultural systems to analyze impacts from pests at the local and regional levels. The results of this study contribute to designing future interventions for pest control in the region, along with the factors which may turn out to be “side effects” or unwanted results. To design pest control interventions at a regional level, a sound understanding of the variables or factors that control the system dynamics at various levels is required. This study represents the first step towards that end.

The purpose of this study is to develop a testing method for tin pest in tin – copper (SnCu) alloys. Tin pest is the allotropic transformation of white β-tin (body-centered tetragonal structure) into gray α-tin (diamond cubic structure) at temperatures < 13.2°C.

Bulk samples of Sn99Cu1 weight per cent (purity, 99.9 weight per cent) were cast in the form of roller-shaped ingots with a diameter of 1.0 cm and a height of 0.7 cm. The samples were then divided into four groups. The first group included samples artificially inoculated with α-tin powder. The second group was inoculated in the same way as the samples from the first group but additionally subjected to mechanical pressing. The third group of ingots was only subjected to mechanical pressing. The fourth group of samples consisted of as-received roller-shaped ingots.All samples were divided into two groups and kept either at −18°C or at −30°C for the low-temperature storage test. For tin pest identification, a visual inspection was made, using a Hirox digital microscope over 156 days at intervals not longer than 14 days. The plot of the transformation rate, presented as the average increase in the area of α-tin warts in time, was also determined. To demonstrate the differences between regions of β- and α-tin, scanning ion microscopy observations using the focused ion beam technique was performed.

The first symptoms of tin pest were observed for the inoculated, mechanically pressed samples stored at −18°C, as well as those at −30°C, after less than 14 days. In the first stage of transformation, the rate was higher at −30°C for some time but, after about 75 days of storage at sub-zero temperatures, the rate at −30°C became lower compared to the rate at −18°C. Inoculation via the application of substances which are structurally similar to α-tin was efficient for the proposed new approach of rapid testing only when applied with simultaneous mechanical pressing. Infection from pressed-in seeds, leading to conventional seeded growth, was more rapid than infection in contact with seeds (without mechanical pressing), where the transition mechanism was induced by the epitaxial growth of metastable ice.

The new rapid method for the diagnostic testing of the susceptibility of different SnCu alloys to tin pest in a period much shorter than 14 days (within single days for storage at −30°C) is proposed and described. The test procedure described in this paper produced results several times quicker than conventional procedures, which may take years. In effect, the behavior of tin alloys in the face of tin pest may be predicted much more easily and much earlier. The same procedure can be applied to other SnCu alloys used in electronics (and in other areas), if the test samples are prepared in a similar manner.

The purpose of this paper is to investigate tin pest formation in lead‐free alloys.

Samples of Sn99.5Ag3.0Cu0.5, Sn99Cu1 and Sn98Cu2 alloys were prepared in four different forms. The first group was prepared using traditional PCB technology and a hand soldering method. The next group of samples was composed of as‐received ingots of these alloys. To check the impact of mechanical treatment on the transformation process, additional cold‐worked and cold‐rolled samples were prepared (30 kN). All samples were placed initially either at −18°C or at −65°C for low temperature storage testing. Visual observations, scanning electron microscopy observations and X‐ray diffraction analysis were performed to identify the transformation process. Additional samples were prepared using a force of 75 kN and placed in a chamber at a temperature of −30°C for long‐term testing.

The detectable symptoms of tin pest in samples subjected to mechanical processing with 1 and 2 wt.% of Cu addition stored at −18°C were observed at the edges of the samples after 17 months of storage. Further aging at −18°C showed the progress of α/β transformation with time under low‐temperature stress, but only in these specimens. With the application of greater force to the pressing process (75 kN instead of 30 kN) and at a temperature of storage close to the maximal transformation rate (−30°C), there was a significant acceleration of the α/β transformation, and this dependence can be used in predicting the risk of tin pest occurrence in various lead‐free alloys.

The paper shows that the degree of mechanical processing had a great influence on the α/β transformation rate. Based on these observations, it is proposed that such mechanically processed samples can be used for accelerated testing of tin‐rich lead‐free alloys at low temperatures. Such tests would be appropriate for a practical estimation of the tin pest risk when the design life of some electronic equipment ranges from 15 to 25 years.

Using the remarkable olfaction ability, insects can sense trace amounts of host plant volatiles that are notorious for causing severe damage to fruits and vegetables and in consequence the industry. The purpose of the paper is to investigate the interactions between olfactory proteins, odorant-binding proteins (OBPs) and host plant volatiles through the developed olfactory biosensors. It might be helpful to develop novel pest control strategies.

Using the successfully expressed and purified OBPs of the oriental fruit fly Bactrocera dorsalis, a biosensor was developed by immobilizing the proteins on interdigitated electrodes through nitrocellulose membrane. Based on electrochemical impedance sensing, benzaldehyde emitted by the host plants, such as Beta vulgaris, was detected, which could be used to investigate and analyze the mechanisms of pests’ sense of chemical signals. The relative decreases of charge transfer resistances of the sensor were proportional to the odorant concentrations from 10⁻⁷ M to 10⁻³ M. Meanwhile, the interactions between OBPs and benzaldehyde were studied through the process of molecular docking.

The paper provides a pest OBPs-based biosensor that could sensitively detect the host odorants benzaldehyde. Meanwhile, the most related amino acids of OBPs that bind to host plant volatiles can be distinguished with molecular docking.

An olfactory biosensor was developed to explore interactions and mechanism between the pest OBPs and benzaldehyde, which showed promising potentials for small organic molecule sensing. Simultaneously, it might be helpful for novel pest control strategies.

The purpose of this paper is to describe the effects of mechanical testing and thermal treatment prior to storage at either −18 or −40°C, for periods in excess of ten years on the Sn‐37Pb alloy.

For over a decade, The Solder Research Group at The Open University has studied tin pest development in several of the new lead‐free solders. Bulk samples, employed for mechanical testing, are laid down at −18 and −40°C, and inspected periodically.

In a previous examination in 2006, there was no evidence of tin pest formation in this alloy. On re‐examination of the same specimens in 2008, about one in ten of the samples stored at −18°C, both “as cast” and “tested”, exhibited warts of tin pest. Storage at −40°C increased this ratio to about one in three following treatment.

The paper's findings demonstrate that, even with high concentrations of lead present, eventually tin pest will form. So, for interconnections used in long‐term applications, whether lead‐free or lead‐bearing solders are employed, performance and structural integrity considerations should not ignore tin pest.

The purpose of this paper is to analyse factors affecting the use of pesticides in intensive vegetable farming in Java, Indonesia. Evaluating such factors is expected to provide appropriate policies to reduce pesticides, and eventually, mitigates the adverse impacts of pesticides on human health and the environment.

Data were compiled from a farm survey of randomly selected 240 vegetable farmers in three regions of Java in 2014. A concept of economic threshold was employed to analyse the pesticide use determinants, which were estimated using econometric models.

Factors leading to the increase in the application of pesticides were the number of observed insect pests, prices of vegetables, use of local varieties, and use of mixed pesticides. Conversely, factors lowering the use of pesticides were the number of observed diseases, the cost of pesticides, and area planted to vegetables. The most important factor in influencing pesticide use was farmers’ perception on the correct prediction of yield losses associated with pests and diseases.

The sample for this research is somewhat low and the analysis was based on one-year data of the quantity of pesticides in a formulation.

The use of pesticides can be reduced by training farmers on crop protection practices, which provide correct information on pests and diseases. Policies related to the price of pesticides would be ineffective, as farmers still highly relied on pesticides. These findings will be useful for reducing the use of pesticides in intensive vegetable farming in Indonesia, and in tropical countries in general.

Pesticides have two opposite properties: to increase income on the one side and to cause devastation of life on the other side. Because pesticides are generally less selectively toxic than would be desired, non-targets including humans and the environment must be protected from contamination by these agrochemicals. This study found the most important determinants for reducing pesticide exposures in Indonesian intensive farming.

Malnutrition is widespread and affects about one-third of humanity. Increasing production and consumption of vegetables is an obvious pathway to improve dietary diversity, nutrition and health. This chapter analyses how climate change is affecting vegetable production, with a special focus on the spread of insect pests and diseases. A thorough literature review was undertaken to assess current global vegetable production, the factors that affect the spread of diseases and insect pests, the implications caused by climate change, and how some of these constraints can be overcome. This study found that climate change combined with globalization, increased human mobility, and pathogen and vector evolution has increased the spread of invasive plant pathogens and other species with high fertility and dispersal. The ability to transfer genes from wild relatives into cultivated elite varieties accelerates the development of novel vegetable varieties. World Vegetable Center breeders have embarked on breeding for multiple disease resistance against a few important pathogens of global relevance and with large evolutionary potential, such as chili anthracnose and tomato bacterial wilt. The practical implications of this are that agronomic practices that enhance microbial diversity may suppress emerging plant pathogens through biological control. Grafting can effectively control soil-borne diseases and overcome abiotic stress. Biopesticides and natural enemies either alone or in combination can play a significant role in sustainable pathogen and insect pest management in vegetable production system. This chapter highlights the importance of integrated disease and pest management and the use of diverse production systems for enhanced resilience and sustainability of highly vulnerable, uniform cropping systems.