This dissertation develops biosensors for rapid detection of pathogens for environmental monitoring and food safety applications and utilizes the multidisciplinary and multi-application characteristics of biosensors to develop a lesson plan that can be implemented in secondary education classrooms. The detection methods evolve from particle immunoagglutination assay, PDMS optofluidic lab-on-a-chip, and spectrum analysis to smartphone and image analysis without any reagent; the potential application in secondary education also underlines the extended value of biosensors. In the first paper presented here, an optofluidic lab-on-a-chip system and subsequent sampling procedure were developed for detecting bacteria from soil samples utilizing Mie scattering detection of particle immunoagglutination assay. This system and protocol detected the presence of Escherichia coli K12 from soil particles in near real-time (10 min) with a detection limit down to 1 CFU mL⁻¹ and has the potential to be implemented in the field. We also compared the interaction between E. coli and soil particles to the two-step protein-surface interaction. In the second paper, a smartphone-utilized biosensor consisting of a near-infrared (NIR) LED (wavelength of 880 nm) and a digital camera of a smartphone was developed for detecting microbial spoilage on ground beef, without using any reagents. The method was further improved by programming a smartphone application that allows the user to position the smartphone at an optimum distance and a range of angles utilizing its internal gyro sensor to measure a series of scatter intensities against the detection angle. This handheld device can be used as a preliminary screening tool to monitor microbial contamination on meat products. In the third paper, we designed a lesson plan for secondary education classrooms using biosensors as a core and branching out to different applications and fields of study with the goal of heightening students' interest and motivation toward attaining degrees and careers in STEM fields. Results revealed that the lesson was more effective in affecting younger students than older students, and more effective in teaching about the applications of biosensors than about the techniques of biosensor development.

Metagenomics is the study of a collective microbial genetic content recovered directly from natural (e.g., soil, ocean, and freshwater) or host-associated (e.g., human gut, skin, and oral) environmental communities that contain microorganisms, i.e., microbiomes. The rapid technological developments in next generation sequencing (NGS) technologies, enabling to sequence tens or hundreds of millions of short DNA fragments (or reads) in a single run, facilitates the studies of multiple microorganisms lived in environmental communities. Metagenomics, a relatively new but fast growing field, allows us to understand the diversity of microbes, their functions, cooperation, and evolution in a particular ecosystem. Also, it assists us to identify significantly different metabolic potentials in different environments. Particularly, metagenomic analysis on the basis of functional features (e.g., pathways, subsystems, functional roles) enables to contribute the genomic contents of microbes to human health and leads us to understand how the microbes affect human health by analyzing a metagenomic data corresponding to two or multiple populations with different clinical phenotypes (e.g., diseased and healthy, or different treatments). Currently, metagenomic analysis has substantial impact not only on genetic and environmental areas, but also on clinical applications. In our study, we focus on the development of computational and statistical methods for functional metagnomic analysis of sequencing data that is obtained from various environmental microbial samples/communities.

Protozoa and bacteria can easily cause disease in humans, specifically E. coli, Plasmodium falciparum, and Cryptosporidium parvum. These three pathogens are associated with large public health concerns that span the globe. The variety of locations in which these can be found is extremely high. Cryptosporidium spp. are extremely resilient when in oocyst form, P. falciparum is in the Anopheles spp. mosquito, while E. coli can be found on anything from food and water, to the skin and gut. The diverse range of locations these can be found in means that a portable sensor for their detection is necessary. In detecting Cryptosporidium, microscopy is the preferred method of identification currently. This requires a trained lab technician as well as calibrated and expensive optical equipment. Technician error can lead to false negative or positive diagnoses as well as sample destruction. A method to remove this technician interaction is thus necessary. This method must allow for objective results that are not open to interpretation. Particle immunoagglutination assays with Mie scatter allow for such an approach using inexpensive components. Particle immunoagglutination relies on the principles of antibody-antigen interaction and antibody conjugated latex particles. Using highly carboxylated latex particles, it is possible to attach IgG antibodies that are specific to a target antigen. Mie scatter is governed by particle size rather than wavelength as other forms of scatter. These two combined allow for an increase in light scatter based on particle size. This is correlated in a linear manner as long as the number of antibody-conjugated particles is higher than the number of antigens. Microfluidics is an ever growing field in the field of lab-on-a-chip that works very well with particle immunoagglutination. In this paper, a method to rapidly identify the presence of Cryptosporidium using microfluidics and particle immunoagglutination is discussed and analyzed. This method allows for a low detection limit of 1-10 oocysts/sample and an assay time of approximately 10 minutes. Results are displayed on a computer screen as the value of light scatter intensity and, when compared to a standard curve, is an objective way to identify the concentration and presence of oocysts in a diverse range of samples. These samples include PBS, pool water, and sump water. This system also works with P. falciparum, which causes malaria in rural and urban poor regions of the world. With the low income and remote nature of these locations, a portable microfluidic device is necessary. Smartphones allow for a portable microfluidic device that can detect P. falciparum antigens in 10% whole blood. This system is capable of detecting as little as 1 pg/mL antigen. The microfluidic chip is inexpensive and disposable, allowing for a portable and inexpensive system. Using a single smartphone, a lab technique requiring a spectrometer, light source, and laptop can be made portable and less expensive, while maintaining sensitivity and specificity. In order to identify biological agents, there are commonly 3 methods for doing so: PCR, culturing, and ELISA. Culturing can take more than 24 hours, but results in a high signal to initial target ratio, while ELISA has poor sensitivity due to a 1:1 signal to target ratio, though is much quicker than culturing at usually 3 hours or less. PCR manages to solve both these problems by exponentially increasing the number of copies of target genetic material in a relatively short time frame of 1-3 hours. PCR relies on 4 basic components: target genetic material, primers to set a start and end location for duplication, polymerase to add base pairs to the strand beginning at the primers, and heat. PCR has worked very well during the past 31 years. It has worked so well that it is often the gold standard. However, there are flaws built into today's systems. These largely come in the form of inefficient heat transfer via conduction and large sample volumes due to unnecessary additions of nuclease free water (NFW). Both of these can be easily overcome by droplet PCR. Droplet PCR relies on small sample volumes of between 8 and 12 μL and convection in oil rather than conduction through plastic. In this study, it was found that droplet PCR could be performed on genomic E. coli DNA in as little as 15 minutes for 30 cycles. Sensitivity was also analyzed and found to be 2.62 pg DNA/μL or about 5 x 10² cfu/sample. PCR has a theoretical lower limit of 1 copy of genetic material and this is only 2 orders of magnitude above that. The system was also tested for portability and resistance to shock and vibration. It was found that the surface heated, thermocouple guided system is more shock and vibration resistant than standard wire guided, hanging droplet PCR systems. It was also found that the use of coconut oil allows for the system to be transported without fear of the contents spilling out and contaminating other samples. This is because of coconut oil's high melting temperature.

The utilization of lignocellulosic residues to produce renewable energy is an interesting alternative to meet the increasing demand of fuels while at the same time reducing greenhouse gas emissions and climate change. Sweet sorghum bagasse is a lignocellulosic residue composed mainly of cellulose, hemicellulose, and lignin; and it is a promising substrate for ethanol production because its complex carbohydrates may be hydrolyzed and converted into simple sugars, and then fermented into ethanol. However, the utilization of lignocellulosic residues is difficult and inefficient. Lignocellulose is a very stable and compact complex structure, which is linked by β-1,4 and β-1,3 glycosidic bonds. Furthermore, the crystalline and amorphous features of cellulose fibers and the presence of hemicellulose and lignin make the conversion of lignocellulose into fermentable sugars currently impractical at commercial scale. The bioconversion of lignocellulose in nature is performed by microorganisms such as fungi and bacteria, which produce enzymes that are able to degrade lignocellulose. The present study evaluated the bioconversion of lignocellulosic residues of sweet sorghum into simple sugars using filamentous fungi directly in the hydrolysis of the substrate, without prior isolation of the enzymes. The fungus Neurospora crassa and some wild fungi (that grew naturally on sweet sorghum bagasse) were used in this investigation. The effect of the fungi on substrate degradation and the sugars released after hydrolysis were evaluated, and then compared with standard hydrolysis performed by commercial enzymes (isolated cellulases). In addition, different combinations of fungi and enzymes were used to determine the best approach. The main goal was to verify if the fungi were able to attack and break down the lignocellulose structure directly and at a reasonable rate, rather than by the current method utilizing isolated enzymes. The main finding of this study was that the fungi (N. crassa and wild fungi) were able to degrade sweet sorghum bagasse directly; however, in all of the cases, the hydrolysis process was not efficient because the hydrolysis rate was much lower than the enzymatic hydrolysis rate. Hydrolysis using a combination of fungus and commercial enzymes was a good approach, but still not efficient enough for practical use. The best results of combined hydrolysis were obtained when the substrate was under the fungus attack for three days and then, commercial enzymes with low enzymatic activity (7 FPU/g and 25 CBU/g) were added to the solution. These enzymes represent 10% of the current enzymatic activity recommended per gram of substrate. This process reached reasonable levels of sugars (close to 85% of sugars yield obtained by enzymatic hydrolysis); however, the conversion rate was still slower, making the process impractical and more expensive since it took twice the amount of time as commercial enzymes. Furthermore, the wild fungi able to degrade cellulose were isolated, screened, and identified. Two of them belong to the genus Aspergillus, one to the genus Acremonium, and one to the genus Rhizopus. Small concentration of spores-0.5mL- (see Table 4, CHAPTER III- for specific number of spores per mL) did not show any sugar released during hydrolysis of sweet sorghum bagasse. However, when the concentration of spores was increased (to 5mL and 10mL of solution), citric acid production was detected. This finding indicates that those wild fungi were able to degrade lignocellulose, even though no simple sugars were measured, citric acid production is an indicator of fungi growing and utilization of lignocellulose as nutrient. It is assumed that the fungi consume the sugars at the same time they are released, thus they are not detected. The maximum concentration of citric acid (~14.50 mg/mL) was achieved between days 8-11 of hydrolysis. On the other hand, before using lignocellulose, the substrate needed to be pretreated in order to facilitate its decomposition and subsequent hydrolysis. Sweet sorghum bagasse was washed three times to remove any soluble sugars remaining after the juice was extracted from the stalks. Then, another finding of this study was that the first wash solution could be used for ethanol production since the amount of sugars present in it was close to 13°Brix. The ethanol yield after 48 hours of fermentation was in average 6.82mg/mL, which is close to the theoretical ethanol yield. The other two washes were too dilute for commercial ethanol production. In terms of pretreatments, the best one to break down sweet sorghum bagasse was 2% (w/v) NaOH. This pretreatment shows the highest amounts of glucose and xylose released after hydrolysis. Unwashed and untreated bagasse (raw bagasse) did not show any sugar released. In terms of ethanol, 74.50% of the theoretical yield was reached by enzymatic hydrolysis, while 1.10% was reached by hydrolysis using the fungus N. crassa. Finally, it is important to remark that further investigation is needed to improve the direct conversion of lignocellulose into fermentable sugars by fungal enzymes. This approach is a promising technology that needs to be developed and improved to make it efficient and feasible at commercial scale.

High-pressure fog (HPF) systems have advantages for greenhouse cooling compared to traditional systems, such as pad and fan. Such advantages include the potential of improving climate uniformity. Water is distributed throughout the greenhouse space thus reducing water use and energy operation costs, especially if used within naturally ventilated greenhouses. Fog cooling in combination with natural ventilation is difficult to manage, primarily because accurate estimation of air exchange rates is required to determine the precise amount of fog required. This limitation on automated control has been the main reason restricting the widespread commercial use of HPF systems. The goal of this research was to develop and implement a control strategy for a naturally ventilated greenhouse with a variable HPF system. The strategy that was developed included variable rate of fog introduced into the greenhouse, a dynamic control of the air ventilation openings, and it considered the contribution of cooling and humidification from the crop by evapotranspiration. Three evapotranspiration models, including Penman-Monteith, Stanghellini and Takakura, were calibrated and evaluated in terms of prediction accuracy. The Stanghellini model provided the best overall performance for several growing seasons and under two different evaporative cooling systems (i.e. pad and fan and natural ventilation with HPF), and was selected and implemented in the cooling control strategy. The strategy utilized enthalpy and vapor pressure deficit (VPD) of the greenhouse atmosphere for the control parameters. Using a calibrated greenhouse mechanistic climate model, a computer algorithm was created to simulate the capabilities of the proposed. The control strategy that was developed was able to maintain the greenhouse climate closer to the pre-established set points while consuming less water and energy, compared to a constant HPF system based on VPD control. Finally, the strategy was implemented in a single span research greenhouse. A four-day validation study provided good agreement for measured and simulated greenhouse climate values, as well as for water and energy use. Moreover, the strategy was able to maintain VPD around its set point for all the experiments and temperature remained around its set point when outside enthalpy was lower than the enthalpy set point.

A multi-wavelength laser diode based optical sensor was designed, developed and evaluated for monitoring and control microalgae growth in real-time. The sensor measures optical density of microalgae suspension at three wavelengths: 650 nm, 685 nm and 780 nm, which are commonly used for estimating microalgae biomass concentration and chlorophyll content. The sensor showed capability of measuring cell concentration up to 1.05 g L⁻¹ without sample dilution or preparation. The performance of the sensor was evaluated using both indoor photobioreactors and outdoor paddle wheel reactors. It was shown that the sensor was capable of monitoring the dynamics of the microalgae culture in real-time with high accuracy and durability. Specific growth rate (μ) and ratios of optical densities (OD ratios) at different wavelengths were calculated and were used as good indicators of the health of microalgae culture. A series of experiments was conducted to evaluate the sensor's capability of detecting environmental disturbances in microalgae systems, for instance, induced by dust or Vampirovibrio chlorellavorus, a bacteria found to cause crash of microalgae culture. Optical densities measured from the sensor were insensitive to the amount of dust that consisted of 59.7% of dry weight of microalgae in the system. However, the sensor was able to detect multiple events of introduction of dust timely by μ and OD ratios. The sensor was also capable of detecting subtle changes of culture in color that leads to a total crash of the culture before it can be differentiated by naked eye. The sensor was further integrated into an existing outdoor raceway to demonstrate the sensor's potential of being a core component to control microalgae production system. A real-time monitoring and control program along with a graphical user interface (GUI) was developed for a central control station aiming at improving resource use efficiency for biomass production.

The burdensome capital cost of urban water distribution systems demands the use of efficient optimization methods capable of finding a relatively inexpensive design that guarantees a minimum functionality under all conditions of operation. The combinatorial and nonlinear nature of the optimization problem involved accepts no definitive method of solution. Adaptive search methods are well fitted for this type of problem (to which more formal methods cannot be applied), but their computational requirements demand the development and implementation of additional heuristics to find a satisfactory solution. This work seeks to employ adaptive search methods to enhance the search process used to find the optimal design of any water distribution system. A first study presented here introduces post-optimization heuristics that analyze the best design obtained by a genetic algorithm--arguably the most popular adaptive search method--and perform an ordered local search to maximize further cost savings. When used to analyze the best design found by a genetic algorithm, the proposed post-optimization heuristics method successfully achieved additional cost savings that the genetic algorithm failed to detect after an exhaustive search. The second study herein explores various ways to improve artificial neural networks employed as fast estimators of computationally intensive constraints. The study presents a new methodology for generating any large set of water supply networks to be used for the training of artificial neural networks. This dataset incorporates several distribution networks in the vicinity of the search space in which the genetic algorithm is expected to focus its search. The incorporation of these networks improved the accuracy of artificial neural networks trained with such a dataset. These neural networks consistently showed a lower margin of error than their counterparts trained with conventional training datasets populated by randomly generated distribution networks.

An evaluation for Lag time, defined as the time from the centroid of rainfall excess to the centroid of direct runoff, was performed for seven small watersheds in the Southwestern United States. The size of these watersheds range in size from 0.33 to 4.37 ha. The evaluation period goes from 2000 to 2010. This evaluation was compared versus 28 lag time equations.The USDA-ARS Southwest Watershed Research Center has developed an electronic data processing system where rainfall and runoff data is collected from sensors in the field and are transmitted to computers in the office.Prior to these data sets there were no measurable rainfall and runoff data. This digital data is generated by means of synchronized clocks in rain gages and flumes. As a result, the data from this electronic processing system offers a unique opportunity for hydrologic research. This infrastructure is a characteristic not often available in many other sites and a condition not enjoyed in previous investigations.There are several definitions of lag time depending on what particular time period is used to describe the occurrence of unit rainfall and runoff. But, time parameters currently lack commonly-accepted standard definitions.The various definitions for time parameters such as Lag Time, Time of Concentration, Time to Peak, Equilibrium Time and others, sometimes, are used interchangeably. Another aspect is that in Lag time determination, centers of mass play a critical role. This study found out that depending of the loss model chosen to estimate rainfall excess, it shall influence the determination of center of mass and hence the lag time.Some negative values were obtained for lag time when measured from peak of runoff to centroid of effective rainfall. However, in the lag time definition from centroid of effective rainfall to centroid of direct runoff, negative values were not obtained.One field in particular, time parameters currently lacks commonly-accepted standard definitions. This has become a source of profound confusion in this branch of science to the point where teams of scientists writing about and discussing hydrological Time Parameters can be compared to the aftermath at the Tower of Babel.

One of the motivating reasons for the development of hydroponics was avoidance of root pathogens. Hydroponics involves growing crops in relatively sterile media, isolated from the underlying soil which may have disease pressure. However, even when hydroponics is coupled with controlled environments such as high tunnels and climate-controlled greenhouses, soil-borne pathogens can enter the growing area and proliferate due to optimal environmental conditions for pathogen growth. Control of root pathogens is difficult and usually achieved through synthetic fungicides since few biocontrol options are available. Compost water extracts (CWE) have recently been gaining the attention of greenhouse growers because they may be a low-cost, environmentally friendly approach to control root disease. CWE are mixtures of compost and water incubated for a defined period of time, either with or without aeration, and with or without additives intended to increase microbial populations, which in turn suppress disease. Much anecdotal, but very little scientific, evidence exists describing CWE effect on suppressing soil-borne pathogens. The present study 1) examined the effect of an aerated CWE on disease suppression at the laboratory scale and in container studies using different soilless substrates, 2) investigated a phenotypic change at the root level caused by CWE that may be associated with disease suppression, and 3) isolated some factors in the production of CWE that affect the ability of a CWE to suppress disease. The common model pathogen-host system of Fusarium solani f.sp. pisi and pea was used to examine CWE-induced disease suppression, with information then being translatable to similar patho-systems involved in greenhouse crop production. In the first study, laboratory-based root growth and infection assays resulted in 100% suppression of F. solani when roots were drenched in CWE. These protected seedlings were then taken to a greenhouse and transplanted into fine coconut coir, watered with hydroponic nutrient solution, and grown for five weeks. At the end of the experiment, 23% of the shoots of the pathogen-inoculated, CWE-drenched seedlings remained healthy while only 2% of the inoculated seedlings without CWE drench remained healthy. All of the roots of the inoculated seedlings developed lesions, even those drenched in CWE. However, 29% of the CWE drenched roots were able to recover from disease, growing white healthy roots past the lesion, while only 2% recovered naturally. A shorter-term container study was conducted in the laboratory to determine the effects of CWE-induced suppression when peas were grown in different substrates and to determine if the hydroponic nutrient solution had an effect on the suppression. Peas were grown in sterilized fine and coarse coconut coir fiber and sand irrigated with water, with a second set of fine coir irrigated with hydroponic nutrient solution. Pea seeds with 20-25mm radicles were inoculated with pathogen and sown directly into CWE-drenched substrate and grown for three weeks. At the end of the experiment, 80%, 60%, 90%, and 50% of the shoots of the inoculated, CWE-drenched seedlings remained healthy when grown in fine coir, coarse coir, sand, and fine coir irrigated with hydroponic nutrient solution, respectively. Nearly 100% of the roots grown in coconut coir substrates again developed necrotic lesions but 83%, 87%, 100%, and 87% grew healthy roots beyond the disease region. The hydroponic nutrient solution had a negative effect on suppression, with a reduction of at least 30 percentage points. Sand demonstrated a natural ability to suppress F. solani. Only 23% of inoculated seedlings had dead or dying shoots by the end of the experiment (compared to 77-80% in coir substrates) and although all but one of the roots developed lesions, all were able to recover on their own with CWE. CWE further increased shoot health and also prevented 57% of the roots from developing lesions. In a second study, two different CWE were used to examine the effect on root border cell dispersion and dynamics in pea, maize, cotton, and cucumber and its relation to disease suppression. Dispersal of border cells after immersion of roots into water or CWE was measured by direct observation over time using a compound microscope and stereoscope. Pictures were taken and the number of border cells released into suspension were enumerated by counting the total number of cells in aliquots taken from the suspension. Border cells formed a mass surrounding root tips within seconds after exposure to water, and most cells dispersed into suspension spontaneously. In CWE, >90% of the border cell population instead remained appressed to the root surface, even after vigorous agitation. This altered border cell phenomena was consistent for pea, maize, and cotton and for both CWE tested. For most cucumber roots (n=86/95), inhibition of border cell dispersal in both CWE was similar to that observed in pea, maize, and cotton. However, some individual cucumber roots (8±5%) exhibited a distinct phenotype. For example, border cells of one root immersed into CWE remained tightly adhered to the root tip even after 30 minutes while border cells of another root immersed at the same time in the same sample of CWE expanded significantly within 5 minutes and continued to expand over time. In a previous study, sheath development over time in growth pouches also was distinct in cucumber compared with pea, with detachment of the sheaths over time, and root infection was reduced by only 38% in cucumber compared with 100% protection in pea (Curlango-Rivera et al. 2013). Further research is needed to evaluate whether this difference in retention of border cell sheaths plays a role in the observed difference in inhibition of root infection. In the third study, a series of investigations were conducted to isolate different factors that contribute to the suppression ability of a CWE by changing incrementally changing some aspect of the CWE production process. The basic aerated CWE recipe (with molasses, kelp, humic acid, rock phosphate, and silica) provided 100% protection of pea from root disease while the non-aerated basic recipe CWE provided 72% protection. Aerated CWE made of only compost and water resulted in 58% protection. It was found that molasses did not contribute to the suppression ability of the ACWE, while kelp contributed strongly. When soluble kelp was added by itself to the compost and water, the CWE provided 80% suppression. However, when all additives were included except molasses and kelp, suppression remained high (93%) indicating that humic acids, rock phosphate, and/or silica were also major contributors toward the suppression effect. Optimal fermentation time for ACWE was 24 hr to achieve 100% suppression, with increased time resulting in inconsistent suppression results. Optimal fermentation time for NCWE was 3 days or 8 days. These studies are important contributions to understanding the differences that might be expected in CWE suppression when growing in different substrates, some of the factors in the production of CWE that affects the ability of a CWE to suppress disease, and the phenotypic effect CWE has on the root zone of plants and the possible relationship between that effect and disease suppression.

Submitted by Eliana Katia Pupim (katiapupim@tupa.unesp.br) on 2018-06-28T13:30:07Z No. of bitstreams: 1 pupim_ek_do_mar.pdf: 5107031 bytes, checksum: 8847c7bb4b7bf86bf7add53a1e945d29 (MD5) / Approved for entry into archive by Satie Tagara (satie@marilia.unesp.br) on 2018-06-29T14:31:46Z (GMT) No. of bitstreams: 1 pupim_ek_dr_mar.pdf: 5107031 bytes, checksum: 8847c7bb4b7bf86bf7add53a1e945d29 (MD5) / Made available in DSpace on 2018-06-29T14:31:46Z (GMT). No. of bitstreams: 1 pupim_ek_dr_mar.pdf: 5107031 bytes, checksum: 8847c7bb4b7bf86bf7add53a1e945d29 (MD5) Previous issue date: 2018-05-30 / Não recebi financiamento / A profissão do Engenheiro de Biossistemas ainda é recente no Brasil, sendo que a implantação do primeiro curso superior ocorreu em 2009. Em função da sua afinidade com a Engenharia Agrícola, os órgãos reguladores da profissão de Engenharia ainda não reconhecem seus egressos como Engenheiros de Biossistemas, mas sim os intitulam de Engenheiros Agrícolas com especificidade em Biossistemas. Diante desta problemática, o objetivo desta pesquisa foi traçar paralelos entre os campos científicos das Engenharia Agrícola e Engenharia de Biossistemas, de forma a permitir a elaboração de subsídios que levem à compreensão dos pontos de proximidade e de distanciamento dos domínios estudados. O método utilizado para alcançar o objetivo proposto foi a Análise de Domínio, optando pelas abordagens com Estudos Históricos e Estudos Bibliométricos, com a adoção da análise de conteúdo de Bardin e a elaboração de nuvens de palavras para as analogias. Os resultados permitiram compreender que sim, há vários momentos em que a Engenharia de Biossistemas e a Engenharia Agrícola são análogas, como na organização e na duração e integralização dos cursos, porém quanto aos conteúdos disseminados oferecem uma variação quanto aos temas relacionados à Zootecnia e Ciências Biológicas, sendo que enquanto a Engenharia de Biossistemas os trata como temas centrais, a Engenharia Agrícola os tem como temáticas periféricas. A produção científica também tem suas características peculiares, havendo periódicos que publicam apenas o conteúdo de uma ou de outra Engenharia, contudo há em número maior os periódicos que publicam as duas Engenharias concomitantemente, demonstrando que apesar de suas especificidades, há muito em comum na Engenharia de Biossistemas e na Engenharia Agrícola. / The profession of the Biosystems Engineer is very recent in Brazil. The first undergraduate major was implemented in 2009. Due to its affinity with Agricultural Engineering, the regulatory entities of the Engineering majors in Brazil do not recognize its graduates as Biosystems Engineers, but rather call them Agricultural Engineers with specificity in Biosystems. In view of this problem, the objective of this research was to draw parallels between the scientific fields of Agricultural Engineering and Biosystems Engineering, in order to find information that lead to understanding the points of proximity and distancing of the studied domains. The method used to reach the proposed goal was Domain Analysis, opting for approaches with Historical Studies and Bibliometric Studies, with the adoption of the Bardin content analysis and the elaboration of word clouds to allow for comparisons. The results allowed us to understand that there are several moments in which Biosystems Engineering and Agricultural Engineering are similar, as in the organization and duration and completion of the majors. However, the disseminated contents offer a variation regarding the subjects related to Zootechnics and Sciences Biological Sciences. While Engineering of Biosystems treats them as central themes, Agricultural Engineering has them as peripheral themes. Scientific production also has its peculiar characteristics, and there are periodicals that publish only the content of one or the other Engineering, however there are in greater number periodicals that publish the two Engineering concomitantly, demonstrating that despite their specificities, there is much in common in Engineering Biosystems and Agricultural Engineering.