Scale Production Research Articles

Machine learning techniques for coffee classification: a comprehensive review of scientific research

In the realm of agribusiness, transformative shifts are underway, propelled by the growing demands and expanding scales of grain production. This evolution calls for a critical reevaluation of the existing paradigms in coffee production and marketing paradigms, with a specific focus on integrating Artificial Intelligence (AI). This work aims to review, synthesize, and summarize the available data regarding how Machine Learning (ML) has been used to detect and classify characteristics in coffee beans and leaves. For this purpose, a comprehensive literature review of the most significant research contributions describing the application of AI for advanced classification techniques in coffee agriculture has been carried out. Our analysis suggests that implementing AI technologies allows the classification of coffee, encompassing various attributes such as maturity, roast intensity, disease identification, flavor profiles, and overall quality. More largely, this technological advancement holds the potential to revolutionize coffee farming by providing producers and agricultural specialists with sophisticated tools to enhance production efficiency, minimize costs, and improve the accuracy and confidence of their decision-making processes. The motivation for the literature review is to address the increasing global demands and evolving scales of grain production, particularly in coffee farming, by critically reevaluating existing paradigms and integrating AI techniques. This review aims to synthesize and summarize how ML has been utilized to detect and classify various characteristics of coffee beans and leaves, thereby highlighting the potential of AI to revolutionize coffee farming by enhancing production efficiency, minimizing costs, and improving decision-making accuracy. This article presents the latest studies in ML in the coffee area, observes the methodology used, and allows researchers to develop new solutions that cover gaps in the literature, open problems, challenges, and future trends, bringing a real contribution to the scientific field. Finally, this article gathers and presents the databases used in many studies, which may be useful for future ML projects.

Biocontrol of plant pathogens by Lysobacter enzymogenes isolate LEC: efficacy of shake flask broth, fermentation broth and dried preparations

ABSTRACT The aim of our study was to upscale the production of Lysobacter enzymogenes strain LEC from shake flasks to a laboratory bioreactor. The obtained fermentation broth was to be downstream-processed by lyophilisation and fluidised bed-drying, followed by testing of the dried preparations against plant pathogens. Different batches of broth from shake flasks and from individual fermenter runs were characterised and compared. Number of viable cells, in vitro efficacy (ED90 value) against the apple scab pathogen Ventura inaequalis, as well as efficacy against Phytophthora infestans on potato plants were all reproducible and not impaired by upscaling the production volume from shake flask to the bioreactor. Fermentation broth was processed by lyophilisation and fluidised bed-drying. In bioassays, the activity against downy mildew (Pseudoperonospora cubensis) on cucumber were comparable for the unformulated fermentation broth and the fluidised bed-dried product, while the lyophilised product was significantly more effective. Strain LEC showed reproducible pathogen suppressive activity, independent from production scale and batch. Production upscaling and formulation by drying are possible without loss of efficacy.

Research on automated defect detection system based on computer vision

Abstract. With the intensification of market competition and consumer demand for product quality enhancement, people's development of industrialization is also more and more in-depth, the production scale and complexity of a variety of products is also increasing. However, in the process of automated production, product defects are unavoidable due to various factors such as equipment, environment, and human influence. The traditional human inspection method is inefficient, costly, and subjective, making it difficult to meet the needs of modern industrial production. Therefore, the need for an efficient, accurate and automated inspection system is urgent. Based on the current social situation, this paper will introduce the automated defect detection system based on computer vision, which is widely used in many fields, and has a great guarantee for people in the production of products with high quality and low cost, based on the needs in these areas, this paper will firstly introduce the relevant algorithms and their main contributions to the application scenarios of computer vision technology, and then introduce the key technologies of computer vision in defect detection in the key technology.

The Impact of GDP Growth on Foreign Direct Investment: An Analytical Study

This study explores the relationship between Gross Domestic Product (GDP) growth and Foreign Direct Investment (FDI) inflows in developing economies. As FDI plays a pivotal role in driving economic progress, understanding its dynamics relative to GDP growth provides valuable insights for policymakers and investors. The manufacturing sector, with its need for cost efficiency, production scale, and infrastructure, attracts FDI when GDP growth fosters these elements. Conversely, the services sector, which relies on skilled labour and technology, benefits from rising GDP, fuelling local demand for services. This research uses historical data, descriptive statistics, and regression analyses to evaluate GDP's impact on FDI from 1970 to 2023. The findings reveal a positive correlation between GDP growth and FDI inflows, with distinct sectoral variations that highlight specific economic demands in manufacturing versus services. The study’s conclusions aim to guide targeted policies for fostering sectoral FDI, supporting balanced and sustainable economic development.

Blasting techniques applied to control vibrations, flyrock, and slope damage while ensuring compatibility with fragmentation

Blasting operations in mines near communities are of increasing social concern and scientific investigation due to the potential structural damage and human discomfort caused by blasting induced vibrations. Therefore, a technical-scientific approach is necessary to conduct these activities safely and sustainably compatible with fragmentation requirements of the scale of production. This paper presents a case study of an open-pit mine located in Brazil, where blasts are frequently carried out near a community. Additionally, controlling flyrock is extremely important in this mine due to the proximity of people to the blasting sites, as well as controlling the slope damage. Thus, it became necessary to develop a methodology for the application and combination of techniques and simulation fo blasting-induced vibration and wall control, flyrock and fragmentation such as attenuation law, signature holes, decking charge techniques, pre-split holes. The proposed methodology was effective, validated, and is recommended for open-pit mines operating near communities.

Microfluidic Synthesis of Magnetic Nanoparticles for Biomedical Applications.

Magnetic nanoparticles have attracted great attention and become promising candidates in the biomedicine field due to their special physicochemical properties. They are generally divided into metallic and non-metallic magnetic nanoparticles, according to their compositions. Both of the two types have shown practical values in biomedicine applications, such as drug delivery, biosensing, bioimaging, and so on. Research efforts are devoted to the improvement of synthesis strategies to achieve magnetic nanoparticles with controllable morphology, diverse composition, active surface, or multiple functions. Taking high repeatability, programmable operation, precise fluid control, and simple device into account, the microfluidics system can expand the production scale and develop magnetic nanoparticles with desired features. This review will first describe different classifications of promising magnetic nanoparticles, followed by the advancements in microfluidic synthesis and the latest biomedical applications of these magnetic nanoparticles. In addition, the challenges and prospects of magnetic nanoparticles in the biomedical field are also discussed.

Pennycress reduces potential for nutrient loss in Illinois.

Nutrient export of nitrogen and phosphorus from row crop agriculture in the Upper US Midwest is a threat to the structure and function of aquatic systems. To meet Environmental Protection Agency (EPA) nutrient reduction goals, the Upper US Midwest needs to implement strategies to reduce nutrient export from agriculture. Studies demonstrate the potential of cover crops to reduce the export of nitrate-nitrogen from the Upper US Midwest. We investigated the impact of the economically viable winter cash cover crop pennycress (Thlaspi arvense) on soil porewater nutrients and soil nutrients and characteristics. We used nine replicated 0.8ha plots (n=3 per treatment) at a production scale research farm over 4 years with pennycress and fertilized pennycress (56kg ha-1 of urea) treatments compared to a fallow reference. Over the study period, soil porewater nitrate-nitrogen was reduced by 53% in pennycress plots and 34% in fertilized pennycress plots relative to the fallow reference at a depth of 45cm. Early season establishment was crucial in providing nutrient reduction potential. In 2021, poor pennycress establishment resulted in porewater nitrate-nitrogen concentrations 141% higher than in 2022 with excellent pennycress establishment. Following pennycress termination, soil nitrate-nitrogen was reduced by 24% in pennycress and 26% in fertilized pennycress compared to the fallow reference in the top 30cm of soil. Following 4 years of pennycress planting, nitrate-nitrogen concentrations were significantly reduced with no broad effect on soil characteristics. We conclude that the novel pennycress crop has potential to reduce nutrient loss from row crop agriculture in the Upper US Midwest.

Edible Films from the Laboratory to Industry: A Review of the Different Production Methods

AbstractEdible films or coatings as potential replacements for traditional plastic food packaging are a popular subject for research. This article provides a narrative summary of the progress of research into edible food packaging and preparation methods at three different production scales over the past 5 years. First, at the laboratory research level, commonly used coating methods include dipping, vacuum dipping, and spraying. Films are mostly made by solution casting, while 3D printing film technology and electrospinning/electrostatic spraying are emerging technologies in the field. At the pilot level, panning coating, brush coating, and fluidized bed technologies give edible food packaging a more scalable and realistic approach. On an industrial manufacturing scale, in order to improve film formation efficiency, blowing, injection, calendering, etc. are generally based on the extrusion mode. Laboratory-scale research is critical for developing materials and exploring their properties. The technology used for industrial-scale production needs to consider factors such as cost and efficiency. Each technology for making food packaging needs to be selected according to the production purposes and the currently available packaging equipment. However, commonly used edible packaging source materials are generally derived from biological macromolecules such as proteins and polysaccharides. These materials are heated and extruded in industrial production, and their performance will be inferior to that of traditional plastic packaging. In addition, high cost is also a factor that must be considered.

Genome reduction improves octanoic acid production in scale down bioreactors.

Microorganisms in large-scale bioreactors are exposed to heterogeneous environmental conditions due to physical mixing constraints. Nutritional gradients can lead to transient expression of energetically wasteful stress responses and as a result, can reduce the titres, rates and yields of a bioprocess at larger scales. To what extent these process parameters are impacted is often unknown and therefore bioprocess scale-up comes with major risk. Designing platform strains to account for these intermittent stresses before introducing synthesis pathways is one strategy for de-risking bioprocess development. For example, Escherichia coli strain RM214 is a derivative of wild-type MG1655 that has had several genes and whole operons removed from its genome based on their metabolic cost. In this study, we engineered E. coli strain RM214 (referred to as WG02) to produce octanoic acid from glycerol in batch-flask and fed-batch bioreactor cultivations and compared it to an octanoic acid-producing E. coli MG1655 (WG01). In batch flask cultivations, the two strains performed similarly. However, in carbon limited fed-batch bioreactor cultivations, WG02 provided a greater than 22% boost to biomass compared to WG01 while maintaining similar titres of octanoic acid. Reducing the biomass accumulation of WG02 with nitrogen limited fed-batch cultivation resulted in a 16% improvement in octanoic acid titre over WG01. Finally, in a scale-down system consisting of a stirred tank reactor (representing a well-mixed zone) and plug flow reactor (representing an intermittent carbon starvation zone), WG02 again improved octanoic acid titre by almost 18% while maintaining similar biomass concentrations as WG01.

Sulfamic Acid Catalyzed One‐Pot Three‐Component Synthesis of Spiro‐Oxindole Fused Dihydroquinazolinone Derivatives in Aqueous Medium

AbstractA simple, efficient, and straightforward protocol has been developed for the synthesis of spiro‐oxindole fused dihydroquinazolinone derivatives from one‐pot three‐component reactions of isatoic anhydride, various primary anilines, and substituted isatins using a catalytic amount of sulfamic acid as an organocatalyst in water under refluxed conditions. All the synthesized compounds were formed within just 2 h and isolated pure by simple filtration with excellent yields (89%–94%). Gram scale production, use of commercially available low‐cost organocatalyst, green solvent, reusability of the medium, one‐pot three‐component reaction strategy, no column chromatography, and high atom economy are some of the major benefits of this newly developed protocol.

Scaling sustainable pig manure treatment: Life cycle assessments for small to large piggeries in China

Over 50 % of pig stockpiling and slaughtering in China is attributed to medium and large piggeries. The diverse scales and distributions of these piggeries present significant challenges for the sustainable management of pig manure, with a research gap in assessing the environmental benefits of treatment technologies across different farm sizes. Therefore, the environmental and economic performances of ten pig manure treatment technologies for small, medium and large piggeries were evaluated via life cycle assessment and life cycle costing methods. The black membrane biogas pool (BMBP) technology for medium-scale piggeries demonstrates superior environmental performance, reducing emissions by 44.00 kg CO2 equivalent, 0.36 kg SO2 equivalent, and 0.05 kg PM2.5 equivalent per ton of dry pig manure treated. Additionally, the products generated from this process can offset 2.93 GJ of energy consumption and 0.25 tons of water consumption. Meanwhile, the ectopic microbial fermentation bed technology provides the best economic efficiency, at the cost of only $17.88 per ton. Significant disparities in the scale of piggeries and manure production across provinces necessitate region-specific policies. The estimated global warming potential (GWP) from pig manure treatment nationwide was 5.31 million tons of CO2 equivalent, with Henan, Sichuan, and Hunan provinces accounting for a combined 28.3 % of this total in 2020. Scenario analysis indicates that by 2025, achieving a pig manure utilization rate of 90 % could reduce GWP by 9.1 % (0.5 million tons of CO2 equivalent) compared to an 80 % utilization rate, with reductions ranging from 1.78 % to 22.36 % across other environmental indicators. Promoting technologies such as BMBP and transitioning 5 % of aerobic processes to anaerobic processes could reduce emissions by 2.9 %, while also lowering other environmental indicators by 12.8 % to 20.1 %. The utilization of anaerobic technology, coupled with enhanced utilization rates, can prove more efficacious in mitigating carbon emissions and pollutants.

Use of a rugged mid-infrared spectrometer for in situ process analysis of liquids

The widespread application of mid-infrared (MIR) spectroscopy for process monitoring is currently limited by the poor transmission of MIR light through fibre optics. In this work, the performance of a novel and robust MIR spectrometer has been evaluated for practical deployment in a pilot plant or production environment. The spectrometer utilises a Sagnac interferometer design containing no moving parts and is directly attached to an attenuated total reflectance probe, eliminating the need for fibre optics. The quantitative performance of the spectrometer for the in situ analysis of ternary solvent mixtures was assessed. The predictions obtained by partial least squares were accurate (root mean square error of prediction of < 1 % w/w) and comparable to those of a benchmark Michelson-based spectrometer with a fibre-coupled probe, which is more amenable to process development in a laboratory or pilot plant. Calibration transfer between the two spectrometers was performed using the spectral space transformation method to mimic the scenario of the scale-up of a process from the laboratory to pilot scale or from a pilot plant to production scale, where the two different MIR instruments might be deployed. The ability to perform in situ reaction monitoring with the robust Sagnac-based spectrometer was then demonstrated. Spectra acquired during an esterification reaction were resolved using multivariate curve resolution, to produce concentration profiles of each component. These results demonstrate the suitability of this rugged spectrometer for quantitative in situ monitoring of liquid processes, opening up new opportunities for process monitoring in the MIR region.

Nanotechnology in pharmaceutical manufacturing: present innovations and future opportunities

Nanotechnology has revolutionized the pharmaceutical industry by enabling the design and delivery of drugs with enhanced precision, efficacy, and safety. This review provides a comprehensive overview of current trends and future prospects in nanotechnology-based drug manufacturing. It explores the application of nanocarriers, such as liposomes, micelles, and nanoparticles, which have improved drug bioavailability, targeted delivery, and reduced side effects. Nano formulations like solid lipid nanoparticles (SLNs) and polymeric nanoparticles are also highlighted for their role in controlled drug release and cancer treatment. Technological innovations, including advanced nanofabrication techniques and 3D printing, are driving the development of complex drug formulations. The review also addresses the challenges in scaling production and the evolving regulatory landscape. Future prospects include the use of nanobots and advanced Nano machines for drug delivery, the integration of nanotechnology in gene therapy and CRISPR, and the exploration of new research and investment opportunities. Ethical and safety considerations, such as the long-term effects of nanomaterials on human health and the environment, are discussed. This review underscores the transformative potential of nanotechnology in drug manufacturing, offering insights into its role in shaping the future of the pharmaceutical industry.

ANALYTICAL EVALUATION OF THE EFFECTIVENESS OF EQUITY MANAGEMENT IN AGRICULTURAL, FORESTRY AND FISHERY ENTERPRISES IN UKRAINE

The purpose of the research is to generalize the theoretical and methodological aspects and implementation an analytical evaluation of the effectiveness of the management of equity of agricultural, forestry and fishery enterprises of Ukraine using the data of official statistics on large, medium and small enterprises for ten years (2013-2022) as a basis for directing analysis results for the further search for reserves to improve the efficiency of equity management. Methodology. The basis of the research methodology is a dialectical approach, an analysis of data on the composition and structure of equity capital of agricultural, forestry and fishing enterprises of Ukraine for the period from 2013 to 2022 with the division of enterprises into large, medium and small using official statistical information, published on the website of the State Statistics Service of Ukraine. The results of the research showed that in the period from 2013 until 2022, the largest increase in the equity capital of agricultural, forestry and fishing enterprises of Ukraine was observed at the end of 2015 compared to the end of 2014 due to the simultaneous increase in the value of the indicator at enterprises of different sizes. In the structure of equity capital, the share of retained earnings (uncovered loss) was the most significant. In the vast majority of the research years, at average and small enterprises, cash revenue exceeded the amount of equity capital, while at large enterprises, from 2016 to 2022, equity capital made less than one turnover per year. As the calculations showed, large enterprises in the field of agriculture, forestry and fisheries of Ukraine do not properly take advantage of the possibilities of the influence of the scale of production on the formation of indicators of the efficiency of the use of equity. Practical implications. The practical significance of the obtained results lies in their focus on confirming the expediency of the further search for reserves to increase the efficiency of the use of equity, first of all, by large enterprises in the field of agriculture, forestry and fisheries of Ukraine. Value / Originality. The results of the conducted research serve as the basis for further in-depth analysis and search for reserves to increase the efficiency of equity management at different sized of business entities.

Research on tomato disease image recognition method based on DeiT

Tomatoes, globally cultivated and economically significant, play an essential role in both commerce and diet. However, the frequent occurrence of diseases severely affects both yield and quality, posing substantial challenges to agricultural production worldwide. In China, where tomato cultivation is carried out on a large scale, disease prevention and identification are increasingly critical for enhancing yield, ensuring food safety, and advancing sustainable agricultural practices. As agricultural production scales and the demand for efficient methodologies grows, traditional disease recognition methods no longer meet current needs. The agricultural sector's move towards more modern and scalable production methods necessitates more effective and precise disease recognition technologies to support swift decision-making and timely preventive actions. To address these challenges, this paper proposes a novel tomato disease recognition method that integrates the data-efficient image transformers (DeiT) model with strategies like exponential moving average (EMA) and self-distillation, named EMA-DeiT. By leveraging deep learning technologies, this method significantly improves the accuracy of disease recognition. The enhanced EMA-DeiT model demonstrated exemplary performance, achieving a 99.6 % accuracy rate in identifying ten types of tomato leaf diseases within the PlantVillage public dataset and 98.2 % on the Dataset of Tomato Leaves, which encompasses six disease types. In generalization tests, it achieved 97.1 % accuracy on the PlantDoc dataset and 97.6 % on the Tomato-Village dataset. Utilizing the improved DeiT model, a comprehensive tomato disease recognition system was developed, featuring modules for image collection, disease detection, and information display. This system facilitates an integrated process from image collection to intelligent disease analysis, enabling agricultural workers to promptly understand and respond to disease occurrences. This system holds significant practical value for implementing precision agriculture and enhancing the efficiency of agricultural production.

Dielectric drying of black soldier fly larvae (Hermetia illucens): impact on microbiological product quality, safety and stability

Abstract Along with the increasing scale of industrial production of insects as food and feed, the need for processing methods applicable on large scale is rising within the insect sector. One important processing technology in this context is drying, which aims at stabilising the quality of the insects. This study investigated the impact of dielectric drying technologies, specifically microwave (μW) and radio frequency (RF) drying, on the microbiological quality, safety, and stability of black soldier fly (BSF) larvae in comparison to the traditional methods oven drying and freeze drying. Before, during and after subjecting a large batch of blanched BSF larvae to the four drying technologies, their water activity and moisture content as well as general microbial and pathogen counts were assessed. Dielectric drying effectively reduced water activity, thus enhancing product stability. Microbiological analyses revealed the efficacy of blanching in microbial reduction, with dielectric (especially RF) drying further contributing to these reductions. The results, however, do not conclusively support nonthermal microbial inactivation through dielectric treatment. Specific analyses targeting foodborne pathogens indicated the absence of most selected bacterial pathogens, except for (presumptive) Bacillus cereus. This pathogen was detected in a few samples but remained below safety thresholds and was effectively eliminated by dielectric drying. Finally, a shelf life stability evaluation showed minimal changes in dielectrically dried BSF larvae over six months, indicating a microbiologically stable product. In conclusion, dielectric drying technologies can retain or even improve the microbiological quality and stability of BSF larvae in the insect industry and can be considered as valuable and more efficient (time, energy consumption) alternatives to oven and freeze drying.

Digital Infrastructure, Opening-up to the Outside World and the Transformation of Digital Intelligence of Enterprises

Nowadays, the trend of the digital economy is prevalent, enterprises actively carry out the transformation of digital intelligence to seek a favourable position, and the Chinese government also vigorously promotes digital infrastructure, but the relationship between them remains to be investigated. Based on the panel data of A-share listed companies from 2011 to 2022, this paper constructs a double fixed effect model and demonstrates that digital infrastructure has a positive effect on the digital intelligent transformation of enterprises. The results show that technology spillover effect, production scale and digital sales play an intermediary role in the promotion of digital infrastructure to the transformation of digital intelligence of enterprises. Digital infrastructure has a significant role in promoting the transformation of enterprises in the eastern and western regions and areas with weak business environments. The level of enterprises’ opening-up plays a moderating role in the promotion of digital infrastructure to the digital intelligent transformation of enterprises. Based on this, some suggestions are put forward to speed up the construction of digital infrastructure and build a digital infrastructure system according to local conditions.

3D stochastic simulation of a deep-water turbidite system: An example from the Los Molles Formation, southern region of the Neuquén Basin, Argentina

A recurring challenge in geological modeling is bridging the gap between different scales. For example, difficulties arise when connecting outcrop data through production to exploration scale models. An object-based stochastic simulation was performed using outcrop data from the Arroyo La Jardinera area in the southern region of the Neuquén Basin, Argentina. This simulation involved four depositional sequences in a vertical succession that includes turbidites and associated deep marine facies. The aims of this study are (a) to determine the best geological model consistent with field and aerial image data; (b) to validate the application of object modeling to determine facies distribution; (c) to evaluate uncertainties from models based on scarce data. The studied interval covers a transgressive (J1) to regressive succession (J21, J22, and J23) of basin plain to slope depositional settings, featuring sandy and gravelly turbidite channels, turbidite lobes and interlobes, lobe fringes, and muddy slope and basin plain. Each depositional sequence model was constructed using specific input parameters for architectural elements, with lithological proportions based on sedimentary logs. The J1 sequence includes basin plain, lobe fringe, and minor lobe deposits; J21 features turbidite lobes, fringes, and subordinate channels; J22 accommodates turbidite channels scoured into muddy slope facies; and J23 encompasses gravelly and sandy turbidite channels carved on muddy slope facies. The geostatistical modeling of outcrop data has allowed building a quantitative sedimentological model useful for understanding subsurface facies heterogeneity in both exploration (vertical) and production (horizontal) scales.

Techno-economic analysis of bioplastic and biofuel production from a high-ash microalgae biofilm cultivated in effluent from a municipal anaerobic digester

Rotating Algae Biofilm Reactors (RABRs) are a promising technology for efficient treatment of wastewater and production of algae-based bioproducts. However, RABR-grown algae can contain a high content of ash (30–60 wt%, dry basis), which influences the technical and economic feasibility of bioproduct conversion processes. In this report, experimental studies and economic analysis were conducted to compare different processes for bioproduct conversion of a high-ash microalgae biofilm grown using a RABR treating 0.6 million gallons per day of anaerobic digestion centrate at the Central Valley Water Reclamation Facility in Salt Lake City, UT. Process and economic models were developed and compared for three conversion processes: 1) the production of bioplastics, 2) the production of bioplastics with a lipid-extraction pretreatment, and 3) the production of biocrude via hydrothermal liquefaction. Techno-economic analysis was performed for each conversion process, including three cases for algae productivity: 231, 391, and 577 metric tons per year (dry basis). The calculated value for the minimum plastic selling price (MPSP) of bioplastics produced from algae ranges from $4050 to $3520 per metric ton based on the baseline and final productivity cases of the RABR, respectively. The extraction of lipids in addition to bioplastic production results in an MPSP of $4570 to $4000 per metric ton for the same productivity cases. The relatively small production scale and complex processing for hydrothermal liquefaction results in a minimum fuel selling price of the biocrude of $5.32 per gallon of gasoline equivalent. The conversion process for bioplastic production from whole algae has the highest income:expense ratio and the most cost-competitive pricing of the three modeled processes.

Family farm and family business: Distinction and transition between concepts

Objective: Explore the conceptual limits between the family farming unit and the agricultural family business to identify the elements that determine the transition from one figure to another. Methodology: The distinctive elements between both concepts were determined from the most relevant definitions reported in the literature. Subsequently, the transition from a family farming unit to an agricultural family business was illustrated based on the case study of an enterprise dedicated to the production and collection of barley in Hidalgo, Mexico. Results: Seven distinctive elements were identified between the family farming unit and the agricultural family business. Two elements (the scale of production and productive diversification) drive the transition, three are modified consequently (the source of labor, the priority destination of productive activity, and the strength of the link with agricultural land), and the remaining two are carried out infrequently (assignment of a non-family member as main head and disengagement of family members from community life). Limitations: The findings of the study lack statistical representativeness as they come from a case study. Conclusions: The seven distinctive elements between a family farming unit and an agricultural family business can be used to study the phenomenon of entrepreneurship around agriculture and to typify agricultural units to design differentiated strategies for political intervention.