The asymmetry of information detected in this study might result in deterrence for some producers to participate in the program if they perceive that producers that do not share PRRS status have competitive advantages over those that do share information. This study used data from a 24-month period to evaluate a disease that has been present in the US for more than 30 years. The decreasing PRRS trend shown here is consistent with a similar trend reported at a national level, however, clearly, our discussion must consider that any short-term trend can be affected by some random shock and may not reflect the true long-term trend of the disease. For example, the decrease of PRRS incidence may be explained, at least inpart, by the emergence of PED in 2013, which had a major impact on the US swine industry. Because producers and veterinarians became more worried about certain practices that might facilitate PED spread, increased bio-security might also have helped PRRS control. Another interesting finding was the negative correlation between the probability of sharing PRRS status and occurrence of disease . This result may be explained, at least in part, by the expectation that negatives premises may have been more willing to share PRRS status than positive premises, because of the differential in the perceived economic consequences of sharing that infected and non-infected premises have. However, an alternative explanation for this finding is that producers may have recognized the value of increasing their level of PRRS-related information collected from neighbors and trading-partners that may have helped them to select their suppliers of inputs. Some have suggested that information obtained via the production chain can achieve desirable outputs more efficiently than by using laboratory analyses to detect system failure, arguing, for example, that efforts to reduce information asymmetries and ensure product quality has led to vertical integration and extended production contracts in animal food systems. Vertical integration allows perfect information throughout the production chains, drying weed which may be more efficient than laboratory tests to identify disease prevalence, which then must be translated into control efforts.

Similarly, certain attributes of the voluntary cooperation in RCPs, in terms of accessibility to data and information among producers located in a specific area, may resemble those observed in vertical systems, which may be useful and complementary to regular surveillance and strategy selection to control PRRS. Results in this study also reveal that the higher the density of medium and large premises at the county level, the higher the probability of occurrence of PRRS for farms in those counties. This result suggests that disease spread is positively related to the density of production premises and/or the number of swine. Consequently, one may hypothesize that given that larger premises have higher odds of being infected, they could act as sources of infection for secondary cases, given the larger susceptible population and associated management factors. The final model included premises nested into counties, which indicates certain heterogeneity among counties in terms of the relative importance of the variables assessed here. Indeed, and despite the declining incidence of PRRS over the study time, spatial, temporal and spatial-temporal aggregations were detected through the study period . Additionally, results from this study are consistent with a combination of direct and indirect mechanisms of spread, as suggested by the persistence of spatial aggregation in some areas, but with extensions into others regions that may result as a consequence of between premises movements. In conclusion, this study has established a systematic approach to quantify the effect of RCPs on PRRS control. There is evidence that RCP-N212 has attracted a growing proportion of producers to share disease status information, suggesting a rising awareness that sharing information can lead to more effective disease control. By evaluating the effect of participation on the occurrence of PRRS, the value of sharing information among producers may be demonstrated, in turn justifying the existence of RCPs. These results provide useful indicators regarding the evolution of the RCP-N212, and, ultimately, support for disease control in Minnesota. Furthermore, the methods presented here may be applied to measure progress in other RCPs.farming offers a sustainable solution to scarcity of fresh produce.

The concept of indoor farming has been explored for millennia. The concept of shielding plants from vacillating weather conditions by growing plants inside a greenhouse was first implemented by agrarian communities in 30 CE. As time and technology progressed, full control over ventilation, air flow, growth medium, and light exposure became feasible. One of the first fully-fledged controlled environment research facilities began operation at North Carolina State University in 1968. Recent developments in the semiconductor industry have made it cost effective for light-emitting diodes , which can provide the specific wavelengths of light for photosynthesis, to supplant broadspectrum sunlight. This has given rise to “plant factories”and indoor farming “pods” : warehouses and shipping containers outfitted with LEDs, hydroponics, cameras and advanced sensors which are nominally more efficient than traditional farms and greenhouses.Shade is not a concern for indoor farms as, with optimal optical design, all plants can receive the requisite light for photosynthesis. As such, many indoor farms will organize hydroponically grown plants in either 1) vertically-stacked shelves or 2) adjacent panels hanging from the ceiling. This dense packing of plants facilitates more growth on less land. To put this into perspective, a 30-story vertical indoor farm with a 5-acre base could produce a crop yield equivalent to 2400 acres of a traditional farm.Different plants require different wavelengths of light for optimal photosynthesis and optimal growth of features such as stem length and leaf thickness. LEDs are perfectly suited to supply plants with the specific, optimal combination of colors of light they need, because LEDs emit a narrow band of wavelengths depending on the bandgap of their constituent semiconductor material. Thus, indoor pod farms with “walls” of LED light strips reduce energy waste by maximizing the amount of power absorbed by the plants and minimizing the power lost to excess heat. Beams of light supplied by LEDs can be collimated by addition of optical lenses, further reducing energy lost to non-plant targets and reducing the distance between the plants and LEDs. Additionally, exponential development in the semiconductor industry over the past three decades has made LEDs smaller, faster-actuating, more efficient, and more durable than traditional incandescent light sources, rendering LEDs economically viable for indoor farming applications.Hydroponics is a method of growing plants in a nutrient rich solution without the need for soil. Depending on the type of crop, this method can be executed via drip irrigation, aeroponics, nutrient film technique, ebb and flow, aquaponics, or deep-water culture. Although physically very different in the method of delivery, most of these techniques share the same fundamentals: a nutrient solution is pumped to the plants via a specialized delivery system and then circulated back to a reservoir where the nutrients are replenished. We refer the reader to for a comprehensive description of these techniques. Hydroponic methods use, on average, 10% of the water utilized in traditional farming as nutrients are delivered directly to the plant roots, minimizing water lost to evaporation. This mode of growing plants can be easily automated and, vertical growing systems combined with the fact that the lack of soil protects against pests, these systems make it easier to cater to the unique physiological needs of the plants while eliminating the need for pesticides and other chemicals. These systems, however, have high start-up costs and thus present a dire need for high operational efficiency to recoup these costs.The practice of vertical indoor farming in shipping container “pods,” enabled by LED light sources and hydroponic nutrient sources, is still nascent and little work has been done to quickly and efficiently model and optimize such systems. A digital-twin of an indoor pod farm can be safely and cheaply manipulated without jeopardizing the system or the plants’ well-being, making it an exceedingly quick, inexpensive, and useful approach for identifying optimal operational parameters.

The indoor farming pod is a complex system with a multitude of physical phenomena including air flow, light propagation, and energy transfer. Several digital-twin frameworks have been developed to capture the physics of light propagation in greenhouse, agrophotovoltaic, and food decontamination applications using ray tracing techniques and to capture and optimize the physics of energy flow and air flow. Ray tracing techniques decompose light into rays whose interactions with surfaces are quickly geometrically traced, facilitating fast computation of a large number of interactions between rays and surfaces and optimization of the surface shape for maximum absorption/reflection. Digital-twins have been scarcely employed in optimizing agricultural systems, and they are even more rarely implemented in indoor farming pods. Two such implementations were carried out by Randolph et al. and Sambor et al. to optimize the energy consumption of an off grid indoor farming pod to determine optimal operation time for each component of the system. These implementations, however, do not allow for manipulation of the orientation and/or shape of the system’s components for maximum operational efficiency. In [29], computational fluid dynamics methods were utilized to model the air flow inside an indoor farming pod, but such methods have a prohibitively high computational cost, especially when running various configurations and performing optimization. Thus, an easily manipulated, computationally inexpensive model that accurately captures the system’s physics is desired.Indoor farming is a promising mode of next-generation agriculture offering numerous benefits such as year-round crop cultivation, reduced transportation costs, and enablement of urban farms. However, these systems still face challenges related to energy consumption, and there has been limited quantitative analysis of their overall efficiency. To fill this gap and promote innovative design, we introduce a cost-effective digital-twin to analyze the optical properties of an indoor farming pod using a ray-tracing model. We utilize a genomic optimization scheme to identify the most optimal LED geometric configurations and emission characteristics toward maximizing energy absorbed by the constituent plants. The proposed digital-twin and optimization framework serves as a foundational framework that takes a physics-driven approach to optimize energy flow and paves the way for more sustainable indoor farming practices. To adapt the framework to other indoor farming configurations, we can adjust design objectives via cost function design and incorporate constraints via parameter search bounds. The framework could also be extended to include models for water usage or crop-specific reactions to different chemical/pesticides, thereby enhancing the accuracy of the digital-twin. Extending the framework to include wavelength-specific power flow could further improve predictions of energy efficiency and crop yield by providing each plant with its ideal lighting conditions. Such refined models can serve as a valuable tools for testing and estimating how a particular design would perform in the real world, enabling farmers to make informed decisions and effectively optimize their own indoor farming setups.The growth of the dairy industry has been accompanied by an increased volume of waste emissions that mainly consist of fecal and farm matrices. Manure contains a large number of undigested organic nutrients such as sugars, amino acids, nucleic acids, and vitamins. It is thus a valuable source of organic matter, nitrogen, phosphorus, potassium, and some micronutrients. Animal manure has therefore been used on farms as one of the most important and valuable sources of nutrients to improve soil fertility and increase agricultural crop production. Some farms recycle the solids in manure to use as bedding material, which can have advantages for farmers in terms of availability, convenience, and cost effectiveness. Researches have demonstrated that the use of organic manure, whether it is used alone or in combination with inorganic fertilizers, can have positive effects on crop yield and can improve the soil quality. In China, manure has been used in many agricultural regions of the country for centuries. The application of manure to agricultural land is an environmentally friendly method of waste disposal. However, in addition to organic matter, manure also contains many harmful gases, heavy metals, parasite eggs, antibiotic resistance genes, and a variety of intestinal microflora and opportunistic pathogens, as well as antimicrobial resistant bacteria. Pathogenic and antimicrobial-resistant microorganisms contained in the manure can lead to the contamination of edible agricultural products. Thus,if these manures are used as fertilizer without treatment or are not treated properly, dangerous microorganisms could be transferred from animals to humans, bringing about a threat to the environment and to human health. In addition, bacterial contamination of dairy farm environments can cause disease or spoilage of milk and its secondary products.