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Effectiveness of Community Bowling Program for Youth with Disabilities

The pandemic-related social distancing protocols and resultant limitations in recreational activities raised additional barriers for children with disabilities participating in sports and social events. This study describes the effects of an adaptive recreational community bowling program on quality of life (QoL) and physical abilities in children with disabilities during the COVID-19 pandemic. Thirty-four children participated at four different bowling locations. Pre- post-intervention data collected included the PedsQL: Parent Report Quality of Life and General Welwell-being scale for children, pinch strength test, grip strength test, trunk flexion test, and shoulder range of motion measure. Results showed significant improvements (p-value=0.01) in bilateral pinch strength and thoracolumbar range of motion. No differences were found in grip strength or shoulder range of motion. Significant improvements were found in QoL (p-value=0.01) primarily related to social and emotional factors. This suggests that adaptive community recreational bowling programs can have therapeutic effects on children with disabilities.

Traywick, L., Griffin, T. W., Curtis, D., and James, D.

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Agriculture Drone

Farm operators consider financial and non-monetary factors when investing in technology; however, economic analyses usually ignore important non-monetary factors while focusing on only monetary factors. Non-monetary factors such as human capital costs and quality-of-life benefits explain adoption rate deviation from industry expectations. Six technologies examined include automated guidance, automated section control, imagery, precision soil sampling, variable rate, and yield monitors. Rather than exclusively relying on financial analyses to model technology adoption decisions, a holistic economic perspective replete with joint utility maximization within the household is proposed. Future generations of digital technology are likely to be developed with less reliance on required human capital investment while improving quality of life.

Traywick, L., Nilsson, T., González de Cosío, A., Griffin, T. W.

Autonomous robotic systems may replace status quo single-pass destructive harvest with two or more passes. Multiple-harvest systems avoid production and quality penalties from non-optimum harvest timing. Interperiod carryover penalties for perishable crops reduce physical production available for harvest. Reduced quality adversely affects sales price. In addition to maximized returns to fixed costs, optimum timing for each multiple-pass harvest event was reported. Multiple-pass optimization models are useful for forestry and logging, fresh produce such as berries and tomatoes, orchard crops such as apples and pears, field crops such as cotton, and other high-value indeterminate crops. Here, cotton, a high-value indeterminate field crop with specialized harvest equipment was the example. Results are pertinent to farmers, researchers, and equipment manufacturers developing the next generation of machinery to perform their own what-if analyses using interactive web dashboard tools.

Griffin, T. W., Yeager, E. A., Rains, G. C, Griffin, T. G., Raper, T. B., 

Lindhorst, C. 


Farm data valuation has been an emergent topic across the agricultural sector for several decades. Previous analyses focused on estimating damages from misappropriation, although no existing estimates of valuation within the farm gates for data, especially inaccessible data. Based on actual events when yield monitor data became inaccessible to farm operators, damages were estimated in anticipation of litigation. Valuation was estimated given how yield monitor data was intended to be used in the decision-making process. Specifically, valuation was estimated within the context of conducting farmer-managed on-farm experimentation. Farmers implicitly value on-farm experiments given the financial and non-monetary, i.e. human capital, investments. Key outcomes included 1) farm operators must be perceived to use data and 2) data must be treated as valuable. Each on-farm experiment was valued at over $40,000.

Griffin, T. W.

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