The increased need for and scarcity of hydrocarbon energy pushes the search and extraction of reserves toward more technically difficult deposits and less efficient forms of hydrocarbon energy. The increased use of hydrocarbons also predicates the increased emission of detrimental chemicals in our surrounding environment. For these reasons, there is a need to find feasible sources of renewable energy that could prove to be more environmentally friendly. One possible source that meets these criteria is biomass, which in the United States is the largest source of renewable energy as it accounts for over 3 percent of the energy consumed domestically and is currently the only source for liquid renewable transportation fuels. Continued development of biomass as a renewable energy source is being driven in large part by the Energy Independence and Security Act of 2007 that mandates that by 2022 at least 36 billion gallons of fuel ethanol be produced, with at least 16 billion gallons being derived from cellulose, hemi-cellulose, or lignin. However, the production of biomass has drawbacks. The market for cellulosic bio-fuel feedstock is still under development, and being an innovative technique, there is a lack of production knowledge on the side of the producer. Some studies have been conducted that determine farmers’ willingness to produce switchgrass, however, they have been limited in geographic scope and additional research is warranted considering a broader area. Also, there have been production decision tools aimed at bio-mass, but these have either not been aimed at switchgrass specifically or have been missing key costs such as those incurred in storage. The overall objectives of this study are: 1.) to analyze the willingness of producers in the southeastern United States to plant switchgrass as a biofuel feedstock, 2.) to estimate the area of switchgrass they would be willing to plant at different switchgrass prices, 3.) to evaluate the factors that influence a producer’s decision to convert acreage to switchgrass, and 4.) to present a spreadsheet-based decision tool for potential switchgrass producers.

<p><a>Indiana is the leading state of cover crop adoption within the Upper Mississippi River Basin. However, since 2015 the cover crop adoption has slowed to a plateau. In order to regain the previous momentum, there must be an increased understanding of the spatiotemporal dynamics of cover crop adoption on the county and watershed scale. Currently, the cover crop adoption is monitored biannually through a driving transect survey method that investigates only 8.5% of the watershed and extrapolates to the entire county. However, the observations made by the driving transect survey can merely cover limited fields and is time-consuming. In addition, the driving transect survey did not provide comparative analysis among consecutive years. Therefore, we developed a rapid cover crop survey method by using remote sensing technology. The fundamental objectives of this research are: (1) evaluating the accuracy of the rapid cover crop survey method relative to the driving transect data and determining the best cut-off value (COV) of Normalized Difference Vegetation Index (NDVI); (2) performing a hindcasting analysis of cover crop adoption within the Big Pine Creek Watersheds within the period of 2014-2018 by employing a rapid cover crop survey remote sensing techniques; (3) accessing cover crop adoption management tendencies of farmers within the Big Pine Watersheds, and (4) determining the cover crop adoption tenure of farmers within the Big Pine Creek watersheds between 2014 and 2018. The cover crop management tendency represents the farmers’ preference on cash crop rotation method after harvesting cover crops, and the cover crop adoption tenure means that how often farmers adopt cover crops in a specific field in the research period.</a></p> <p>The results of this research demonstrated that relative to the conventional driving transect, remote sensing is a feasible method to successfully detect cover crop adoption on a county and watershed scale. Over a 4-year period (2015-2018), Producer’s Accuracy (PA) under the best COV, which represented how much vegetation-covered field recorded in transect data that can be captured in the processed NDVI map, was 89.02%. This PA value was relatively high compared with previous spatial crop classification research. The rapid remote sensing method also provided individual field locations of cover crop adoption over time within the entire watershed, compared to the driving transect that only gives extrapolated average of adoption. The hindcasting analysis of cover crop adoption revealed a 74% increase in cover crop acreage in the watershed from 2014 to 2018, which equated to a 0.71% increase in land receiving cover crops among all cultivated land annually. The evaluation of farmer cover crop adoption tendencies demonstrated that over a 4-year period, cover crop adoption going into corn was 19.7% greater on average relative to before soybean. Another key finding was that the level of cover crop adoption annually in the watershed was heavily influenced by the cash crop rotation. The cover crop tenure analysis demonstrated that agricultural fields of greater cover crop tenure represented the smallest portion of the cultivated land in the watershed, where 84.2% of the watershed was void of cover crop adoption and field that received cover crops for more than 4 consecutive years represented only 1% of cultivated land.</p> <p> To conclude, we are confident that the rapid cover crop survey method could replace the traditional driving transect survey. Our findings suggest that rapid assessment methods of cover crop adoption involving processed NDVI map could help advance the effectiveness, speed, and accuracy of cover crop adoption and assessment in the state of Indiana and the entire Mississippi River Basin region.</p>

<p dir="ltr">Cover crops and soil residual herbicides are some of the essential tools within the integrated weed management. When used at cover crop termination, residual herbicides can extend the period of weed control and reduce the selection pressure for herbicide resistance. However, previous research has indicated that the use of cover crops can increase the microbial activity of the soil which, in turn, is the primary route for herbicide degradation in the soil. In addition to the potential effect on the microbial breakdown of herbicides, cover crops can also alter the fate of herbicides by interception. Three field projects were established to (1) investigate the influence of cover crop [cereal rye (<i>Secale cereale</i> L.) and crimson clover (<i>Trifolium incarnatum</i> L.)] use on soil enzyme activities [β-glucosidase (BG) and dehydrogenase (DHA)], its effect on the concentration of residual herbicides (sulfentrazone, <i>s</i>-metolachlor, cloransulam-methyl, atrazine, and mesotrione) in the soil, and the interception of herbicides by cover crop residue; (2) to investigate the effect of cover crop termination strategies (fallow, standing, and roller crimped 1 d prior to application) and simulated rainfall volumes (0, 4.2, and 8.3 mm simulated over 20 min; equivalent to 0, 12.5, and 25 mm h^-1) on atrazine wash off from cereal rye biomass onto the soil; (3) to investigate the effect of cereal rye termination strategies on the concentration of sulfentrazone, <i>s</i>-metolachlor, and cloransulam-methyl in the soil, weed control, and soybean [Glycine max (L.) Merr.] yield.</p><p dir="ltr">Results from the first project suggests that the use of cover crops occasionally resulted in increased BG and DHA activities relative to the fallow treatment. However, even when there was an increase in the activity of these two enzymes, increased degradation of the residual herbicides was not observed. Furthermore, the use of cereal rye or crimson clover as cover crops did not reduce the efficacy of the residual herbicides in controlling weeds early in the growing season.</p><p dir="ltr">In regards to the fate of atrazine after simulated rainfall, the results from the second project indicated that cereal rye biomass accumulation negatively impacted the amount of herbicide reaching the soil at the time of application. Although the roller crimped cereal rye reduced the amount of herbicide reaching the soil relative to the standing cereal rye, it also reduced atrazine leaching below the 0-5 cm of soil. Furthermore, in cover cropping systems with high levels of cereal rye biomass, more than 8.3 mm of rain are required to wash most of the atrazine off of the biomass.</p><p dir="ltr">Lastly, the adoption of the planting green systems resulted in up to 84% interception of residual herbicides by the roller crimped cereal rye biomass. The use of cereal rye as cover crop did not improve the weed control relative to the fallow during the two years of field research. Soybean yield losses ranged from 10 to 44% with the adoption of the planting green system, primarily due to stand losses. However, there are strategies and proper equipment available that can be used to minimize soybean stand losses.</p>

Risk, and how one proceeds with uncertainty, are key indicators of behavior. In particular, in observing farmers, risk perception is found to influence the decision to innovate and adopt new crops (Ghadim et al., 2005). Farmers who are more risk-averse tend to be later adopters of new crops, while risk-loving farmers tend to be first adopters (Barham et al., 2014). As such, the recent legal shifts in hemp production laws have prompted many growers eager to test out the crop to do so. A vast majority of current licensees planted less than 50 acres to start, despite being mostly corn and soy producers—implying large acreage access. The American ‘hemp rush’ provides us with a real-time display of adoption behavior and its gendered implications.