The impact of balsamo (Myroxylon balsamum L. Harms) on coffee yield and household income in El Balsamar, El Salvador

El Balsamar is a community that relies upon coffee trees intercropped with the balsamo tree (Myroxylon balsamum L. Harms) for a substantial portion of household income. The balsamo tree is valued for its resin which is used as medicine in the community and sold commercially. Farmers believe that the shade from the balsamo tree decreases coffee yield compared to the shade from non balsamo species. Thirty coffee farms were studied, each set up as a paired plot. When cover type was balsamo, coffee yield was more likely to decrease. Plots with higher basal area were more likely to be balsamo cover type. As basal area increased, coffee yield decreased. Although coffee yield is lower under balsamo cover type, farmers still continue to plant and manage coffee under this cover type. Farmers accept a lower coffee yield because balsamo resin provides an important income source. Farmers rely on the community cooperative to provide them work to support their households. The cooperative relies on the farmers to provide the labor needed to harvest coffee and extract balsamo resin.

Planting and production of switchgrass (Panicum virgatum L.) as a bioenergy crop in Michigan's Upper Peninsula

Switchgrass (Panicum virgatum L.) is a perennial grass holding great promise as a biofuel resource. While Michigan’s Upper Peninsula has an appropriate land base and climatic conditions, there is little research exploring the possibilities of switchgrass production. The overall objectives of this research were to investigate switchgrass establishment in the northern edge of its distribution through: investigating the effects of competition on the germination and establishment of switchgrass through the developmental and competitive characteristics of Cave-in-Rock switchgrass and large crabgrass (Digitaria sanguinalis L.) in Michigan’s Upper Peninsula; and, determining the optimum planting depths and timing for switchgrass in Michigan’s Upper Peninsula. For the competition study, a randomized complete block design was installed June 2009 at two locations in Michigan’s Upper Peninsula. Four treatments (0, 1, 4, and 8 plants/m2) of crabgrass were planted with one switchgrass plant. There was a significant difference between switchgrass biomass produced in year one, as a function of crabgrass weed pressure. There was no significant difference between the switchgrass biomass produced in year two versus previous crabgrass weed pressure. There is a significant difference between switchgrass biomass produced in year one and two. For the depth and timing study, a completely randomized design was installed at two locations in Michigan’s Upper Peninsula on seven planting dates (three fall 2009, and four spring 2010); 25 seeds were planted 2 cm apart along 0.5 m rows at depths of: 0.6 cm, 1.3 cm, and 1.9 cm. Emergence and biomass yields were compared by planting date, and depths. A greenhouse seeding experiment was established using the same planting depths and parameters as the field study. The number of seedlings was tallied daily for 30 days. There was a significant difference in survivorship between the fall and spring planting dates, with the spring being more successful. Of the four spring planting dates, there was a significant difference between May and June in emergence and biomass yield. June planting dates had the most percent emergence and total survivorship. There is no significant difference between planting switchgrass at depths of 0.6 cm, 1.3 cm, and 1.9 cm. In conclusion, switchgrass showed no signs of a legacy effect of competition from year one, on biomass production. Overall, an antagonistic effect on switchgrass biomass yield during the establishment period has been observed as a result of increasing competing weed pressure. When planting switchgrass in Michigan’s Upper Peninsula, it should be done in the spring, within the first two weeks of June, at any depth ranging from 0.6 cm to 1.9 cm.

Sediment yield reduction in an agricultural watershed

With proper application of Best Management Practices (BMPs), the impact from the sediment to the water bodies could be minimized. However, finding the optimal allocation of BMP can be difficult, since there are numerous possible options. Also, economics plays an important role in BMP affordability and, therefore, the number of BMPs able to be placed in a given budget year. In this study, two methodologies are presented to determine the optimal cost-effective BMP allocation, by coupling a watershed-level model, Soil and Water Assessment Tool (SWAT), with two different methods, targeting and a multi-objective genetic algorithm (Non-dominated Sorting Genetic Algorithm II, NSGA-II). For demonstration, these two methodologies were applied to an agriculture-dominant watershed located in Lower Michigan to find the optimal allocation of filter strips and grassed waterways. For targeting, three different criteria were investigated for sediment yield minimization, during the process of which it was found that the grassed waterways near the watershed outlet reduced the watershed outlet sediment yield the most under this study condition, and cost minimization was also included as a second objective during the cost-effective BMP allocation selection. NSGA-II was used to find the optimal BMP allocation for both sediment yield reduction and cost minimization. By comparing the results and computational time of both methodologies, targeting was determined to be a better method for finding optimal cost-effective BMP allocation under this study condition, since it provided more than 13 times the amount of solutions with better fitness for the objective functions while using less than one eighth of the SWAT computational time than the NSGA-II with 150 generations did.