Peanut seed, (cv. Hanoch and Congo) were stored both shelled and in-shell at various moisture contents and 15, 20 and 26 C, in an apparatus designed to purge air at relative humidities in equilibrium with the moisture contents of the seed. Storage lasted .nearly 6 months and during this period the moisture contents and germination percentages of the seed were examined periodically.The fesults of germination trials showed significant differences between in-shell and shelled seed for the cv. Hanoch, but not for the cv. Congo. The calculated moisture content required to maintain 90% germination for shelled seeds stored for six months at 15 C was 8.0% for Hanoch and 7.9% for Congo. To conserve the same germination level for 6 months at 26 C, the calculated moisture contents were 7.1% for Hanoch and for Congo.Key Words: Groundnuts, seed storage, germination, temperature, moisture content.Peanut seeds may be stored either in-shell or shelled. A general belief is that seed are better preserved when stored in-shell than after shelling. However, the former method has two disadvantages. The first is that in-shell peanuts occupy a far greater storage volume. The second is that a larger percentage of kernels are damaged mechanically during shelling since the in-shell peanuts were stored at a low moisture content (m.c.) to prevent degradation during storage. The higher the level of broken kernels, the lower the germination percentage of the seeds (5).Two factors known to influence the preservation of peanut seed are temperature and relative humidity (r.h.) (6, 9, 10). Molds that affect the germination power of seed are also influenced by the ambient humidity and temperatures in storage (4). However, literature on the comparative preservation of shelled and in-shell peanut seed is limited. According to Gelmond (S), to preserve peanut seed for one year at 21 C, a m.c. of 5% or less is necessary. Boswell et al. (3) reported on peanut seed preservation at different temperatures and relative humidities.The objective of this investigation was to determine the influence of moisture content on the germination capacity of two peanut cultivars, Hanoch (Virginia type) and Congo (valencia type), when stored both shelled and in-shell at different temperatures. Materials and MethodsThe by water addition to obtain the following kernel m.c.'s for both shelled and in-shell seed: for Hanoch 9.5% and 12.5%; and for Congo, 9.0% and 11.0%. These levels were chosen to obtain m.c.'s of each cultivar in equilibrium with air r.h. of 80 and 90%. After moistening, the seeds were placed in and filled, 2-liter containers. On average each container held one of the following: Hanoch 1400 g shelled (1160 seeds), Hanoch 573 g in-shell (310 seeds), Congo 1420 g shelled (2840 seeds), and Congo 520 g in-shell (676 seeds). Through these, air was purged, whose r.h. had been adjusted to 80% and 90% at 15, 20 or 26 C by bubbling through wash bottles maintained at the respective temperature and containing sulfuric acid at suitable concentrations (11). Flow ...
Truckload (TL) pricing is a major factor that influences the manufacturing and retail costs of products. In the U.S., trucks accounts for more than 90% of freight shipped based on value, and it is expected to grow in the following years. TL price setting is a very complex task for logistic companies as it depends on a number of factors including the logistics carriers' business strategies and other social and economic variables. Understanding TL patterns across the U.S. is important not only for logistic companies, but also for policy makers. TL prices are commonly provided on a dollar per mile rate. Thus the total transportation costs on a route will be the product of the truckload price rate and the distance. More accurate prediction of TL price will enable logistic companies to develop more optimal strategies to operate their transportation activity across destinations and effectively allocate resources on potential demand locations. Freight and economic policy makers will also be able to use this information to explore different potential economic scenarios. This research analyses private data sets (TL rates), and publicly available data such as diesel cost, unemployment, wages, population, and gross state product to understand trends in TL prices. TL rates are evaluated through exploratory and visualization techniques to obtain useful insights. Time series analysis (TSA) and spatial econometric analysis (SEA) are conducted for forecasting TL prices. TSA provides with a general model based on time and delivery distance between origin and destination. Spatial econometric panel models incorporate the spatial dependency, being used for drawing inferences across space, and also for forecasting TL prices. Results indicate that TL prices are closely associated with unemployment, which links the consumer spending with transportation cost. Diesel cost has not impacted TL prices significantly during the last years, as is evidenced in the TSA and SEA. Moreover, in low demand condition such as high unemployment, carriers are likely to serve larger delivery distance in order to reduce TL prices, which impact TL prices in neighboring locations. Increasing the delivery distance by 1.00% was found to reduce the price in dollar-per-mile by about-0.25%, and raise prices in neighboring locations by about +0.05%. Similarly, 1% increase in unemployment rate was found to reduce prices by about-0.30% and increase prices in neighboring locations by about +0.06%. Forecasting models indicate accurate TL price values, with MAPE values less than 10% for the TSA model for estimating an overall monthly price in the U.S.; and less than 20% for the SEA that consider spatial dependence for estimating a yearly price at each U.S. state. This research represents a benchmark in the analysis of freight prices, providing useful insights, identifying significant variables impacting TL prices, and potential methodologies for forecasting truckload prices. iii DEDICATION I would like to dedicate this work to my father Wilder, my mother Graciela, my s...
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