Apparent Thermal Conductivity of Mulch Materials Exposed to Forced Convection

Soil temperature controls plant growth and many related processes in the soil. A mulch or crop residue covering the soil may alter soil temperatures significantly. Available simulation models often lack experimental data for the mulch thermal conductivity and its dependence on air velocity. The apparent thermal conductivity (k) of wheat straw, pine straw, tire chips, dry sandy soil, and the thermal resistance of Bermudagrass sods were measured using a guarded hot plate at air velocities between 0 and 5 m/s. For all mulch materials, k ranged between 0.1 and 0.6 W m–1 °C–1, and increased with increasing air velocity, except for the more compact materials such as soil and, to a lesser extent, small tire chips. We found a minimum in k around 1 m/s for the thicker (\u3e 0.1 m) layers of wheat straw and pine straw, which was tentatively attributed to interactions between the straw and the convection (free versus forced mechanism at the 1 m/s velocity). A model was created for predicting apparent thermal conductivity through mulches in thermally unstable environments. Using estimated mulch opacity parameters and fitting convection parameters, r2 values ranging from 0.72 to 0.99 were obtained. The model may be used in field situations where the soil under a mulch is warmer than the air above the mulch, which is a typical nighttime condition. The model should be tested using independently measured data

Measurement And Modeling Of Heat Transfer Mechanisms In Mulch Materials

Crop residues or mulches affect soil temperature influencing plant growth and related processes in the soil. A hot/cold plate combination was used to quantify heat transfer through several common dry test mulch materials (rubber chips, pine straw, wheat straw) and identify and quantify heat transfer mechanisms with the goal of modeling apparent thermal conductivity of the mulch. Mulch material bulk densities ranged from near 0 kg/m3 to 33 kg/m3 , mulch thickness ranged from 61 mm to 140 mm and test temperatures ranged from 20°C to 45°C. To determine the effect of thermal radiation on heat transfer, measurements were taken with the test material between both a set of low emissivity aluminum (Al) plates and a set of high emissivity black painted plates. To quantify free convection, measurements were made in a thermally unstable configuration with the hot plate on the bottom and the cold plate on top and in a thermally stable configuration with the cold plate on the bottom and the hot plate on top. In thermally unstable situations (i.e., bottom plate hot, top plate cool), free convection and conduction mechanisms best explained the heat flux. In thermally stable conditions, radiation and conduction best explained heat flux. The percentage of heat due to thermal radiation decreased as mulch thickness and density increased in both the thermal stable and unstable conditions. The percentage of heat transfer due to free convection (unstable case) and due to conduction (stable case) generally increased as mulch thickness and density increased. For a given mulch material, the thermally unstable condition results in an increased apparent thermal conductivity (k) value. The difference between the k values for stable and unstable cases tended to diminish with pine straw or wheat straw mulches compared to air. Increasing the mulch thickness (plate spacing) resulted in the most difference with low mulch densities or no mulch. Differences are probably not statistically meaningful at the high mulch densities. For pine straw the average k was 0.11 W m–1 K–1 and for wheat straw 0.08 W m–1 K–1. Models were created to develop the radiation, conduction and convection parameters for the mulches tested, with r2 values for the estimated parameter fit ranging from 0.75 to 0.99. These models could be used to estimate the apparent k of dry mulches in the field

Development Of Hot/Cold Plate Apparatus For Determining Heat Transport Mechanisms In Mulch Materials

To study the effects of mulches and crop residues on soil temperature, researchers have frequently used simulation models. In such models, quantification of heat transport within the mulch material is often weak and heat transport mechanisms are poorly understood. In this paper we describe an apparatus to quantify heat transport through dry mulch materials. In addition, heat transport mechanisms (conduction, thermal radiation, free and forced convection) can be identified and quantified using this apparatus. The apparatus consists of precisely controlled and monitored 0.9 m by 0.9 m hot and cold plates. The hot plate actually consists of three component plates: a test, a guard, and a bottom plate that are individually controlled (temperature) and monitored (temperature and power). The guard plate surrounds the test plate, minimizing undesired lateral heat flow. The bottom plate is positioned in parallel with the test and guard plates to insure that all wattage into the test plate moves off the top of the plate through the mulch. The correct functioning of the hot plate was verified using three reference materials with a known thermal resistance. The cold plate is based on techniques using thermoelectric devices (Peltier coolers). In addition, heat sinks and fans are used to transport heat away from the cold plate. A two–dimensional numerical simulation showed that errors caused by lateral heat flow in a sample contained between the hot and the cold plate can be neglected. The thermal conductivity of air was measured using the apparatus, yielding a value of 0.026 W m–1ºC–1, exactly matching the theoretical value, thus confirming the correct functioning of the hot/cold plate combination

Soil Temperature Under A Dormant Bermudagrass Mulch: Simulation And Measurement

The ENergy and WATer BALance (ENWATBAL) model is a mechanistic, numerical model that simulates soil water and temperature profiles, evaporation from soil, and transpiration from crops, but it does not simulate the effects of a mulch layer. Surface vegetative mulches are becoming more common, especially in reduced -tillage systems, limiting the model’s applicability. Our objective was to modify ENWATBAL to enable physically based simulation of the effects of a dense mulch. As a preliminary evaluation of the model, soil temperatures simulated with the modified model were compared with those measured at Watkinsville, Georgia, in Cecil sandy loam (clayey, kaolinitic, thermic, Typic Kanhapludult) under a dense, thatchy layer of dormant bermudagrass (Cynodon dactylon, [L.] Pers.) that acted as a mulch during the simulation period. Measured daily soil temperature amplitudes at 0.04 m depth were about 2.5ºC during an 8-day period in December 1995. Simulated amplitudes were 12ºC with the original ENWATBAL model (configured for a bare soil) and 3.5ºC with the mulch-enhanced model. The root mean square error between hourly measured and simulated soil temperatures was 4.1ºC using the original ENWATBAL model and 1.1ºC using the mulch-enhanced model. Measured soil temperatures lagged behind those simulated, indicating that conduction may be an important process of heat transfer through the mulch. Two solution methods were tested: an iterative solution for mulch and soil surface temperatures implicit in the energy balance equations, and a linearized explicit solution of the energy balances. The latter method was 50 times faster than the iterative method without compromising accuracy; the largest linearization error was only 0.01ºC. The capability to simulate mulch effects increases the scope of problems where ENWATBAL is applicable

Modeling Product Flow Through a Generic Post-Harvest Distribution System

A spreadsheet-based stochastic model was developed to track fruit numbers and fruit value for 1,000 individual items grown in a farmer's field, sorted at a packinghouse with and without advanced inspection technology, distributed with and without repack, and sold at a retail store. The quantities generated at each step are value per unit volume in the production field and the respective price multipliers and passing fractions at the packinghouse, distribution center, and retail store. Values of these coefficients were set to reflect experience with the onion industry. It was assumed that about 30% (with repackaging) to 40% (without repackaging) of the fruit leaving the farmer's field would reach the consumer. The initial price per unit volume and pricing multipliers were configured to give representative prices at the production field and representative price per unit fruit at steps through the system to the consumer. The pass-through percentage was decreased an extra 10% to 15% with technology and up to 20% with repack, with corresponding increases in subsequent steps to maintain the 25% to 25% total pass-through. Repacking and technology addition in the packinghouse tended to result in increased value at the retail level. Placing technology in the packinghouse did not result in increased value for the packinghouse. Vertical integration that included the packinghouse would be required to make it profitable to add sorting technology that increases quality by removing defective items. Both technology addition and repackaging reduce the total number of fruits reaching the consumer. The model suggests that the notion of early removal of fruits with latent damage to avoid increased distribution costs does not really benefit the consumer for the conditions modeled. Additional considerations such as food security are required for one to expect additional equipment adoption under current scenarios

Modeling Product Flow Through a Generic Post-Harvest Distribution System

A spreadsheet-based stochastic model was developed to track fruit numbers and fruit value for 1,000 individual items grown in a farmer's field, sorted at a packinghouse with and without advanced inspection technology, distributed with and without repack, and sold at a retail store. The quantities generated at each step are value per unit volume in the production field and the respective price multipliers and passing fractions at the packinghouse, distribution center, and retail store. Values of these coefficients were set to reflect experience with the onion industry. It was assumed that about 30% (with repackaging) to 40% (without repackaging) of the fruit leaving the farmer's field would reach the consumer. The initial price per unit volume and pricing multipliers were configured to give representative prices at the production field and representative price per unit fruit at steps through the system to the consumer. The pass-through percentage was decreased an extra 10% to 15% with technology and up to 20% with repack, with corresponding increases in subsequent steps to maintain the 25% to 25% total pass-through. Repacking and technology addition in the packinghouse tended to result in increased value at the retail level. Placing technology in the packinghouse did not result in increased value for the packinghouse. Vertical integration that included the packinghouse would be required to make it profitable to add sorting technology that increases quality by removing defective items. Both technology addition and repackaging reduce the total number of fruits reaching the consumer. The model suggests that the notion of early removal of fruits with latent damage to avoid increased distribution costs does not really benefit the consumer for the conditions modeled. Additional considerations such as food security are required for one to expect additional equipment adoption under current scenarios.Agribusiness,