We integrated the construction and operation of hoop houses into a general education course to provide students with basic agriculture skills such as basic agricultural construction, greenhouse crop production, and greenhouse environmental data collection, while immersing them in an experiential learning environment. Students in the class constructed three 12 × 15-ft hoop houses, installed an irrigation system and climate data acquisition system, and grew radish (Raphanus sativus ‘Cherry Belle’) and lettuce (Lactuca sativa ‘Black-Seeded Simpson’) within each hoop house. At the end of the exercise, 86% of students agreed that they knew the basic techniques of hoop house construction, and 89% agreed that they understood the practical application of building a hoop house. More instruction on calculating crop fertilizer requirements would benefit students because only 43% of students agreed or strongly agreed that they understood how to compute crop fertilizer requirements. Climate data demonstrated that air temperature within the unvented hoop houses exceeded the optimal growing temperature for lettuce and radish. We conclude that construction and operation of hoop houses provided practical agricultural skills in an experiential learning environment while revealing subject areas that warrant further instruction.
For farmers to accurately schedule future water delivery for irrigations, a prediction method based on time-series measurements of soil moisture depletion and climate-based indicators of evaporative demand is needed. Yet, numerous reports indicate that field instruments requiring high in-season labor input are not likely to be used by farmers. In New Mexico, pecan (Carya illinoensis) farmers in the Mesilla Valley have been reluctant to adopt new soil-based or climate-based irrigation scheduling technologies. In response to low adoption rates, we have developed a simple, practical irrigation scheduling tool specifically for flood-irrigated pecan production. The information presented in the tool was derived using 14 years of archived climate data and model-simulated consumptive water use. Using this device, farmers can estimate the time interval between their previous and the next irrigation for any date in the growing season, in a range of representative soil types. An accompanying metric for extending irrigation intervals based on field-scale rainfall accumulation was also developed. In modeled simulations, irrigations scheduled with the tool while using the rainfall rule were within 3 days of the model-predicted irrigation dates in silty clay loam and loam soil, and less than 2 days in sandy loam and sand soil. The simulations also indicated that irrigations scheduled with the tool resulted in less than 1% reduction in maximum annual consumptive water use, and the overall averaged soil moisture depletion was 45.14% with an 18.1% cv, relative to a target management allowable depletion of 45%. Our long-term objective is that farmers using this tool will better understand the relationships between seasonal climate variation and irrigation scheduling, and will seek real-time evapotranspiration information currently available from local internet resources.
Accurate measurement of evapotranspiration (ET) is difficult and expensive for large, in-ground container (pot-in-pot) plants. We engineered and used a simple and inexpensive system to determine evapotranspiration of in-ground container trees. The system was shop-assembled and used a block and tackle system attached to a collapsible tripod. A unique container harness system attached to the block and tackle system was used to lift containers that were sunken in the ground. Containers were weighed with a battery-operated balance that was accurate to 1 g (0.04 oz) at its maximum load capacity of 60 kg (132.3 lb). One person operated the system, and the weight of the system exclusive of the balance was 17.5 kg (38.50 lb). Gravimetric water use data obtained with the system werecombined with meteorological data to compute crop coefficients (Kc) of mexican elder (Sambucus mexicana). The system detected small changes in daily water use of mexican elder trees grown in 76-L (20-gal) in-ground containers. Crop coefficients ranged from 0.17 to 0.71. The acquisition of evapotranspiration data from relatively large, containerized landscape plants may be facilitated because the system is simple, inexpensive, and accurate.
Optimal pecan (Carya illinoiensis) production in the southwestern United States requires 1.9 to 2.5 m of irrigation per year depending on soil type. For many growers, scheduling flood irrigation is an inexact science. However, with more growers using computers in their businesses, and with soil moisture sensors and computerized data-collection devices becoming more inexpensive and accessible, there is potential to improve irrigation and water use efficiencies. In this project two low-cost soil monitoring instruments were introduced to a group of pecan producers. They were also given instruction on the use of Internet-based irrigation scheduling resources, and assistance in utilizing all of these tools to improve their irrigation scheduling and possibly yield. The objectives were to determine whether the technology would be adopted by the growers and to assess the performance of the sensors at the end of the season. Three out of the five growers in the project indicated they used either the granular matrix (GM) sensors or tensiometer to schedule irrigations, but compared to the climate-based irrigation scheduling model, all growers tended to irrigate later than the model's recommendation. Graphical analysis of time-series soil moisture content measured with the GM sensors showed a decrease in the rate of soil moisture extraction coincident with the model's recommended irrigation dates. These inflection points indicated the depletion of readily available soil moisture in the root zone. The findings support the accuracy of the climate-based model, and suggest that the model may be used to calibrate the sensors. Four of the five growers expressed interest in continued use of the tensiometer, but only one expressed a desire to use the GM sensor in the future. None of the participants expressed interest in using the climate-based irrigation scheduling model.