Abstract:

The development of software that facilitates the application of theoretical concepts to solve problems in specific case studies designed by the student may have a major role in the teaching-learning process in engineering. Fertilizer recommendation is a crucial task in managing sustainable agricultural systems that look for an efficient use of resources and a minimum environmental impact. However, selecting the best management alternatives of fertilizers, either organic or mineral, is a complex task, as it requires integrating knowledge on crops, soils and nutrient cycling tailored to a particular crop rotation. The aim of this study is to describe the potential application of the Windows software FertiliCalc to teach fertilizer management in Bachelor and Master degrees related to agriculture. This software calculates the required seasonal N, P and K rates, and the best combination of commercial fertilizers. It also provides estimates of the Ca, Mg and S balances, acidification risk, and N losses. Novel aspects of the calculations include the development of stochastic flexible fertilizer programs for N. Regarding P and K, estimations are based on threshold values of common availability indexes. It also allows selection of the best complex fertilizer for pre-plant applications to avoid blending of simple fertilizers at the farm. The software has been developed in up to 87 languages and can be downloaded freely from the web page that also provides access to a manual and bibliographic material in which the program is based. The effect of FertiliCalc as a learning tool was assessed by mean of a pre-test-post-test design applied to a group of 24 students of the third year of the School of Agriculture Engineering (Universidad Politécnica de Madrid). A knowledge survey that contained 20 questions was answered by the students before practicing with FertiliCalc. Then, the students attended lectures (4 hours) explaining the program, its connections with basic concepts on fertilizer management and doing simple exercises to be capable of using the program. Afterwards, the students worked with the program over 2 hours by themselves. After these lectures and working sessions, students answered the same survey a second time. For each student a pre- and a post-test score was calculated as the percentage of correct answers in each test. The mean, median and standard deviation were calculated for the pre- and post-test scores. Comparison of students pre- and post-test scores was also conducted by one-way analysis of variance and graphical representation of students scores. The mean pre-test score of the students was 41% and the median 36%, whereas for the post-test score the mean and the median were 54%. The post-test score was significantly higher (p>0.001) than the pre-test. Overall, 18 students increased their scores, 2 had the same and 4 slightly decreased their scores. The graphical representation showed that students that already had a basic knowledge (pre-test score > 20) were able to increase more their learning. FertiliCalc showed high potential for being used as a teaching tool since it helps understanding the rationale behind fertilizer management.

Keywords:

Agriculture, Agronomy, Decision tools, Fertilizers, Pre-Test-Post-Test assessment, Virtual lab.