Developing an in-Field Yield Monitoring System and Predicting Some Nutritional Quality Properties of Alfalfa Using Shear and Compressive Energy

ماشین های کشاورزی

Article 6, Volume 4, Issue 2 - Serial Number 8, 2014, Pages 184-193   

Document Type: Research Article

DOI: 10.22067/jam.v4i2.28114

Authors

M. Maharlooei; M. Loghavi^* ; S. M. Nassiri

Shiraz University

Abstract

Precision Agriculture is continuously trying to address the sources and factors affecting the in-field variability and taking appropriate managerial decisions. One of the popular research focuses in the recent three decades has been on the development of new approaches to making yield variability maps. Advancement in development of sensors and the importance of quality factor in high value crops has motivated scientists to investigate real-time and nondestructive testing methods. This study tried to introduce and evaluate a new approach to concurrent yield mapping and to estimate some nutritional qualitative factors of alfalfa production. In this study, yield quantity was determined by measurement of added hay slice in every hay compression cycle by employing a new star wheel and integrating its output with positioning data from Global Positioning System. To predict some nutritional quality properties, measurement of specific shear energy applied on the cutting blade and compressive energy on plunger head of a hay baler in field conditions were also evaluated. The results of statistical analysis of yield quantity measurement data showed a very good correlation between the suggested approach and yield mass (r=0.96 and R2=0.92). The results of using specific shear energy for estimation of crude fiber and cumulative index RFV with regard to field conditions were rated as acceptable. Using specific compression energy was suitable only for estimating the dry matter. None of the suggested methods was able to estimate the hay crude protein. Further investigations at more extensive variations of quality indices and alfalfa varieties are suggested.

Keywords

Alfalfa; Nutritional quality indices; Precision agriculture; Quantitative yield