Estimation of Dry Matter Yield in Mediterranean Pastures: Comparative Study between Rising Plate Meter and Grassmaster II Probe

João Serrano (), Júlio Franco, Shakib Shahidian and Francisco J. Moral
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João Serrano: MED—Mediterranean Institute for Agriculture, Environment and Development and CHANGE—Global Change and Sustainability Institute, University of Évora, Mitra, Ap. 94, 7006-554 Évora, Portugal
Júlio Franco: MED—Mediterranean Institute for Agriculture, Environment and Development and CHANGE—Global Change and Sustainability Institute, University of Évora, Mitra, Ap. 94, 7006-554 Évora, Portugal
Shakib Shahidian: MED—Mediterranean Institute for Agriculture, Environment and Development and CHANGE—Global Change and Sustainability Institute, University of Évora, Mitra, Ap. 94, 7006-554 Évora, Portugal
Francisco J. Moral: Departamento de Expresión Gráfica, Escuela de Ingenierías Industriales, Universidad de Extremadura, Avenida de Elvas s/n, 06006 Badajoz, Spain

Agriculture, 2024, vol. 14, issue 10, 1-25

Abstract: This study evaluates two expedient electronic sensors, a rising plate meter (RPM) and a “Grassmaster II” capacitance probe (GMII), to estimate pasture dry matter (DM, in kg ha −1 ). The sampling process consisted of sensor measurements, followed by pasture collection and a laboratory reference analysis. In this comparative study, carried out throughout the 2023/2024 pasture growing season, a total of 288 pasture samples were collected in two phases (calibration and validation). The calibration phase (n = 144) consisted of measurements on three dates (6 December 2023, 29 February and 10 May 2024) in 48 georeferenced sampling areas of the experimental field “Eco-SPAA” (“M G ” field), located at Mitra farm (Évora, Portugal). This pasture is a permanent mixture of various botanical species (grasses, legumes, and others) grazed by sheep, and is representative of biodiverse dryland pastures. The validation phase (n = 144) was carried out between December 2023 and April 2024 in 18 field tests (each with eight pasture samples), in three types of representative pastures: the same mixture for grazing (“M G ” field), a commercial and annual mixture for cutting (mowing) and conservation (“M M ” field), and legumes for grazing (“L G ” field). The best estimation model for DM was obtained based on measurements carried out in February in the case of the GMII probe (R 2 = 0.61) and December 2023 and February 2024 in the case of RPM (R 2 = 0.76). The estimation decreased very significantly for both sensors based on measurements carried out in May (spring). The validation phase showed greater accuracy (less RMSE) in “M G ” field tests (RMSE of 735.4 kg ha −1 with GMII and 512.3 kg ha −1 with the RPM). The results open perspectives for other works that would allow the testing, calibration, and validation of these electronic sensors in a wider range of pasture production conditions, in order to improve their accuracy as decision-making support tools in pasture management.

Keywords: dryland pasture productivity; proximal sensors; calibration; validation; Montado ecosystem (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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