The machine-harvested fields are mechanically chipped 2.5–7.5 cm (1–3 in) above the crown and transported to dehydrators.
For multiple harvests, parsley should be cut at least 3 cm (1.25 in) above the crown. Charles, in Handbook of Herbs and Spices (Second Edition), Vol24.2.9 Harvestingĭepending on the crop quality, multiple harvests of parsley are possible by machine or hand. Proximal optical sensors for nitrogen management of vegetable crops: a review. Red Edge Normalized Difference Vegetation index (RENDVI)Īdopted from Padilla, F.M., Gallardo, M., Peña-Fleitas, M.T., De Souza, R., Thompson, R.B., 2018. Optimized Soil Adjusted Vegetation Index (OSAVI) Green Normalized Difference Vegetation index (GNDVI) Normalized Difference Vegetation index (NDVI) A good choice of crop sensor should consider the crop growth stage, real application conditions and sensing period. The prediction accuracy of VI varied among different sensing devices ( Al-Gaadi et al., 2016) or crop sensors. The use of NDVI and SAVI for potato yield prediction showed moderate to good prediction accuracy ( R 2 = 0.39 to 0.65). However, the NDVI can be used as a proxy to calculate LAI ( Pontailler et al., 2003) and yield prediction ( Pantazi et al., 2016). Later in crop season, high LAI can cause some VI measurements insensitive to the crop responses. During the initial crop growth stage, low LAI and soil light scattering make spectral measurement difficult to isolate crop vegetation from soil ( Huete, 1988). It is considered as an important factor for explaining various physiological processes in crop such as evapotranspiration, photosynthesis, and crop yield ( Price and Bausch, 1995). The NDVI showed a strong correlation ( R 2 = 0.85) with leaf area index (LAI) ( Sankaran et al., 2015), which is defined as the total leaf area per unit of ground area ( Watson, 1937). Among all VIs, the normalized difference vegetation index (NDVI) ( Sellers, 1985) is probably the most widely reported and used vegetation index ( Padilla et al., 2018). The VIs must be measured directly from the crop canopy although some other specific vegetation indexes differentiate crop vegetation from the soil surface, for example, the soil adjusted vegetation index (SAVI) ( Huete, 1988). One should be wise to choose an optimal VI and/or their combinations for accurate estimation of crop yield ( Chlingaryan et al., 2018). Some of the most commonly used VIs are presented in the Table 3, although > 100 VIs have been reported ( Bannari et al., 1995 Ollinger, 2011 Xue and Su, 2017) for different applications. Vegetation indices are mathematical combinations of several spectral bands mainly the red, green and infrared wavelengths, and they are designed to find functional relationships between crop characteristics and sensing observations ( Wiegand et al., 1989). Therefore, a group of vegetation indexes (VIs) are being repeatedly reported for monitoring crop quality and predicting crop yield ( Marino and Alvino, 2014). Early detection of crop biotic and abiotic stresses is also essential to reduce yield losses and increase profitability. Assessment of overall crop growth and health condition cannot be done directly by measuring crop morphological attributes. Canopy dimensions including crop height, width and volume were widely considered to develop variable rate recommendation ( Rüegg et al., 1999 Viret et al., 2007). Multiple studies reported the use of canopy information as potential indicators to predict crop yield ( Villalobos et al., 2006 Zaman et al., 2006) and biomass production ( Ehlert et al., 2008). Crop canopy and it's geometric characteristics are the key indicators of crop growth and productivity ( Lee and Ehsani, 2009). Crop quality indicators can be used as the measure of crop health and yield potentiality.
0 kommentar(er)
