Row Orientation and Canopy Position Affect Bud Differentiation, Leaf Area Index and Some Agronomical Traits of a Super High-Density Almond Orchard

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Some quantitative relationships between leaf area index and canopy nitrogen content and distribution.

In a previous study (Yin et al. 2000. Annals of Botany 85: 579-585), a generic logarithmic equation for leaf area index (L) in relation to canopy nitrogen content (N) was developed: L=(1/ktn)1n(1+ktnN/nb). The equation has two parameters: the minimum leaf nitrogen required to support photosynthesis (nb), and the leaf nitrogen extinction coefficient (ktn). Relative to nb, there is less informati...

متن کامل

Estimation of Leaf Area Index and Plant Area Index of a Submerged Macrophyte Canopy Using Digital Photography

Non-destructive estimation using digital cameras is a common approach for estimating leaf area index (LAI) of terrestrial vegetation. However, no attempt has been made so far to develop non-destructive approaches to LAI estimation for aquatic vegetation. Using the submerged plant species Potamogeton malainus, the objective of this study was to determine whether the gap fraction derived from ver...

متن کامل

Mapping almond orchard canopy volume, flowers, fruit and yield using lidar and vision sensors

This paper present a mobile terrestrial scanning system for almond orchards, that is able to efficiently map flower and fruit distributions and to estimate and predict yield for individual trees. A mobile robotic ground vehicle scans the orchard while logging data from on-board lidar and camera sensors. An automated software pipeline processes the data offline, to produce a 3D map of the orchar...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Agronomy

سال: 2021

ISSN: 2073-4395

DOI: 10.3390/agronomy11020251