Agriculture Reference
In-Depth Information
can also be integrated with embedded microcontrollers to form “mechatronic” sys-
tems on agricultural machinery. Recent advances in miniaturization and networking
of microprocessors have been gradually permeating into many agricultural applica-
tions. Progress has been reported recently on agri-robotics, auto-guidance systems,
real-time controls, in-field environment, machinery, crop remote monitoring, and
integrated data management and decision support systems. These advanced tech-
nologies have been contributing to the increases in productivity and sustainability of
agriculture production and process.
Precision agriculture (PA) technology has been promoted and implemented
around the world in the past decades. The factual base of PA is the spatial and tempo-
ral variability of soil and crop factors between and within fields. Before the comple-
tion of agricultural mechanization, the very small size of fields allowed farmers to
monitor the field conditions and vary treatments manually. With the enlargement of
fields and intensive mechanization, crops have been treated under “average/uniform”
soil, nutrient, moisture, weed, insect, and growth conditions. This has led to over-/
underapplications of herbicides, pesticides, irrigation, and fertilizers. PA presents
a system approach targeting at reorganizing the production system toward a low-
input, high-efficiency, sustainable agriculture. This new approach benefits from the
emergence and convergence of several technologies, including Global Positioning
System (GPS), geographic information system (GIS), miniaturized computer com-
ponents, automatic control, in-field and remote sensing, mobile computing, advanced
information processing, and telecommunications. Various sensors and actuators
with intelligence (i.e., “smart sensors”) have been used for data acquisition, field
monitoring, and treatment controls. The goal of the PA approach is to
improve the
productivity and sustainability of agricultural production by treating the right plant
at the right place at the right time.
Nowadays, agricultural production management
or the so-called “worksite management” can be based on detailed in-field spatial and
timely information to make relevant, specific decisions on crop/field treatments and
machinery operations.
13.2 REAL-TIME WORKSITE MANAGEMENT SYSTEM
In agricultural production, the term “worksite” often refers to fields where farming
operations are needed. Many categories of information are important in order to
optimize worksite management, which includes (1) agronomic information including
soil, plant, and environment; (2) information regarding any agricultural operations;
and (3) marketing and economical information of products. Agronomic informa-
tion describes field conditions. For example, soil conditions can be obtained from
soil moisture, soil conductivity, and surface temperature measurements. They are
often used to determine the schedule of irrigation. Crop height, leaf color, and stalk
diameter at a certain growth stage are used to select relevant chemical treatments.
Weather data including solar radiation, rainfall, and wind speed have been playing
an important role in decision-making on farming operations. Information on agri-
cultural operations is mainly acquired from farm machinery in order to optimize
their use efficiency. For example, location, current/completed operations, the and
fault/failure report of machinery have been used to optimize management plans.
