Predictable Scenarios of Fuzzy Logic Analysis for Sprinkler Irrigation Control

MATLAB will be utilized to validate the various irrigation systems and report it; the air temperature, wind, and humidity will be member functions to improve the efficiency of irrigation performance before the irrigation process, and the fuzzy information system consists of fuzzy rules, which are derived from information of experts or from input-output learning of the system. Rules mimic human reasoning. Mamdani method is mostly applied in the fuzzy inference technique, and the generalized bell function is used for both of temperature and wind where the triangular function used for humidity. The principles were based on the last experiments and personal experiences, and the output will change into a crisp value from this procedure of defuzzification. There are many different methods to do defuzzification, but the most common technique is centroid method. The resultant surface graphic is enough to monitor, validate, and report the irrigation system efficiency to execute and schedule the irrigation practice management.

Introduction to Precision Agriculture

The global population is increasing at a tremendous speed; thus, the demand for safe and secure food to meet this population is in demand. Therefore, traditional farming methods are insufficient to meet this demand; thus, the next revolution in agriculture is required, which is Precision Agriculture (PA), the Fourth Agriculture Revolution. PA is a technology where the concept of farm management is based on observation, measuring, and responding to inter- and intra-field variability in crops. The technologies used for performing precision agriculture are mapping, global positioning system (GPS), yield monitoring and mapping, grid soil sampling application, variable-rate fertilizer application, remote sensing, geographic information systems (GIS), quantifying on farm variability, soil variation, variability of soil water content, time and space scales, robots, drones, satellite imagery, the internet of things, smartphone, and machine learning. Hence, the current chapter will be emphasizing the overview, concepts, history, world interest, benefits, disadvantages, and precision farming needs.

A Web-Based Platform for Crop-Specific Data Management and Exchange of Farmers' Experiences

In this chapter, the research theme is focused on the relationship between small farmers and information and communication technologies (ICT). Although there are other previous works that have already analyzed this same relationship, the authors believe that access to information remains a major challenge for farmers. With the application of workshops on agricultural practices of maize, in communities of Oaxaca and Veracruz, they learned about the practices of farmers around the production cycle and applied a survey to find out their opinion regarding the use of ICT. In addition, they used a specialized database to complement the workshops objectives. Next, in collaboration between researchers in the areas of biology and computing, they developed a web platform for access and use of information related to the variables of interest to farmers. Among the main results, they highlight that the community prefers to use cell phones to access such information and that the older generations are looking to transmit experiences and knowledge to the young with the aim of conserving ancestral knowledge.

On the Use of Artificial Intelligence Techniques in Crop Monitoring and Disease Identification

The use of technology for the purpose of improving crop yields, quality and quantity of the harvest, as well as maintaining the quality of the crop against adverse environmental elements (such as rodent or insect infestation, as well as microbial disease agents) is becoming more critical for farming practice worldwide. One of the technology areas that is proving to be most promising in this area is artificial intelligence, or more specifically, machine learning techniques. This chapter aims to give the reader an overview of how machine learning techniques can help solve the problem of monitoring crop quality and disease identification. The fundamental principles are illustrated through two different case studies, one involving the use of artificial neural networks for harvested grain condition monitoring and the other concerning crop disease identification using support vector machines and k-nearest neighbor algorithm.

Precision Agriculture

Precision agriculture is a management system that aims to reduce inputs like seeds, water, and energy; protect the environment; and maximize profitability. Precision agriculture uses advanced technology like positioning technology, geographical information systems, satellite navigation, and remote sensing. There are different factors affect the adoption of precision agriculture like farm size, legal affairs, and social interaction. Under climate change and increases in world population, adoption of precision agriculture could assist farmers to face various challenges to achieve ideal production and maximizing profitability. Information, technology, and management are considered the backbone of the precision agriculture system, and combining these elements reduces inputs and maximizes productivity. Different threats attacked precision agriculture including threats to confidentiality, threats to integrity, threats to availability, and crowding of the spectrum signal. This chapter explains the different roles of precision agriculture in developing agricultural production.

The Role of the Institutional, Assistance, and Source Information Analysis on Food Security and Extension Policy

The chapter aims to analyze the role of institutional sources of funding/assistance, source information in term of food security and extension policy. The results of the research show the information on problematic areas in policy implementation with respect to food security and extension policy in term of poverty reduction. The role of the institutional, assistance, and source information is useful in the implementation of other policy sectors in the future, because similar issues or problems may be avoided by taking precautions not to repeat the same mistakes or by applying measures which address the implementation issues. In this way, policy implementation can be carried out effectively, and the outcomes will meet the policy objectives.

Raising the Efficiency of Seohen's Model to Predict Soil Resistance Faced by Chisel Plow

This research was carried out to study the effect of crop factor, which is represented in some plant roots of crops residues (broad bean and wheat) on soil mechanical properties (cohesion strength, C, and internal friction angle, Φ), and thus, the effect of these roots on the power requirements of chisel plow to face the soil resistance was studied. Soil mechanical properties and power requirements of chisel plow (7 blades) were measured in the field directly at various soil depths of (0.05, 0.1, 0.15, and 0.2 m) with and without roots at constant tractor forward speed of about 4 km/h. Moisture content of the soil, broad bean roots, and wheat roots were 21%, 16%, and 14%, respectively, The results showed that the effect of roots of previous crops residues had a significant effect on the soil mechanical properties and power requirements for chisel plow when using the crop factor, which is represented in characteristic of crop residual roots in terms of root mean diameter.

Precision Management Practices for Legal Cultivation of Cannabis (Cannabis sativa L.)

Cannabis (Cannabis sativa L.) growers worldwide lack reliable and research-based information about precision management practices (PMP) of cannabis. The history, legal framework, and PMP for cultivation of cannabis have been reviewed with special emphasis on water management, nutrient management, and disease control for optimum cannabis production. The aim is to provide guidelines for precision farming of cannabis to meet fibrous and medicinal needs of the humankind. Therefore, the scope of this chapter is for the potential of hemp cultivation to meet industry needs of fiber and medicine. Methods of irrigation scheduling, nutrient applications, and keeping greenhouse hygienically clean for disease-free (i.e., powdery mildew) hemp production are discussed. Reviewed and recommended application rates of irrigation and nutrients, and environment controls have been tabulated. Chemical, biological, and physical controls of PM control and crop input requirements for disease-free cultivation of hemp are presented.

An Overview of Internet of Things Technology Applied on Precision Agriculture Concept

The internet of things (IoT) is characterized by devices that communicate without human interference, sending and receiving data online, to which they have shaped the way of connecting household appliances, machines, and equipment, cars, among other things, also arriving at the field through characterized by the communication between devices, sensors, drones, and machines. They have great potential to improve production processes, making agriculture increasingly digital, creating solutions, connectivity, and training for specialist labor. As well as irrigation systems and other intelligent machines with the ability to talk to each other enabling management in the use of energy, resources, and inputs making the production process more efficient. Precision agriculture encompasses a series of components and factors from which the best procedures can be chosen that are appropriate in a given agricultural operation that effectively meets your needs, also related to the application of inputs at the right time and in the right place, following the growth and productivity over the entire length of a plantation by controlling pests, among other technologies, providing a reduction in production costs and spending on inputs, reducing the pollution of nature by the pesticides used, making it possible to reduce operating costs, increasing precision in obtaining results in the same way as less variability in production. Therefore, this chapter aims to provide an updated overview and review of the use of the internet of things in the precision agriculture system showing and approaching its success relation, with a concise bibliographic background, categorizing and synthesizing the potential of both technologies.

Lipids in Ruminant Nutrition and Its Effect on Human Health

Scientific evidence and nutritional guidelines recommend a reduction in total fat intake, particularly of saturated fatty acids, which are associated with an increased risk of obesity, hypercholesterolemia, and cancer. Nutritionists recommend a higher intake of polyunsaturated fatty acids (PUFA), especially n-3 PUFA at the expense of n-6 PUFA. Besides the beneficial effects of n-3 fatty acids on human health, the conjugated linoleic acid (CLA) isomers have attracted increased attention as a result of their health promoting biological properties. As milk and meat are the main sources of CLA for human consumption, increasing such important nutrient in animal products is strongly recommended. Fat supplementation is one of the methods of increasing PUFA content in ruminant products, and it has been shown that PUFA can be increased in milk by supplementation with vegetable oils and oil seeds. Vegetable oils as equivalent to oilseeds show similar effects on CLA content in ruminant products.