# Evaluation of an Optical Sorter Effectiveness in Separating Maize Seeds Intended for Sowing
## 1 Introduction  
Optical sorting is an emerging automated process for separating solid products using spectral cameras and lasers. Optical sorters may identify the color, size, form, structural characteristics, and chemical composition of an object depending on the types of sensors employed and the software-driven processing system. Optical sorting is one of the fields in which the most recent developments in artificial intelligence may be successfully used. The increasing spread of artificial intelligence applications, which may augment human and equipment capacities, is revolutionizing the production framework and task automation [1; 2; 3; 4]. Testing and validation operations are essential components of all system engineering architectures. In the final phases of a complex technical flow design, the testing phases have the role to determine whether the quality requirements are met and whether installing additional components in the system is financially justified. Engineers are responsible for creating and building systems that are not only reliable but also flexible in response to changing demands. Technicians use a variety of methods and techniques, such asdesign matrices and constraint analysis, to build systems that satisfy the requirements of all stakeholders [5; 6; 7]. Certified seed production plays an extremely important role in obtaining increased quantities of fruits and vegetables and helps in the implementation of emerging agricultural technologies. This influence can determine an increase in the level of the agricultural harvest by up to 30%; therefore, seed production has received high research attention in recent years [8; 9; 10]. There are several factors that might affect agricultural crop production, starting with the influence of the planting material, culture technology, soil type, water availability, or phyto-sanitary treatments [11; 12; 13]. The careful selection of appropriate seedlings is one of the key factors in developing optimal growth of grain crops. To ensure that the crop has appropriate genetic features for a particular environment and use, the seeds must be selected for an appropriate genetic mix [14; 15; 16]. In the seed production activity, the professional requirements are higher, and the work technology is more demanding and requires more technical equipment [17]. The efficiency of seed production is conditioned by the existence of some technological links without which it is not possible to produce seed lots (irrigation, fertilization, and maintenance of crops through specific works (purified, etc.)). Thus, there is a need for technological discipline, professional training, and high-performance equipment [17; 18]. Obtaining quality seeds and maintaining the initial characteristics of the variety or hybrid is performed according to special techniques, methods, scientific studies, and research [19; 20; 21]. The growing demands for modern agriculture, such as low input, high efficiency, and sustainable development, have made the transition to the concept of precision seeding systems [22; 23; 24]. Thus, the mechanization of agriculture has gradually transformed into \"intelligent agriculture\" as a result of advancements in agricultural science and technology. These concepts include novel agricultural machinery, the precise application of agricultural technologies, and improved management of agricultural production [25; 26; 27; 28]. As maize seeds vary in size and shape depending on many factors, special batches of corn seeds are calibrated and labeled appropriately in order to achieve the highest level of seed uniformity [29; 30; 31; 32]. However, the processing of seeds intended for planting includes a complex set of operations aimed at removing all impurities and non-compliant seeds, correcting humidity, sizing, grinding, dredging, chemical treatment, etc. These tasks are carried out by using improved machines and aggregates, grouped in installations that are currently called seed conditioning stations [33; 34; 35; 36; 37].