Egypt is among the world’s largest producers of sugarcane. This crop is of great economic importance in the country, as it serves as a primary source of sugar, a vital strategic material. The pre-cutting planting mode is the most used technique for cultivating sugarcane in Egypt. However, this method is plagued by several issues that adversely affect the quality of the crop. A proposed solution to these problems is the implementation of a sugarcane-seed-cutting device, which incorporates automatic identification technology for optimal efficiency. The aim is to enhance the cutting quality and efficiency of the pre-cutting planting mode of sugarcane. The developed machine consists of a feeding system, a node scanning and detection system, a node cutting system, a sugarcane seed counting and monitoring system, and a control system. The current research aims to study the pulse widths (PW) of three-color channels (R, G, and B) of the RGB color sensors under laboratory conditions. The output PW of red, green, and blue channel values were recorded at three color types for hand-colored nodes [black, red, and blue], three speeds of the feeding system [7.5 m/min, 5 m/min, and 4.3 m/min], three installing heights of the RGB color sensors [2.0 cm, 3.0 cm, and 4.0 cm], and three widths of the colored line [10.0 mm, 7.0 mm, and 3.0 mm]. The laboratory test results s to identify hand-colored sugarcane nodes showed that the recognition rate ranged from 95% to 100% and the average scanning time ranged from 1.0 s to 1.75 s. The capacity of the developed machine ranged up to 1200 seeds per hour. The highest performance of the developed machine was 100% when using hand-colored sugarcane stalks with a 10 mm blue color line and installing the RGB color sensor at 2.0 cm in height, as well as increasing the speed of the feeding system to 7.5 m/min. The use of IoT and RGB color sensors has made it possible to get analytical indicators like those achieved with other automatic systems for cutting sugar cane seeds without requiring the use of computers or expensive, fast industrial cameras for image processing.

Sunflower threshing is one of the most interesting field processes for making the sunflower ready for seed handling, drying, cleaning and oil extraction. One of the biggest problems observed during the sunflower threshing process is the accumulation of threshed crop on the first third of the threshing roller and passing off some unthreshed parts of sunflower heads. To solve the aforementioned problem and optimize the efficiency of the sunflower threshing process, this research was focused on devising and testing a sunflower threshing machine with a close threshing box system equipped with a screw conveyor that evenly distributed the feedstock of sunflower heads on the entire length of the threshing roller. The machine was tested to assess the seed damage rate, unthreshed seed percentage, threshing efficiency, machine productivity, power requirements and specific energy consumption. The evaluation was done under different roller rotational speeds (150, 200, 250 and 300 rpm) and feeding rates (600, 700, 800 and 900 kg/h). The obtained results revealed that the threshing evaluation parameters were affected significantly by the roller rotational speed and feeding rate. The threshing efficiency was observed to rise with the rise in the roller rotational speed, and it also rose with the increasing feed rate up to 800 kg/h and then started to descend. The unthreshed seed percentage decreased with the increase in the roller rotational speed for all feed rates, and it decreased with the increasing feed rate up to 800 kg/h and then started to increase at the higher feed rates. The damaged seed percentage, power requirement and machine productivity increased with the increase of the roller speed and feed rate. The Buckingham π theorem was followed to find an equation to predict the threshing efficiency, resulting in an equation with an R² value of 0.9309. With elimination of the blockage problem and better threshing efficiency, this machine could be a good choice for small- to medium-sized sunflower farms.