Sugar cane is one of the most important industrial plants which is the first source of sugar production in Iran (about 40-50%). The sugar industry plays a key role among the various industries of the country with the daily supply of energy to the citizens. In addition to household consumption, sugar is of particular importance in the food industry because of its sweetening and volume properties. Sugarcane content is often in the range of 10-15% and in some cases up to 17%. Various factors such as variety and date of planting or harvesting of last year are important to start harvesting. On the other hand, Sugarcane cannot be stored in the factory and its sugars factors are decomposed quickly by storage and sugar cane weight decreases due to loss of moisture. It would be better if the factory consumes more fresh Sugarcane. Therefore, an electronic nose instrument was used to test the variety of Sugarcane syrup and its association with the odors emitted from it to identify the variety of Sugarcane for harvesting time. Four Sugarcane varieties (CP57, CP69, IRC99-02, and CP48) were selected from the Sugarcane sample fields. Linear discriminant analysis (LDA), principal component analysis (PCA) and neural networks (ANN) were used to detect the different Sugarcane varieties. The results showed that all three methods had high accuracy in variety classification. But the LDA and PCA methods performed better than the ANN method. So that, the classification accuracy of Sugarcane varieties was 98. 33%, 97% and 96. 7%, respectively. The results showed the high ability of the olfactory machine to diagnose between the Sugarcane varieties, which can be used as a rapid and low cost instrument in the Sugarcane industry.

Introduction: The performance of agricultural machines depends on the reliability of the equipment used, the maintenance efficiency, the operation process, the technical expertise of workers, etc. As the size and complexity of agricultural equipment continue to increase, the implications of equipment failure become even more critical. Machine failure probability is (1-R) and R is machine reliability, and that 0<R<1 (Vafaei et al., 2010). Moreover, system reliability is the probability that an item will perform a required function without failure under stated conditions for a stated period of time (Billinton and Allan, 1992).

Purpose Sugarcane industries are age-old industrial practices in India which contribute a significant amount of byproducts as waste. Handling and management of these byproducts are huge task, because those require lot of space for storage. However, it provides opportunity to utilize these by-products in agricultural crop production as organic nutrient source. Therefore, it is attempted to review the potential of sugar industries by-products, their availability, and use in agricultural production.Methods A large number of research experiments and literatures have been surveyed and critically analyzed for the effect of Sugarcane by-products on crop productivity and soil properties.Results Application of sugar industries by-products, such as press mud and bagasse, to soil improves the soil chemical, physical, and biological properties and enhanced the crop quality and yield. A huge possibility of Sugarcane industries by-products can be used in agriculture to cut down the chemical fertilizer requirement. If all the press mud is recycled through agriculture about 32, 464, 28, 077, 14, 038, 3434, 393, 1030, and 240 tonnes (t) of N, P, K, Fe, Zn, Mn, and Cu, respectively, can be available and that helps in saving of costly chemical fertilizers.Conclusions Application of Sugarcane industries by-products reduces the recommended dose of fertilizers and improves organic matter of soil during the crop production. It can also be used in combination with inorganic chemical fertilizers and can be packed and marketed along with commercial fertilizer for a particular cropping system. That helps in reduce the storage problem of Sugarcane industries by-products across the India.

The relationship between diversity of plant and arthropod species was studied in Sugarcane fields in Ahwaz, Southern Iran during 1998 to 2001. Strips of alfalfa were planted along the short side of each 250 x 1000 m block. Arthropod species were collected monthly for 24-48 hours using Malaise and pitfall traps which were located inside the Sugarcane blocks. One Malaise trap at 3 meters and two pitfall traps at 2 and 4m from the margin were established in each Sugarcane block. The diversity (species richness) and evenness (relative abundances) of arthropod species were measured by Shannon indices. The percentages of stems attacked by the two stem borers, Sesamia cretica and S. nonagroides (Lepidoptera: Noctuidae) were also recorded on each sampling day. Data was compared for Sugarcane blocks with and without alfalfa strips. Results indicated that species richness was higher and the percentage of infection to stem borers was lower significantly in Sugarcane blocks with strips of alfalfa than without.

Sugarcane pink stem borers, Sesamia spp., are the key pests of Sugarcane in the south of Khuzestan province, Iran. These pests damage heavily the Sugarcane crop and sugar product every year. In this research, spatial dispersion of the stem borers populations were studied in three Sugarcane fields (25 hectare each, Cp69-1062 cultivar) in 2008.Sampling was carried out monthly in seven stages. External symptoms of pest damage were used as a population indicator and the number of infested stems and internodes of Sugarcane were recorded in each sampling station. In order to determine the type of pest spatial dispersion in these three fields, various classical statistics indices were used.In all sampling stages, values of the variance to mean proportion index, index of Patchiness and Morisita’s index were significantly higher than one, and values of 1/k index and Green’s index were higher than zero. The obtained results of all indices indicated that spatial dispersion of Sesamia spp. was aggregated. The regression coefficients of Taylor’s power law b and Iwao’s b were determined 1.45±0.065 and 1.18±0.031, respectively. Thus, they had significant difference from one, and both indicated the aggregated spatial dispersion for the pest life. Based on R2 and P-values of regression analysis, Iwao’s patchiness showed a better fitness for pest spatial dispersion data in comparison with Taylor’s power law.

Sugarcane is cultivated in extensive areas in Khuzestan It is irrigated through hydro-flume and in furrows. For an evaluation of the effect of deficit- irrigation on Sugarcane yield, this experiment was conducted. The treatments consisted of the conventional irrigation method (blank), variable, every other irrigation, (by alternative furrows) and invariable every other irrigation (by fixing the furrow). Results indicated that shifting every other irrigation required the lowest amount of irrigation water in comparison with other treatments. Highest water use efficiency, quality and quantity of Sugarcane belonged to the variable every other irrigation (0.72 kg of sugar per m-3 irrigation water). Conventional irrigation method consumed highest irrigation water and produced lowest quantity of Sugarcane production and water use efficiency (0.48 kg of sugar m-3 irrigation water). Invariable every other furrow irrigation had a Sugarcane production egual to the conventional treatment but water use efficiency was 0.14 kg m-3 more than in the common treatment. From total irrigated waters entering the furrows, about %46.4 and %53.6 were reserved in non- irrigated as against the irrigated furrows respectively.

Sugarcane is an important industrial-agricultural crop in country. Considering the high cultivation level of this product in Khuzestan province and the high volume of data stored in these mechanized agricultural units, it is necessary to have a tool to process stored data. The data mining technique is well equipped to provide Sugarcane manufacturers with the necessary information and patterns in modeling the yield of Sugarcane. One of the most practical of these algorithms is decision trees. The main objective of this research is to predict yield Sugarcane and to evaluate the factors affecting it using decision trees CART and CHAID. The present work was an analytical study conducted on a database containing 13211 records. Data were obtained from farms of Amir Kabir Agro-Industry, during 2013-2016. Data analysis was performed using IBM modeler software version 14. 2 by CRISP methodology. The accuracy of decision tree (CART and CHAID) on the training data and test data were 90, 81, 85 and 79 percent, respectively. The results of this research can be used for Sugarcane production and cultivation industries in Khuzestan Province in order to evaluate and optimize the Sugarcane production process and predict the yield of Sugarcane.

The damage of Sugarcane whitefly, Neomaskellia andropogonic Corbett, has recently increased dramatically in Sugarcane fields in Khuzestan province. In this study, biology of N. andropgonis on four Sugarcane commercial cultivars was evaluated under laboratory conditions. In this experiment, the preimaginal development, adult longevity and fecundity were studied in a growth chamber that was set at 27± 1oC, 60-70%R.H. and 12:12 light dark. The leaf cages were used for the experiment and the cultivars included CP69-1062, CP57-1062, CP48-103 and NCO-310. Mean preimaginal development time was 24.09, 28.06, 27.27 and 26.64 days on the above mentioned cultivars, respectively, producing only female whiteflies. Mean longevity of females was 6, 8.49, 4.15 and 4.60 days on four cultivars, respectively. Females laid 61.80, 58.80, 41.10 and 39.38 eggs on CP69-1062, CP57-1062, CP48-103 and NCO-310 cultivars, respectively. According to the results of this study, the biotic parameters of the pest were lower in CP48-103 and NCO-310 than the other two cultivars.