THE EFFECT OF DOLOMITE AND FERTILIZATION APPLIED ON A TYPICAL GLEISOIL ON THE HARVEST AND QUALITY OF CORN KERNELS

Corn ear damage caused by peeling significantly influence the output and quality of corn harvest. Ear damage recognition is the basis to adjust working parameters and to reduce damage. Image processing is attracting increasing attentions in the field of agriculture. Conventional image processing methods are difficult to be used for recognizing corn ear damage caused by peeling in field harvesting. To address the this problem, in this paper, we propose a peeling damage recognition method based on RGB image. For our method, we develop a dictionary-learning-based method to recognize corn kernels and a thresholding method to recognize ear damage regions. To obtain better performance, we also develop the corroding algorithm and the expanding algorithm for the post-processing of recognized results. The experimental results demonstrate the practicality and accuracy of the proposed method. This study could provide the theoretical basis to develop online peeling damage detection system for corn ear harvesters.

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Sistem Pendukung Keputusan Spesifikasi Biji Jagung Berkualitas Terbaik dengan Metode Multi Attribute Utility Theory

KOMTEKINFO ◽

10.35134/komtekinfo.v5i3.27 ◽

2019 ◽

Vol 5 (3) ◽

pp. 10-19

Author(s):

Chairul Imam ◽

Julius Santony ◽

Yuhandri

Keyword(s):

Decision Support ◽

Decision Support Systems ◽

Utility Theory ◽

Support Systems ◽

High Quality ◽

Multi Attribute Utility Theory ◽

Corn Kernels ◽

Total Price

Farmers sell corn kernels in the company of PT Charoen Pokphan Indonesia Tbk Medan, corn kernels are used to mix feed ingredients to meet the protein values and nutrition of these feeds to be of high quality. The company PT Charoen Pokphan Indonesia Tbk Medan buys corn kernels to farmers by specifying the best quality corn kernels, so they know the total price of corn kernels is in accordance with the quality needed. This research determines the criteria of the best quality types of corn kernels and how to apply the Multi Attribute Utility Theory to decision support systems to determine the quality of corn kernels, to be able to help the company PT Charoen Pokphan Indonesia Tbk Medan in determining the quality of corn kernels. Based on the criteria set out in the company PT Charoen Pokphan Indonesia Tbk Medan to obtain the best quality corn kernels using grade 1 to grade 4 and ranking. The results of testing these methods are produced a decision on an alternative with a total value of 86.7%. So this method is needed to evaluate the determination of the best quality corn kernels to produce the best decisions

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Quality of reading among equipment for determining water content in corn kernels

Semina Ciências Agrárias ◽

10.5433/1679-0359.2020v41n5p1457 ◽

2020 ◽

Vol 41 (5) ◽

pp. 1457-1468

Author(s):

Thais Caroline Rodrigues ◽

◽

Franciele Morlin Carneiro ◽

Rodrigo Garcia Brunini ◽

Patricia Candida de Menezes ◽

...

Keyword(s):

Water Content ◽

Corn Kernels

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Kuantitas dan Kualitas Fodder Jagung, Padi dan Kacang Hijau dengan Waktu Panen yang Berbeda Menggunakan Smart hydroponic Fodder

Jurnal Ilmu Nutrisi dan Teknologi Pakan ◽

10.29244/jintp.19.2.36-41 ◽

2021 ◽

Vol 19 (2) ◽

pp. 36-41

Author(s):

Tera Fit Rayani ◽

Yuni Resti ◽

Ratih Kemala Dewi

Keyword(s):

Mung Bean ◽

Irrigation System ◽

Nutrient Content ◽

Production Quality ◽

Total Biomass ◽

Randomized Design ◽

Nitrogen Free Extract ◽

Green Fodder ◽

Corn Kernels

This experiment was aimed to compare varieties and harvest time of green hydroponic fodder based on it’s quantity and quality. Green fodder is made from corn kernels, mung beans and unhulled rice. Green fodder was grown by mart hydroponics sensors and Arduino systems for controlling the water irrigation system and environmental conditions such as temperature and humidity. Quantity of green hydroponic fodder (corn, mung bean and unhulled rice) based on the biomass production. Quality of green hydroponic fodder based on nutrient content of the forage biomass (dry matter, crude protein, ash, ether extract, crude fiber and nitrogen free extract). Experimental design for fodder productivity was a completely randomized design with 3 x 3 factorial, i.e seed varieties (corn, mung bean and unhulled rice) and harvesting age of the green hydroponic fodder (7, 14 and 21 d). The results showed that total biomass was affected significantly (p<0.05) by harvesting age. Total biomass was increased with longer harvesting age of fodder. Corn green fodder and unhulled rice green fodder produce larger biomass than mung bean green fodder (p<0.05). The nutrient content of greenfodder were higher compared to the seeds. its quality and quantity, the best harvesting age of corn and unhulled rice green fodder was 14 days. Therefore smart hydroponic fodder can be an alternative to provide good quality fodder and land preservative. Key words: feed, hydroponic, green fodder

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PHYSICAL AND TECHNOLOGICAL QUALITY OF CORN KERNELS DURING STORAGE AS A FUNCTION OF PRE-CLEANING

Revista Brasileira de Milho e Sorgo ◽

10.18512/rbms2020v19e1159 ◽

2020 ◽

Vol 19 ◽

pp. 14

Author(s):

MILENA ANA ZAMBIASI ◽

PAULO RICARDO DE JESUS RIZZOTTO JÚNIOR ◽

RAFAEL GOMES DIONELLO ◽

LAURI LOURENÇO RADUNZ ◽

INDIANARA MULLER

Keyword(s):

Moisture Content ◽

Total Production ◽

Stored Grain ◽

Bulk Storage ◽

Technological Quality ◽

Combine Harvester ◽

Stored Grain Pests ◽

Corn Kernels

Maize is the most cultivated and consumed cereal in Brazil, which is the world’s third largest producer of this grain. Estimated losses due to pest attack, especially pest insects and fungi, represent approximately 10% of the total production. The pre-cleaning phase allows the reduction of foreign matters and impurities (IM) present in the grains, which are used as food and shelter for stored grain pests. The aim of this work was to evaluate the effect of pre-cleaning on the physical and technological quality of corn kernels, during bulk storage in a silo-dryer. The grains were harvested with a combine harvester, at a moisture content of around 17% and 0.84% of IM. Part of the grains was submitted to pre-cleaning and subsequently stored in a silo, while the other part was directly stored in a silo-dryer. After pre-cleaning, the grains were sent to the silo-dryer with 0.12% of IM. Drying was carried out by blowing natural air through the grain and the process was completed when the grains reached approximately 12% moisture content. It was concluded that pre-cleaning provided lower hygroscopic equilibrium moisture, reduced the presence of insect damaged grains, and improved the technological classification of grains during storage.

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