| 000 | 02499nam a22002897a 4500 | ||
|---|---|---|---|
| 003 | OSt | ||
| 005 | 20250625092822.0 | ||
| 008 | 250623b |||||||| |||| 00| 0 eng d | ||
| 040 |
_aTUPM _bEnglish _cTUPM _dTUPM _erda |
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| 050 |
_aBTH T 58.5 _bG84 2018 |
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| 100 |
_aGueta Mariden G. _eAuthor |
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| 245 |
_aDevelopment of android-based crop analyze/ _cMariden G. Gueta and Valerie R. Tangonan.-- |
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| 260 |
_aManila: _bTechnological University of the Philippines, _c2018 |
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| 300 |
_ax, 98pages: _c29cm. |
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| 336 | _2rdacontent | ||
| 337 | _2rdamedia | ||
| 338 | _2rdacarrier | ||
| 500 | _aBachelor's Thesis | ||
| 502 |
_aCollege of Industrial Technology.-- _bBachelor of technology major in information technology: _cTechnological University of the Philippines. _d2018. |
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| 504 | _aIncludes bibliographic references and index. | ||
| 520 | _aOveruse of synthetic fertilizer is one of the problems of farmers. Factors contributing to it is the timing of fertilizer application. Farmers operate their farms in the traditional way where most of them rely on the age or the days after transplanting the seed not based on the crop’s needs. The purpose of this study is to develop a mobile application that will help farmers easily determine the nitrogen content of rice and corn and recommend amount of fertilizer to be applied based on Leaf Color Chart panel standards. The system was developed using Android Studio for Android application development. Based on the results of tests done such as functionality, reliability and portability. The application’s functionality for rice analysis has obtained the highest mean of 80% and 70% for corn analysis. The project’s reliability confirmed that the project can be installed and loaded successfully despite the numerous number of users. While the project’s portability confirmed that the application is accessible from Android Jelly Bean 4.3 OS up to Android Lollipop 5.0 OS and that it works with phone’s having 2 megapixels camera. Based on the results of the evaluation conducted using the ISO Software Product Quality, the project was evaluated with a mean average of 4.11 which obtained “Very Good” rating. This indicates that the system is beneficial to rice and corn farmers in terms of determining nitrogen content of rice and corn. | ||
| 650 | _aInformation technology | ||
| 650 | _aAndroid Application | ||
| 650 | _aAgriculture | ||
| 700 |
_aTangonan Valerie R. _eAuthor |
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| 942 |
_2lcc _cBTH CIT _n0 |
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| 999 |
_c29957 _d29957 |
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