By Aakash Goyal and Muhammad Asif
People are relied on plants for nutrition, fibber and extra lately for gas. calls for for crop creation in emerging due to expanding inhabitants, swap in foodstuff conduct and biofuel intake. The publication concentrate on demanding situations, growth and clients of crop construction. It contains of substantial array of themes together with newest agronomics practices for various plants to augment productiveness, mitigate the demanding situations imposed by way of weather switch, increase water use potency, elements controlling dormancy, optimal use of fertilizers and so on. This quantity will function a great source for college kids and researchers and dealing within the region of sustainable crop construction.
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Distribution of harvest area (HA) 2. Satisfaction with rice yield and income Table 2 shows the respondents’ satisfaction with rice yield and income. The values in the table mean the proportion of respondents who answered ‘Yes’ to each question. We found that most households are not satisfied with rice yield and the subsequent income. On the other hand, it was implied that the poverty level experienced was not so serious as to worry about how to live their lives, because respondents (= head of family) were modestly satisfied with their income and they indicated they would not move to another place if they could get a higher income.
List of default field and cultivar parameters in the simulation model. 4. Remote sensing technique for optimizing field and cultivar parameters in the simulation model As mentioned in previous section, the simulation model can do a good job of estimating rice growth when one field parameter and four cultivar parameters in the simulation model can be set appropriately. Remote sensing will be helpful for optimizing these parameters using a simplex method on the regional and global scale. While there are several procedures to optimize the above-mentioned parameters using remote sensing, that shown in Fig.
Figure 15. Relationship between the cumulative LAI of January, May and September and the annual rice production. 5772/54926 It was possible to estimate the annual rice production of 2008 using the cumulative LAI of January, May and September from 2003 to 2007. This study indicates that the cumulative LAI of remotely sensed data is applicable to the estimation of rice production amount over a wide area, and the creation of each estimation equation for the irrigated paddy fields and the rainfed paddy fields will contribute to the improvement of the estimation accuracy of the annual rice production.