Validation of the LCC application under field conditions showed that grain yields were consistently higher than those obtained with other diagnostic tools in all growing seasons, while the MOET application was updated with better grain yield and resource efficiency through field field trials. by omitting nutrients. Three studies were conducted: (1) to assess soil fertility and health and to develop management recommendations to improve soil fertility and health; (2) assess the soil nutrient supply capabilities of different cropping systems; (3) explore long-term trends in the yield gap between potential and actual yields; (4) examine the suitability and sustainability of different rice production systems and develop management recommendations to improve sustainability; and (5) to examine the current soil fertility status of the PhilRice CES. The sustainability of cultivation patterns was measured in terms of productivity, sustainability and profitability.
However, the LCC app needs to be further improved in terms of agronomic efficiency of applied N (AEN). Since SPAD 502 can now be replaced by the LCC app, integration of the LCC app with the MOET app can potentially result in achieving the highest grain yield and best AEN in both DS and WS rice cuttings. This innovation will make the visual assessment of the rice leaves for correct application of N rate.
Development of Android application version of Leaf Color Chart (LCC) for more accurate Nitrogen Topdress application in Rice. The study aimed to develop the PhilRice LCC app, an Android application version of LCC for nitrogen (N) fertilizer management in rice. However, in terms of AEN, the LCC app was comparable to SPAD but still lower at 2.29 kg grain/kg N applied than RR.
The aim of the study was to improve recommended MOET application rates by establishing a linear correlation with NOPT following the settings of the 2018 WS field trials.
Assessment of Existing Diagnostic and Recommendatory Tools for Increasing Nitrogen-use Efficiency
Regression equations for each NPKS in relation to the growing season were included in the MOET App algorithm prior to the first yield trial of 2019 DS. The yield trial consisted of three treatments (NPK, MOET App version (v) 1 and MOET App v.2) in four replicates using three varieties (PSB Rc 82, NSIC Rc 300 and NSIC Rc 204H). The results of the 2019 DS yield trial showed consistently high grain yields under MOET App v.2 for all treatments and varieties used, while the AEN was significantly very high under MOET App v.2 for Rc 300 (32.84 kg/kgN ) and Rc 204H ( 36.19 kg/kgN).
In 2019 WS, the same yield trial (2nd setup) was established and grain yields were again significantly high, ranging from 5.51- 6.69t/ha, under MOET App v.2 across treatments and varieties except for Rc 204H. Furthermore, AEN of MOET App v.2 was observed to be better than MOET App v.1 only in Rc 300 during this harvest period.
Optimization of Crop Management
Components for Attaining the Yield Potential of Recently-released Irrigated Lowland Rice
Optimization of Nitrogen Rate to Achieve the Yield Potential of Recently-Released Irrigated Lowland Rice Varieties,
Effect of Nitrogen Rate and Plant Spacing on Yield Potential of Rice
Relationship of N and K Levels to Incidence of Major Rice Insect Pest and Diseases
ASPPD Research and Analytical Laboratory System and Maintenance
Development of Organic-based Nutrient Management for Paddy Rice and
Management of Productive and Environment- friendly Paddy Soils
Azolla microphylla, which screened to be a heat-tolerant variety, was then used as the potential organic-based topdress N source (FFE Program Annual Report. Comparing the packaged NM and the PalayCheck system, IBNM showed further yield increase when given an organic This apparently showed that the two packaged nutrient managements are complementary to each other and not necessarily contradictory.
In the 2019 trial, NSIC Rc 204H, which was expected to require a higher dose of nutrients, showed higher yield under the OBNM. It performed even better when complimented by full or half of the IBNM than the inbred variety, PSB Rc 82. Finally, by subjecting the OBNM to two different soil conditions, higher yield was observed by the PSB Rc 82 under the continuous flooded soil than in the well-drained or saturated soils.
To support the alternative organic-based topdress N source, Azolla production was maintained as part of the system. To create a cooler microenvironment, vegetables were planted along and above the Azolla pond, where vegetables were also applied with vermicompost and topdressed with composted Azolla. Apart from ensuring the family's food security, growing vegetables over the Azolla production pond can also be an additional income if the farmers want to sell them at a profit.
The vegetables grown together with Azolla production are organically grown and therefore had added value.
Long Term Organic Fertilizer Use in Paddy Soils and in Paddy Rice
Likewise, the pH value of the soil has not changed significantly since 2003 with the addition of either organic or inorganic NPK fertiliser. No significant increase in soil residual N was observed, while soil P was increasing from soils supplied with chicken manure (CM) and soil K was increasing due to rice straw. However, these values were still within the normal ranges in paddy soil for rice normal growth.
Optimized use of Azolla spp as an alternative and potential organic nitrogen nutrient for irrigation.
Optimized Utilization of Azolla spp as Alternative and Potential Organic-based Nitrogen Nutrition for Irrigated
This was followed by the conventional inorganic NPK fertilizer which was higher even compared to the yield under the pure inorganic fertilizer.
Optimization of Different Packaged Organic-based Nutrient Management for Irrigated Rice
Growing vegetables over the Azolla production pond can also provide additional income and food security for the family, as well as additional income if the farmers want to sell them for a profit. Because the vegetables are organically grown, this meant added value for the vegetables produced in the Azolla production.
PRISM: Philippine Rice Information System (PRISM) – Operation
Compared to the previous year's yield performance officially reported by PSA, the national average yields this year were relatively lower at 7.29% during the first semester and slightly higher at 1.03% during the second semester. The observed decrease in yields during the first semester can be attributed to the persistent dry spells and drought conditions that affected some rice-producing regions such as Cagayan Valley, ARMM, Northern Mindanao and Zamboanga Peninsula. The special bulletin contains information on the estimates of rice areas at risk, flooded/drought affected rice areas, and flood and drought maps.
PRISM-Field Monitoring of Rice Areas in the Philippines
Mapping of Rice Areas in the Philippines Using Remote Sensing Technology
PRISM IT Systems Development and ICT Infrastructure
The data and information produced by PRISM are classified, stored, organized and processed on a secure server with remote mirroring and can be accessed, processed and downloaded through the official website/portal of PRISM with identified access level. Remote servers were created at ASTI and DA-ICTS using HPC for redundancy. Additional memory was also procured for new data processed with upgrades and modifications with workstations and servers.
Monitoring of Flooded or Drought-affected Rice Areas
We have improved the design and functionality of the website by developing the Infolib module to assist in the operational monitoring of PRISM data, information, files and other functions. This study aimed to assess rice areas affected by extreme weather events using Synthetic Aperture Radar (SAR) images for floods and optical images for drought detection and assist DAs in making informed decisions and planning interventions and response to affected areas in emergencies through the delivery of remote sensing information. A protocol for assessing the extent of flood- and drought-affected rice areas using remote sensing and field surveys was developed and implemented to provide estimates of threatened rice areas and drought- or flood-affected rice areas to the Bureau of Supply.
Data on rice areas at risk of flood damage due to tropical cyclones (December 2018 to November 2019) and areas at risk of drought damage (November 2018 to March 2019) were submitted to DA. Finally, nine special bulletins (8 for flood and 1 for drought) containing the above information were submitted.
Enhancement of PRISM Rice Yield Monitoring System Using Remote Sensing and Crop Simulation Modelling
Strengthening institutional collaboration and end-user involvement, maximizing regional data applicability and data harmonization were among the key strategies identified to ensure the operational sustainability of the PRISM rice yield monitoring system. BLB - Bacterial Leaf Streak BLS - Bacterial Leaf Streak BCA - Biological Control Agent BS - Breeder's Seeds. CGMS - Cytoplasmic Genetic Male Sterility COF - Commercial Organic Fertilizer CDA - Cooperative Development Authority DAS - Days after sowing.
DOLE - Department of Labor and Employment DTI - Department of Business and Industry DSR - Direct seeded rice. FBS – Farmers’ Business School FC – Farmers’ Cooperative FSM – Farming Systems Models FAA – Fish Amino Acid. FGD - Focused Group Discussion FSP - Foundation Seed Production FRK - Farm Record Keeping GABA - Gamma-aminobutyric Acid GT - Gelatinization Temperature GAD - Gender and Development.
ICT - Information and Communication Technology IEC - Information Education Communication IBNM - Inorganic Based Nutrient Management ICM - Integrated Crop Management.
