scholarly journals THE RICE PLANTING WINDOW IN THE PHILIPPINES: AN ANALYSIS USING MULTI-TEMPORAL SAR IMAGERY

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 241-248
Author(s):  
M. A. Gutierrez ◽  
N. M. Paguirigan ◽  
J. Raviz ◽  
M. R. Mabalay ◽  
E. Alosnos ◽  
...  
Keyword(s):  
Crop Production ◽  
The Philippines ◽  
Wet Season ◽  
Planting Dates ◽  
Pests And Diseases ◽  
Rice Area ◽  
Multi Temporal ◽  
Sar Imagery ◽  
Crop Area ◽  
June July

Abstract. Knowing where and when rice is grown is essential for planning and decision-making in relation to food security, as well as in research wherein crop area and calendar are important inputs in crop production simulations, assessment of biotic and abiotic stresses, and analysis of the effect of climate change on crop production, among others. Remote sensing allows for efficient mapping and characterization of rice areas. In this study, we derived the rice planting window in all rice growing regions in the Philippines from 2016 to 2018 using multi-temporal Synthetic Aperture Radar (SAR), specifically TerraSAR-X and Sentinel-1. Using a rule-based method, rice area and Start of Season (SoS) were mapped based on the unique backscatter behaviour of rice corresponding to the initial deliberate agronomic flooding followed by rapid biomass increase. We defined the planting window per year and semester as the 15th and 85th percentile and the peak of planting as the dominant planting date. The accuracy of the rice map was 93% and the SoS was strongly correlated with the actual planting dates reported by farmers (R2 = 0.71) based on 482 ground observations in the Philippines in 2018 Semester 1. From this analysis, the planting window in the Philippines for the Semester 2 (wet season) is April-August (peak in June-July), and for Semester 1 (dry season) is September-February (peak in November-December) with large differences across regions. In majority of the regions, the planting window spans more than 100 days, which can have implications on incidence of pests and diseases.

scholarly journals Risk level mapping of organophosphate pesticides application in agricultural area of Cangkringan Subdistrict, Yogyakarta, Indonesia

2021 ◽  
Vol 933 (1) ◽  
pp. 012046
Author(s):  
S Rahmawati ◽  
D Wacano ◽  
M Erpinda ◽  
A Juliani
Keyword(s):  
High Risk ◽  
Crop Production ◽  
Loading Rate ◽  
Risk Scores ◽  
Risk Level ◽  
Organophosphate Pesticides ◽  
Wet Season ◽  
Four Levels ◽  
Crop Area ◽  
Very High

Abstract Farmers in Indonesia widely use organophosphate pesticides (OPPs) to increase crop production, despite their risk to human health and the environment. Objective of this study is to estimate the loading rate and risk level of OPPs based on OPPs characteristics, farmers’ knowledge, and the behavior of OPPs application in agriculture area in Yogyakarta Special Region in Indonesia. Data collected through interview and questionnaire distribution revealed three types of OPPs used in study area; profenofos, chlorpyrifos and diazinon. Data on application dose and crop area were used to estimate loading rate. Risk scores can be calculated by multiplying loading rate with toxicity data of each type of OPPs used. Box-Cox transformation was then used to normalized rightly skewed risk score data to get 4 (four) levels of risk classification range; low, medium, high and very high. It was found that there were areas classified as very high risk in wet season, while it is not the case in dry season. However, in total loading per year, areas with high and very high risk level were found for more than >50% in study area.

Evaluating the impact of ponds in sustaining crop production: a case of Zhanghe irrigation system in China

Water Policy ◽  
2009 ◽  
Vol 11 (2) ◽  
pp. 236-249 ◽  
Author(s):  
Shahbaz Mushtaq ◽  
Shahbaz Khan ◽  
Mohsin Hafeez
Keyword(s):  
Agricultural Production ◽  
Crop Production ◽  
Irrigation System ◽  
Pond Water ◽  
Water Shortages ◽  
Water Users ◽  
Rice Area ◽  
Crop Area ◽  
The Impact

Ponds are small reservoirs located in irrigated areas that allow farmers to capture rainfall, store surplus water from irrigation canals and conserve water from other sources. These ponds allow the users to obtain water on-demand providing built-in flexibility by storing water close to water users. Though ponds have been used widely in irrigated areas for many years, a recent increase in the construction of ponds because of growing water shortages and government policies are placing greater need on understanding their role in sustaining crop production. We evaluated the impact of ponds in sustaining agricultural production, specifically the impact of ponds on cost of irrigation, crop area and production. Multivariate regression models were developed to assess the impact of ponds. The results of an assessment of the impact of access to pond water indicated that it reduces the total cost of irrigation. However, the effect is not statistically significant, whereas access to pond water had some positive but non significant impact on rice area and yield. The results did not show any significant increase in yield and rice area because of the similar quality of ponds and the ZIS canal water; the ZIS contributes around 20% to pond water. However, comparing yield using pond water and rainfed agriculture may show a significant impact of pond water. We envision that ponds will continue to play vital roles in sustaining agricultural production.

scholarly journals INTEGRATING TIME-SERIES SAR DATA AND ORYZA CROP GROWTH MODEL IN RICE AREA MAPPING AND YIELD ESTIMATION FOR CROP INSURANCES

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 239-243
Author(s):  
S. Pazhanivelan ◽  
K. P. Ragunath ◽  
N. S. Sudarmanian ◽  
R. Kumaraperumal ◽  
T. Setiyono ◽  
...  
Keyword(s):  
Time Series ◽  
Tamil Nadu ◽  
Crop Insurance ◽  
Crop Growth ◽  
Linear Diffusion ◽  
Temporal Features ◽  
Rice Area ◽  
Multi Temporal ◽  
Sar Data ◽  
Sar Imagery

<p><strong>Abstract.</strong> Lowland rice in tropical and subtropical regions can be detected precisely and its crop growth can be tracked effectively through Synthetic Aperture Radar (SAR) imagery, especially where cloud cover restricts the use of optical imagery. Parameterised classification with multi-temporal features derived from regularly acquired, C-band, VV and VH polarized Sentinel-1A SAR imagery was used for mapping rice area. A fully automated processing chain in MAPscape-Rice software was used to convert the multi-temporal SAR data into terrain-geocoded &amp;sigma;<sup>0</sup> values, which included strip mosaicking, co-registration of images acquired with the same observation geometry and mode, time-series speckle filtering, terrain geocoding, radiometric calibration and normalization. Further Anisotropic non-linear diffusion (ANLD) filtering was done to smoothen homogeneous targets, while enhancing the difference between neighbouring areas. Multi-Temporal Features viz., max, min, mean, max date, min date and span ratio were extracted from VV and VH polarizations to classify rice pixels. Rice detection was based on the analysis of temporal signature from SAR backscatter in relation to crop stages. About sixty images across four footprints covering 16 <i>samba</i> (<i>Rabi</i>) rice growing districts of Tamil Nadu, India were obtained between August 2017 and January 2018. In-season site visits were conducted across 280 monitoring locations in the footprints for classification purposes and more than 1665 field observations were made for accuracy assessment. A total rice area of 1.07 million ha was mapped with classification accuracy from 90.3 to 94.2 per cent with Kappa values ranging from 0.81 to 0.88. Using ORYZA2000, a weather driven process based crop growth simulation model developed by IRRI, yield estimates were made by integrating remote sensing products viz., seasonal rice area, start of season and backscatter time series. By generating average backscatter for each time series and dB stack for each SoS, LAI values were estimated. The model has generated rice yield estimate for each hectare which were aggregated at administrative boundary level and compared against CCE yield. Yield Simulation accuracy of more than 86&amp;ndash;91% at district level and 82&amp;ndash;97% at block level from the study indicates the suitability of these products for policy decisions. SAR products and yield information were used to meet the requirements of PMFBY crop insurance scheme in Tamil Nadu and helped in identifying or invoking prevented/failed sowing in 529 villages and total crop failure in 821 villages. In total 303703 farmers were benefitted by this technology in getting payouts of INR 9.94 billion through crop insurance. The satellite technology as an operational service has helped in getting quicker payouts.</p>

Preliminary survey of pests and diseases of eucheumatoid seaweed farms in the Philippines

2021 ◽  
Author(s):  
Joseph P. Faisan ◽  
Ma. Rovilla J. Luhan ◽  
Rema C. Sibonga ◽  
Jonalyn P. Mateo ◽  
Victor Marco Emmanuel N. Ferriols ◽  
...  
Keyword(s):  
The Philippines ◽  
Preliminary Survey ◽  
Pests And Diseases

scholarly journals Detection of Banana Plants Using Multi-Temporal Multispectral UAV Imagery

2021 ◽  
Vol 13 (11) ◽  
pp. 2123
Author(s):  
Aaron Aeberli ◽  
Kasper Johansen ◽  
Andrew Robson ◽  
David Lamb ◽  
Stuart Phinn
Keyword(s):  
Template Matching ◽  
Crop Production ◽  
Local Maximum ◽  
Banana Plant ◽  
Essential Information ◽  
Object Based ◽  
Agricultural Applications ◽  
Multi Temporal ◽  
Rule Set ◽  
Geographic Object

Unoccupied aerial vehicles (UAVs) have become increasingly commonplace in aiding planning and management decisions in agricultural and horticultural crop production. The ability of UAV-based sensing technologies to provide high spatial (<1 m) and temporal (on-demand) resolution data facilitates monitoring of individual plants over time and can provide essential information about health, yield, and growth in a timely and quantifiable manner. Such applications would be beneficial for cropped banana plants due to their distinctive growth characteristics. Limited studies have employed UAV data for mapping banana crops and to our knowledge only one other investigation features multi-temporal detection of banana crowns. The purpose of this study was to determine the suitability of multiple-date UAV-captured multi-spectral data for the automated detection of individual plants using convolutional neural network (CNN), template matching (TM), and local maximum filter (LMF) methods in a geographic object-based image analysis (GEOBIA) software framework coupled with basic classification refinement. The results indicate that CNN returns the highest plant detection accuracies, with the developed rule set and model providing greater transferability between dates (F-score ranging between 0.93 and 0.85) than TM (0.86–0.74) and LMF (0.86–0.73) approaches. The findings provide a foundation for UAV-based individual banana plant counting and crop monitoring, which may be used for precision agricultural applications to monitor health, estimate yield, and to inform on fertilizer, pesticide, and other input requirements for optimized farm management.

scholarly journals Peach Brown Rot: Still in Search of an Ideal Management Option

Agriculture ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. 125 ◽  
Author(s):  
Vitus Ikechukwu Obi ◽  
Juan José Barriuso ◽  
Yolanda Gogorcena
Keyword(s):  
Fungal Pathogens ◽  
Crop Production ◽  
Control Strategies ◽  
Brown Rot ◽  
Management Option ◽  
Management Options ◽  
Pests And Diseases ◽  
Resistant Varieties ◽  
Rot Disease ◽  
Post Harvest Loss

The peach is one of the most important global tree crops within the economically important Rosaceae family. The crop is threatened by numerous pests and diseases, especially fungal pathogens, in the field, in transit, and in the store. More than 50% of the global post-harvest loss has been ascribed to brown rot disease, especially in peach late-ripening varieties. In recent years, the disease has been so manifest in the orchards that some stone fruits were abandoned before harvest. In Spain, particularly, the disease has been associated with well over 60% of fruit loss after harvest. The most common management options available for the control of this disease involve agronomical, chemical, biological, and physical approaches. However, the effects of biochemical fungicides (biological and conventional fungicides), on the environment, human health, and strain fungicide resistance, tend to revise these control strategies. This review aims to comprehensively compile the information currently available on the species of the fungus Monilinia, which causes brown rot in peach, and the available options to control the disease. The breeding for brown rot-resistant varieties remains an ideal management option for brown rot disease control, considering the uniqueness of its sustainability in the chain of crop production.

scholarly journals Influence of farmers' knowledge of climate change on production of citrus and tomato in Nigeria

2020 ◽  
Vol 48 (2) ◽  
Author(s):  
O. Adebisi-Adelani ◽  
M. Akeredolu
Keyword(s):  
Climate Change ◽  
Value Chain ◽  
Secondary Data ◽  
Sampling Technique ◽  
Structured Interview ◽  
Adaptation Strategies ◽  
Planting Dates ◽  
Horticultural Crops ◽  
Pests And Diseases ◽  
Growing Period

ABSTRACT Production is the basis of value-chain which is a key factor in Agricultural Transformation Agenda (ATA) in Nigeria. Thus, for successful production of horticultural crops the importance of climate cannot be overemphasized. Therefore, in this era of climate change there is the need to study farmers' knowledge of climate change and their production level. The study was carried out in Nigeria. Multistage sampling technique was used to arrive at a study population of 441 tomato and citrus farmers. Data were collected using Focus Group Discussions (FGDs), structured interview schedule and secondary data (FAOSTAT). It was analyzed using descriptive statistics (frequencies, percentage and pie charts) and inferential statistics (Pearson Product Moment Correlation). There existed no significant relationship between knowledge level of respondents and change in production of both crops. The reason for this could be that no matter what the level of knowledge one may have on the subject of climate change it does not have anything to do with production, adaptation strategies is the key. Citrus and tomato farmers' adaptation strategies to climate change includes among others crop management, use of varieties resistant to pests and diseases, altering the timing or location of cropping activities, different planting dates and shortened length of growing period. In conclusion climate change has affected the production of horticultural crops therefore for ATA to have a good footing there is the need to focus on the adaptation strategies that can combat the effect of climatic changes. Key words: Horticultural crops, Horticultural farmers, Climate, Production, Knowledge,

scholarly journals Attaining food self-sufficiency through the Edible Landscaping (EL) Technology: Assessing the Promotional Activities of EL in the Philippines, amidst the COVID-19 Pandemic

2021 ◽  
Vol 879 (1) ◽  
pp. 012014
Author(s):  
F C Sanchez ◽  
Jr.M C Ilang-Ilang ◽  
M C E Balladares ◽  
B V Apacionado ◽  
R R P Tayobong ◽  
...  
Keyword(s):  
Thematic Analysis ◽  
Crop Production ◽  
The Philippines ◽  
Qualitative Approach ◽  
Household Food ◽  
The People ◽  
Self Sufficiency ◽  
Edible Landscaping ◽  
The University ◽  
A Current

Abstract The sustainability of the food supply seems to be a never-ending concern of many households in the Philippines. This concern is most especially felt in this time of pandemic wherein many Filipinos are struggling on where to get their food to feed their families. The adoption of edible landscaping has become more in demand because of the current situation caused by the pandemic. As such, having a sustainable edible garden is very much recommended because it can provide the household a “garden to table” food which can help in making the household food self-sufficient. There is a current need to promote edible landscaping technology primarily through trainings and seminars and it should be intensified to inform and educate the people on food self-sufficiency amidst the COVID-19 pandemic. Edible landscaping (EL) as an approach that merges the science of crop production and the art of landscaping, is continuously being promoted using different strategies and one of which is the conduct of trainings and seminars all over the Philippines. This study assessed the different ways by which the Edible Landscaping Team of the University of the Philippines Los Banos delivered promotional activities such as webinars and e-training amidst the context of the COVID-19 pandemic. This research was conducted using the qualitative approach, specific case studies, and the data gathered were analyzed using thematic analysis. More than 39,000 individuals in the Philippines have already been reached and educated on the technology through the conduct of e-trainings and webinars. The presentations and lectures on edible landscaping were modified based on the needs of the requesting institution and were discussed using a combination of English and Filipino languages. The duration of the eight webinars ranged from a minimum of 30 minutes to a maximum of almost 5 hours (in discussion is written ‘almost 4 hours). Based on the comments, most of the online viewers gave affirmative responses.

scholarly journals ESTIMATION OF DAMAGED AREAS DUE TO THE 2010 CHILE EARTHQUAKE AND TSUNAMI USING SAR IMAGERY OF ALOS/PALSAR

2016 ◽  
Vol III-8 ◽  
pp. 35-42
Author(s):  
Pertiwi Jaya Ni Made ◽  
Fusanori Miura ◽  
A. Besse Rimba
Keyword(s):  
Large Scale ◽  
Aerial Photographs ◽  
Alos Palsar ◽  
Aster Gdem ◽  
Tsunami Damage ◽  
Before And After ◽  
Chile Earthquake ◽  
Multi Temporal ◽  
Sar Imagery ◽  
Inundation Map

A large-scale earthquake and tsunami affect thousands of people and cause serious damages worldwide every year. Quick observation of the disaster damage is extremely important for planning effective rescue operations. In the past, acquiring damage information was limited to only field surveys or using aerial photographs. In the last decade, space-borne images were used in many disaster researches, such as tsunami damage detection. In this study, SAR data of ALOS/PALSAR satellite images were used to estimate tsunami damage in the form of inundation areas in Talcahuano, the area near the epicentre of the 2010 Chile earthquake. The image processing consisted of three stages, i.e. pre-processing, analysis processing, and post-processing. It was conducted using multi-temporal images before and after the disaster. In the analysis processing, inundation areas were extracted through the masking processing. It consisted of water masking using a high-resolution optical image of ALOS/AVNIR-2 and elevation masking which built upon the inundation height using DEM image of ASTER-GDEM. The area result was 8.77 Km&lt;sup&gt;2&lt;/sup&gt;. It showed a good result and corresponded to the inundation map of Talcahuano. Future study in another area is needed in order to strengthen the estimation processing method.

scholarly journals Soil Health as Influenced by Fertilizer Management in Rice Based Cropping System

2021 ◽  
Vol 24 (2) ◽  
pp. 119-131
Author(s):  
MM Haque ◽  
MR Islam ◽  
MS Rahman ◽  
MAR Sarkar ◽  
MAA Mamun ◽  
...  
Keyword(s):  
Crop Production ◽  
Nutrient Management ◽  
Soil Health ◽  
Cropping System ◽  
Crop Productivity ◽  
Cow Dung ◽  
Wet Season ◽  
Management Options ◽  
Cropping Patterns ◽  
Soil C

Nutrient management influences soil health and crop productivity. Sustained crop production re-quires specific nutrient management options after a certain period. The objectives of this investigation were to examine the effects of inorganic and organic fertilization on yields and soil carbon budget under rice based cropping patterns in Bangladesh. The research data and informationhave been gen-erated based on previouslypublished, unpublished sources and own concept.Omission of K or im-balanced K are more influential for reduction in grain yield up to 47% in Boro (dry) season but N was most limiting up to 35% in T. Aman (wet) season. With existing fertilizer rates for growing rice, the balances of N and K are always negative. Balanced chemical fertilizer (NPKSZn) can be an option for improving crop productivity and maintain soil quality. Net ecosystem carbon (C) balances are posi-tive when 3 t ha-1 cow dung (CD), 2 t ha-1 poultry manure (PM) and 2 t ha-1 vermicompost (VC) are used in combination with chemical fertilizers. Soil amendments with organic nutrient sources (rice straw, CD, PM, VC, legume crops) and rice based cropping patterns such as T. Aman-Mustard-Boro, Boro-Fallow-Fallow, Jute-T. Aman-Fallow, Wheat-Mungbean-T. Aman, Grass pea- T. Aus-T. Aman and Potato-Boro-T. Aman can be beneficial in improving soil C budget, soil nutrient ratio, total crop production and maintenance of environmental health that will meet SDGs goal. Bangladesh Rice J. 24 (2): 119-131, 2021

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