PhenoRice:A method for automatic extraction of spatio-temporal information on rice crops using satellite data time series

Agricultural monitoring systems require spatio-temporal information on widely cultivated staple crops like rice. More emphasis has been made on area estimation and crop detection than on the temporal aspects of crop cultivation, but seasonal and temporal information such as i) crop duration, ii) date of crop establishment and iii) cropping intensity are as important as area for understanding crop production. Rice cropping systems are diverse because genetic, environmental and management factors (G × E × M combinations) influence the spatio-temporal patterns of cultivation. We present a rule based algorithm called PhenoRice for automatic extraction of temporal information on the rice crop using moderate resolution hypertemporal optical imagery from MODIS. Performance of PhenoRice against spatially and temporally explicit reference information was tested in three diverse sites: rice-fallow (Italy), rice-other crop (India) and rice-rice (Philippines) systems. Regional product accuracy assessments showed that PhenoRice made a conservative, spatially representative and robust detection of rice cultivation in all sites (r2 between 0.75 and 0.92) and crop establishment dates were in close agreement with the reference data (r2 = 0.98, Mean Error = 4.07 days, Mean Absolute Error = 9.95 days, p < 0.01). Variability in algorithm performance in different conditions in each site (irrigated vs rainfed, direct seeding vs transplanting, fragmented vs clustered rice landscapes and the impact of cloud contamination) was analysed and discussed. Analysis of the maps revealed that cropping intensity and season length per site matched well with local information on agro-practices and cultivated varieties. The results show that PhenoRice is robust for deriving essential temporal descriptions of rice systems in both temperate and tropical regions at a level of spatial and temporal detail that is suitable for regional crop monitoring on a seasonal basis

PRE-TREATMENT AND ENZYMATIC HYDROLYSIS OF BANANA (Musa acuminata x balbisiana) PSEUDOSTEM FOR ETHANOL PRODUCTION

Banana (M. acuminata x balbisiana) is an abundant lignocellulosic waste material in large plantations all over the Philippines, especially in Mindanao, which can be utilized as substrate in producing high-value products like ethanol. To compensate for the low yield based on total weight of substrate due to the high moisture content of banana pseudostem, there is the primary challenge to make the conversion of this lignocellulosic biomass into monomeric sugar and then into ethanol more efficiently in order to achieve yields that would make it cost-competitive. Hence, this study evaluated the effects of solid loading, incubation time and amount of enzyme on yield of reducing sugars in the enzymatic hydrolysis process and attempted to optimize the significant factors by Response Surface Methodology (RSM), specifically using Box-Behnken design. There was significant improvement on the reducing sugar yield of the pretreated banana pseudostem at 20 h incubation time, 15 g solid loading and 0.55 % enzyme concentration. Ethanol production was observed to be higher in the detoxified substrate although biomass was higher for the non-detoxified substrate. As to our knowledge, the present study is the first attempt to produce second generation ethanol using banana pseudostem waste as feedstock in the Philippines

Genome-Wide Association Mapping in a Rice MAGIC Plus Population Detects QTLs and Genes Useful for Biofortification

The development of rice genotypes with micronutrient-dense grains and disease resistance is one of the major priorities in rice improvement programs. We conducted Genome-wide association studies (GWAS) using a Multi-parent Advanced Generation Inter-Cross (MAGIC) Plus population to identify QTLs and SNP markers that could potentially be integrated in biofortification and disease resistance breeding. We evaluated 144 MAGIC Plus lines for agronomic and biofortification traits over two locations for two seasons, while disease resistance was screened for one season in the screen house. X-ray fluorescence technology was used to measure grain Fe and Zn concentrations. Genotyping was carried out by genotype by sequencing and a total of 14,242 SNP markers were used in the association analysis. We used Mixed linear model (MLM) with kinship and detected 57 significant genomic regions with a -log10 (P-value) ≥ 3.0. The PH1.1 and Zn7.1 were consistently identified in all the four environments, ten QTLs qDF3.1, qDF6.2qDF9.1qPH5.1qGL3.1, qGW3.1, qGW11.1, and qZn6.2 were detected in two environments, while two major loci qBLB11.1 and qBLB5.1 were identified for Bacterial Leaf Blight (BLB) resistance. The associated SNP markers were found to co-locate with known major genes and QTLs such as OsMADS50 for days to flowering, osGA20ox2 for plant height, and GS3 for grain length. Similarly, Xa4 and xa5 genes were identified for BLB resistance and Pi5(t), Pi28(t), and Pi30(t) genes were identified for Blast resistance. A number of metal homeostasis genes OsMTP6, OsNAS3, OsMT2D, OsVIT1, and OsNRAMP7 were co-located with QTLs for Fe and Zn. The marker-trait relationships from Bayesian network analysis showed consistency with the results of GWAS. A number of promising candidate genes reported in our study can be further validated. We identified several QTLs/genes pyramided lines with high grain Zn and acceptable yield potential, which are a good resource for further evaluation to release as varieties as well as for use in breeding programs

Determining spatial and temporal patterns of submergence in rice with MODIS satellite data

Rice submergence is the condition by which the water level rises above the rice crop canopy. In general, rice plant response to submergence is to elongate its shoots above the rising water level. This costs in energy and eventually has a direct impact in terms of reducing yields. A specific gene, called Sub1, when introgressed into popular rice varieties by Marker Assisted Back-crossing, nearly stops the natural elongation process and permits a given local rice variety to sustain submerged conditions for a generally recognized period of about 2 weeks. Plant breeders now look for well-identified and location-accurate submergence areas in order to disseminate such improved local rice varieties. Remote sensing is proposed to provide surface water maps at high temporal resolution, determining a percentage of occurrences of surface water for a given pixel. Occurrence is defined as the count of days of identified surface water within a given period, returned in a percentage on that period. Rice area maps and knowledge of crop calendars are proposed to add to the assessment of submergence prone areas in two study areas, the Northeastern Thailand and Nueva Ecija in North Central Philippines

Complementarity of two rice mapping approaches : characterizing strata mapped by hypertemporal MODIS and rice paddy identification using multitemporal SAR

Different rice crop information can be derived from different remote sensing sources to provide information for decision making and policies related to agricultural production and food security. The objective of this study is to generate complementary and comprehensive rice crop information from hypertemporal optical and multitemporal high-resolution SAR imagery. We demonstrate the use of MODIS data for rice-based system characterization and X-band SAR data from TerraSAR-X and CosmoSkyMed for the identification and detailed mapping of rice areas and flooding/transplanting dates. MODIS was classified using ISODATA to generate cropping calendar, cropping intensity, cropping pattern and rice ecosystem information. Season and location specific thresholds from field observations were used to generate detailed maps of rice areas and flooding/transplanting dates from the SAR data. Error matrices were used for the accuracy assessment of the MODIS-derived rice characteristics map and the SAR-derived detailed rice area map, while Root Mean Square Error (RMSE) and linear correlation were used to assess the TSX-derived flooding/transplanting dates. Results showed that multitemporal high spatial resolution SAR data is effective for mapping rice areas and flooding/transplanting dates with an overall accuracy of 90% and a kappa of 0.72 and that hypertemporal moderate-resolution optical imagery is effective for the basic characterization of rice areas with an overall accuracy that ranged from 62% to 87% and a kappa of 0.52 to 0.72. This study has also provided the first assessment of the temporal variation in the backscatter of rice from CSK and TSX using large incidence angles covering all rice crop stages from pre-season until harvest. This complementarity in optical and SAR data can be further exploited in the near future with the increased availability of space-borne optical and SAR sensors. This new information can help improve the identification of rice areas

Relating X-band SAR Backscattering to Leaf Area Index of Rice in Different Phenological Phases

The objective of this study is to provide complete information on the dynamic relationship between X-band (3.11 cm) backscattering intensity (σ°) and rice crop’s leaf area index (LAI) at all growth phases. Though the relationship between X-band σ° and LAI has been previously explored, details on the relationship at the reproductive phase remain unstudied. LAI at the reproductive phase is important particularly at the heading stage where LAI reaches its maximum as it is closely related to grain yield, and at flowering stage where the total leaf area affects the amount of photosynthates. Therefore, this study examined the relationship of increasing LAI (vegetative to reproductive phase) and decreasing LAI (ripening phase) with TerraSAR-X (TSX) ScanSAR (3.11 cm) σ° at HH polarisation and 45° incidence angle. The results showed a statistically significant (R2 = 0.51, p value < 0.001) non-linear relationship of LAI with σ° at the vegetative to reproductive phase while no significant linear relationship was found at the ripening phase. This study completes the response curve of X-band σ° to LAI by filling in the information on the reproductive phase which more accurately characterises the dynamic relationship between the rice crop’s LAI and X-band’s σ°. This contributes to improved knowledge on the use of X-band data for estimating LAI for the whole crop cycle which is essential for the modelling of crop growth and estimation of yield

Assessment of anti-angiogenic effect of Mangifera indica L. (Mango) peel extract using chick chorioallantoic membrane (CAM) assay

Angiogenesis enables the migration and growth of malignant tumor cells through the foramtion of new blood vessels that may result to cancer, however, there are plants with anti-angiogenic effect. The research study entitled Assessment of Anti-Angiogenic Effect of Mangifera indica L. (Mango) Peel Extract using Chick Chorioalantoic Membrane (CAM) Assay aimed to assess the effectiveness of anti-angiogenic properties of mango peel extract using CAM Assay through the method of rotary evaporation; then the administered treatment concentrations were prepared in parts per million (PPM) - 1---ppm, 200-pp,, 300-ppm, and 400-ppm. The study utilized one-way analysis of variance (ANOVA) statistical test. The results showed that fewer number of primary blood vessels developed in the CAM with treatment than the control setup with no treatment specifically with the 300-pp, concentration that exhibits 8-20 number of primary blood vessels. Also, there was a significant difference among the different concentrations of mango extract to the CAM by 5% significance level. Therefore, the anti-angiogenic properties of mango peel are effective on decreasing the number of primary blood vessels. It is recommended to conduct a phytochemical analysis, to provide a comparison of the mango peel extract with a commercially available anti-angiogenic drug, and to compare the anti-angiogenic effect of the peel and the mesocarp of the mango