Concentration of Nutrients in Leaves, Flowers, and Fruits of Genotypes of Coffea canephora

It is important to consider the nutritional demand among genotypes of the same species to achieve high yields. Thus, the objective of this study was to determine the concentration of nutrients in leaves, flowers, grains, and fruit straw in conilon coffee genotypes. The experiment was carried out under a randomized block design, with three replications and the evaluation of nine genotypes. Leaf collections were carried out every three months, from August 2019 to May 2020. Flowers were collected at flowering in July 2019 and fruits in June 2020, upon complete maturation of the genotypes. The materials were dried in an oven and sent for laboratory analysis to determine the nutritional content. Data were subjected to analysis of variance followed by a comparison of means and estimates of genetic parameters and clustering using the hierarchical method (UPGMA). The nutrients found in the highest concentrations in the evaluated plant organs were N and K for macronutrients and Fe for micronutrients. For the leaves, the concentrations of the main nutrients were high in the first and reduced in the last evaluated periods, possibly due to mobilization to the fruits. Considering all the plant tissues evaluated, the order of concentration of macronutrients and micronutrients was N > K > Ca > P = Mg = S and Fe > B > Mn > Cu > Zn, respectively. For a nutritional diagnosis, it is important to take comparisons of the genetic diversity and evaluation periods into consideration.

ANALISIS KLASTER: KARAKTERISTIK, KANDUNGAN ZAT GIZI, DAN SENYAWA AKTIF EXTRA VIRGIN OLIVE OIL DI SUPERMARKET

Latar Belakang. Kandungan zat gizi extra virgin olive oil (EVOO) memiliki banyak manfaat untuk kesehatan manusia. Beberapa manfaat antara lain sebagai imunomodulator, mencegah penyakit jantung dan vaskuler lainnya, mencegah penyakit alergi, memperbaiki fungsi liver, dan mencegah penyakit lainnya. Kandungan zat gizi tiap merek EVOO tidak sama, ditentukan oleh banyak faktor. Tujuan. Penelitian ini bertujuan menganalisis klaster berdasarkan karakteristik kimiawi, kandungan zat gizi, dan senyawa aktif pada tujuh sampel produk EVOO dari supermarket. Metode. Desain deskriptif digunakan dalam penelitian ini. Pengumpulan tujuh sampel produk EVOO di supermarket wilayah Daerah Khusus Ibukota (DKI) Jakarta dilakukan pada bulan Maret 2019. Pemeriksaan sampel produk EVOO dilakukan di Laboratorium Balai Besar Industri Agro (BBIA) Kementerian Perindustrian dan Laboratorium Biofarmaka dan Lembaga Penelitian Pengabdian Masyarakat (LPPM) Institut Pertanian Bogor (IPB). Analisis yang digunakan adalah analisis klaster melalui pendekatan hierarchical method. Hasil. Berdasarkan karakteristik kimiawi, ditemukan bahwa sampel produk EVOO ke-6 memiliki karakteristik kimiawi paling berbeda. Sampel produk EVOO ke-4 memiliki kandungan asam lemak jenuh paling berbeda. Kandungan asam lemak tak jenuh pada sampel produk EVOO ke-1, 3, dan 7 mendekati kesamaan. Kandungan vitamin E pada sampel produk EVOO ke-2 dan kandungan zat besi pada sampel produk EVOO ke-6, berbeda dengan sampel produk EVOO lainnya. Kandungan total flavonoid pada sampel produk EVOO ke-2, 3, dan 4, memiliki kadar mendekati kesamaan. Kandungan total karotenoid pada sampel produk EVOO ke-2 dan ke-6 juga memiliki kadar mendekati kesamaan. Kesimpulan. Karakteristik kimiawi pada semua sampel produk EVOO yang ditemukan dalam penelitian memiliki nilai hampir sama. Sampel produk EVOO di supermarket memiliki perbedaan kandungan asam lemak tak jenuh, total flavonoid, dan total karotenoid.

An Approach of Detecting the Age of a Human by Extracting the Face Parts and Applying the Hierarchical Methods

One of the key challenges that the computer vision is facing is the age prediction. A well efficient CNN is selected for age prediction by performing various CNN operations by taking the categories as age 40 and above age 40. The selected CNN method obtained a training accuracy of 100% at more than 100 epochs. Hence, 100 epochs is considered for training. At this, the validation accuracy achieved is 84.9%. Three kinds of age phases with an age gap of 20,10 and 5 are used to predict the age. The normal method results in very less accuracy. Hence a hierarchical method is formulated. Under the hierarchical method, CNN is trained to estimate the age gaps in decreasing order. Hence not a single classifier, a group of classifiers are used for testing the image. From traditional method to hierarchical method, the 20 age gap accuracy increased from 27% to above 60%, ten age gap increased from 12% to above 35%, and five age gap increased from 5.5% to above 21%. To improve further, the features of the face parts are derived and combined which improves the efficiency compared to normal method, but not good accuracy as Hierarchical method. The combination of hierarchical method along with the face feature extraction method results in a considerable improvement in accuracy.

Hierarchical forecasts of Diabetes mortality in Mexico by marginalization and sex to establish resource allocation

Objective: The mexican population has experimented an astounding rise in type II Diabetes mortality as well as a growing trend for the economic burden in the recent years. The paper’s purpose is to propose an approach to establish a distribution of resource allocation objectively to face the future economic burden. Methodology: Hierarchical forecasts of Diabetes mortality to 2030 by sub-domains of the population are estimated based on marginalization and sex. Results: The forecasts confirm that differences related to sub-domains will be significant. In fact, the rates will increase most notably both in low and high marginalized. Limitations: The hierarchical method just provide point forecast without prediction intervals. Originality: There is not a similar application for mexican data to do that objectively. Conclusions: The most recommendable budget distribution should be mainly addressed among the low and high levels. Implications of these estimates should support unpostponable health policy in general and for the mentioned sub-domains in particular.

Analisis kluster Kabupaten dan Kota di Provinsi Jambi berdasarkan indikator pembangunan

The purpose of this study is to classify Regencies and Cities in Jambi Province based on HDI, economic growth, percentage of population growth, percentage of poor population, percentage of open unemployment rate and Gini ratio. To answer these objectives the hierarchical method used is Average Linkage (Between Groups). The of analysis were obtained, two clusters could be formed, where group 1 consisted of 10 Regencies and Cities, group 2 consisted of 1 Regencies.