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"Pengukuran kandungan nitrogen pada tanah atau tanaman merupakan dasar utama dalam monitoring dan pengambilan keputusan dalam manajemen pemupukan tanaman. Kombinasi teknologi pengukuran menggunakan Bagan Warna Daun (BWD) dan drone dengan kamera multispektral diharapkan dapat memberikan terobosan baru bagi pertanian Indonesia. Tujuan penelitian ini adalah mengembangkan algoritma pemrograman untuk membuat Normalized DifferenceVegetation Index (NDVI) mapping berdasarkan transformasi nilai BWD. Pengambilan foto udara dilakukan saat tanaman berumur 28, 35 dan 42 hari setelah tanam (HST) dengan ketinggian terbang 3 m. Pada hari yang sama, dilakukan pengukuran warna hijau daun dengan BWD. Nilai BWD kemudian ditransformasikan kedalam nilai tone mapping sebagai dasar pembuatan NDVI mapping. Algoritma pemrograman dikembangkan dalam software Matlab dan digunakan untuk menghitung nilai NDVI dengan menerapkan metode mtresholding yang bertujuan untuk menghasilkan nilai NDVI rata-rata yang mendekati nilai NDVI eksperimen di lapangan. NDVI rata-rata secara keseluruhan bertujuan untuk menangkap nilai NDVI global foto lahan yang merepresentasikan keseluruhan tanaman yang ada di foto. Hasil simulasi menunjukkan bahwa pada umur tanaman 28 dan 35 HST, simulasi terbaik menggunakan nilai treshold 0.18 dengan persentase error 18.7% dan 15.92%. Sedangkan pada umur 42 HST, simulasi terbaik menggunakan nilai treshold 0.20 dengan persentase error 13.55%. Kinerja program yang telah dikembangkan dapat dikatakan berhasil cukup baik. Secara kualitatif, hal ini dilihat dari hasil simulasi yang sudah dapat menampilkan perbedaan warna secara visual pada tingkat NDVI yang berbeda dan pada umur tanaman yang berbeda. Secara kuantitatif, ditunjukkan dengan nilai NDVI yang bertambah seiring bertambahnya umur tanaman.

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Measurement of nitrogen content in the soil or plants is the primary basis in monitoring and decision making in crop fertilizer management. The combination of measurement technology using Leaf Color Chart (LCC) and unmanned aerial vehicle (UAV) equipped with multispectral cameras is expected to provide new insight into Indonesian agriculture. The purpose of this study is to develop a programming algorithm to create a Normalized Difference Vegetation Index (NDVI) mapping based on LCC value transformation. Aerial imagery collected at a critical stage of rice growth at 28, 35, and 42 days after planting (DAP) with a flight height of 3 m. Ground measurements were taken along with the UAV campaign using LCC. The LCC value then transformed into the tone mapping value as a basis for making NDVI mapping. The programming algorithm was developed in Matlab software and is used to calculate NDVI values by applying the thresholding method, which aims to produce an average NDVI value close to the NDVI value of experiments in the field. The overall average NDVI aims to capture the global NDVI value of the photo of the land that represents all the plants in the photo. The simulation results show that at the age of plants 28 and 35 DAP, the best simulation uses a treshold value of 0.18 with an error percentage of 18.7% and 15.92%. Whereas at the age of 42 DAP, the best simulation uses a treshold value of 0.20 with an error percentage of 13.55%. The performance of the program developed can be said to be quite successful. Qualitatively, this can be seen from the simulation results, which have been able to display color differences visually at different NDVI levels and different plant ages. Quantitatively, it is shown by the NDVI value that increases with the age of the plant."

"Tanaman Padi merupakan jenis tanaman pangan yang dibudidayakan melalui dataran rendah, salah satu kebutuhan pokok masyarakat dunia dan sumber penghidupan bagi sebagian besar masyarakat Indonesia. Namun jumlah produksi beras di Indonesia masih tergolong rendah dibandingkan dengan tingkat konsumsi masyarakat, sehingga perlu mendapat perhatian lebih dalam mendukung terwujudnya swasembada pangan. Salah satu upaya untuk mencapai hal tersebut dilakukan dengan pemantauan, seperti kondisi kesehatan. Penggunaan penginderaan jauh seperti Citra Sentinel-2 dan SPOT-6 dengan algoritma NDVI (Normalized Difference Vegetation Index) dapat digunakan untuk menganalisis kesehatan tanaman padi. Penelitian ini bertujuan untuk menganalisis persebaran kondisi kesehatan tanaman padi di Kecamatan Parakansalak, Kabupaten Sukabumi, Jawa Barat menggunakan citra satelit Sentinel-2 dan SPOT-6 yang diolah dengan algoritma NDVI dan mengetahui hubungannya dengan nilai NDVI hasil survei lapangan juga faktor fisik lingkungan dan tanaman. Hasil penelitian menyimpulkan bahwa kesehatan tanaman padi di Kecamatan Parakansalak cukup tinggi dengan didominasi klasifikasi kesehatan yang baik seluas 197 hektar atau 52% dari lahan eksisting oleh Sentinel-2, dan sebaran nilai NDVI pada citra SPOT-6 memiliki pola spasial yang serupa. Persentase ini menunjukkan bahwa sebaran nilai NDVI relatif tinggi dan tanaman memiliki kerapatan yang tinggi. Adapun kesehatan tanaman padi dengan nilai NDVI hasil survei lapang menunjukkan hubungan dengan nilai R sebesar 0,929. Berdasarkan hasil overlay dan jumlah sampel yang sedikit ini, Tanaman padi dengan kesehatan lebih tinggi sebagian besar berada pada wilayah dengan lereng yang landai dan dekat dengan jaringan irigasi tersebar di lahan sawah Kecamatan Parakansalak. Sehingga kemudian hasil yang baik ini masih memiliki banyak kekurangan dan memerlukan studi lebih lanjut.

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Rice is a type of food plant that is cultivated through the lowlands, one of the basic needs of the world community and source of livelihood for most Indonesian people. However, the amount of rice production in Indonesia is still relatively low compared to the level of public consumption, so it needs more attention in supporting the realization of food self-sufficiency. One of the efforts to achieve this is through monitoring, such as health conditions. The use of remote sensing such as Sentinel-2 and SPOT-6 with NDVI (Normalized Difference Vegetation Index) algorithm can be used to analyze the health of rice plants. This study aims to analyze the distribution of the health condition of rice plants in Parakansalak District, Sukabumi Regency using Sentinel-2 and SPOT-6 satellite imagery which were processed by the NDVI algorithm and knowing the relationship with an NDVI value from field survey with the physical factors. The results of the study concluded that the health of rice plants in Parakansalak District was quite high with a good health classification dominated by an area of 197 hectares or 52% of the existing land by Sentinel-2, and the distribution of NDVI values in SPOT-6 images had a similar spatial pattern. This percentage indicates that the distribution of NDVI values is relatively high and the plants have a high density. The health of rice plants with an NDVI value from the results of a field survey showed a relationship with an R value of 0.929. Based on the results of the overlay and the small number of samples, the rice plants with higher health are mostly located in areas with gentle slopes and close to irrigation networks scattered in the paddy fields of Parakansalak District. So then this good result still has many shortcomings and requires further study."

"Population Structure of Trichogrammatoidea armigera, Egg Parasitoid of Helicoverpa armigera Based on RAPD-PCR Analysis. Bahagiawati, Damayanti Buchari, Nurindah, H. Rizjaani, Dwinita W. Utami, B. Sahari, and A. Sari. Genetic structures of Trichogrammatoidea armigera (Hymenoptera: Trichogrammatidae), the egg parasitoid of Helicoverpa armigera (Lepidoptera: Noctuidae) were studied. Egg masses of H. armigera were collected from fields of several locations in West Java and East Java with different distances among them and two distinct cultural practices, i.e., monoculture and polyculture. Genetic relationships among T. armigera populations that emerged from the collected H. armigera eggs were analysed by the RAPD-PCR technique using four oligonucleotide primers. The four primers revealed 55 presumptive polymorphic loci that were used to estimate the population structures. The estimated values of Fixation Index (Fst) was 0.16, indicating that there was a division of the populations into subpopulations. This Fst value implied the present of reproductive isolation among the populations that might be due to their low migration rate (1.3 insect per generation). This low migration rate indicated the present of low level of gene flow among the populations. A dendrogram resulted from the NTSYS analysis indicated that the West Java and East Java populations of the egg parasitoid had quite wide genetic distances, while within each of the populations there was a subdivision of minor populations. This finding has an important implication on the program to release Trichogramma spp. as a biological control agent. The release of the parasitoid cannot be done randomly, because if we pick up a minor population, the starter or the released population will mate with the local population and multiply, thus the inundation will fail to control the target pest."

"Genetic parameters of bisma maize population under different levels of fertilizer application. I. Additive-dominant variance of grain yield. Sutoro, Abdul Bari, Subandi, and Sudirman Yahya. New maize varieties could be obtained through improvement of their plant populations. The method used in selection in the crop improvement was based on values of their genetic parameters. Bisma is one of the maize varieties that has a broad genetic background. New maize varieties be obtained by improving their population through selection under different environmental conditions. Genetic parameter value were estimated by conducting an experiment under NCD II crossing at Bogor. Twenty seven sets, which were developed from three females and three males of S1 as parents of each set, were evaluated under three different fertilization schemes. Results of the experiment showed that the additive genetic variance was significanlty different from zero, and so among the different levels of fertilizer applications .."