Manual para processamento de pimentas (Capsicum spp) desidratada.

Introdução. Secagem de pimenta - Processo utilizado pelos produtores. Desidratação de pimenta - Secagem artificial em secador de cabine. Higiene e sanificação. Recomendações gerais para as etapas de processamento. Vantagens deste processo. Referências bibliográficas.bitstream/item/79988/1/doc63-2005.pd

Manual para a produção em pequena escala de conserva de tomate desidratado.

Higiene e sanitização. Fluxograma básico de processamento de tomate. Etapas de processamento de tomate seco. Elaboração de conserva de tomate. Etapas de processamento de conserva. Como estimar o lucro e os custos envolvidos no processamento.bitstream/item/65526/1/2003-DOC-0052.pd

Secagem como método de conservação de frutas.

Secagem como método de conservação: secagem natural x desidratação; tipos de secadores utilizados para frutas. Secadores de frutas desenvolvidos pela Embrapa Agroindústria de Alimentos: secador de frutas elétrico; secador de frutas solar; higiene no processamento de frutas. Processamento de frutas desidratadas: Banana; Uva; Ameixa; Pêssego; Figo; Abacaxi; Manga.bitstream/item/65529/1/2003-DOC-0054.pd

Manual para construção de um desidratador de produtos agroindustriais.

bitstream/item/132845/1/DOC-121.pd

Genotyping Validates the Efficacy of Photographic Identification in a Capture-Mark-Recapture Study Based on the Head Scale Patterns of the Prairie Lizard (\u3ci\u3eSceloporus consobrinus\u3c/i\u3e)

Population studies often incorporate capture‐mark‐recapture (CMR) techniques to gather information on long‐term biological and demographic characteristics. A fundamental requirement for CMR studies is that an individual must be uniquely and permanently marked to ensure reliable reidentification throughout its lifespan. Photographic identification involving automated photographic identification software has become a popular and efficient noninvasive method for identifying individuals based on natural markings. However, few studies have (a) robustly assessed the performance of automated programs by using a double‐marking system or (b) determined their efficacy for long‐term studies by incorporating multi‐year data. Here, we evaluated the performance of the program Interactive Individual Identification System (I3S) by cross‐validating photographic identifications based on the head scale pattern of the prairie lizard (Sceloporus consobrinus) with individual microsatellite genotyping (N = 863). Further, we assessed the efficacy of the program to identify individuals over time by comparing error rates between within‐year and between‐year recaptures. Recaptured lizards were correctly identified by I3S in 94.1% of cases. We estimated a false rejection rate (FRR) of 5.9% and a false acceptance rate (FAR) of 0%. By using I3S, we correctly identified 97.8% of within‐year recaptures (FRR = 2.2%; FAR = 0%) and 91.1% of between‐year recaptures (FRR = 8.9%; FAR = 0%). Misidentifications were primarily due to poor photograph quality (N = 4). However, two misidentifications were caused by indistinct scale configuration due to scale damage (N = 1) and ontogenetic changes in head scalation between capture events (N = 1). We conclude that automated photographic identification based on head scale patterns is a reliable and accurate method for identifying individuals over time. Because many lizard or reptilian species possess variable head squamation, this method has potential for successful application in many species