Spatial Variability of Irrigated Garlic (Allium sativum L.) Production Components

Abstract

<jats:p>Among the crops that are usually grown under irrigation, one can mention garlic, which is a product with high demand in Brazil and the world, it is highly valued in the cuisine of several countries, and is an aggregated crop with high economic value. In 2018, this work was conducted in Yellow Red Latosol. The objective was to characterize the structure and magnitude of the spatial distribution of garlic production components and to map the productive components to visualize spatial distribution and to evaluate the spatial correlation between garlic bulb yield (BY) and other variables of the crop: total plant mass (TPM), number of leaves (NL), floral tassel length (FTL), leaf length (LL), leaf width (LW), pseudostem diameter (PD), shoot wet mass (SWM), shoot dry mass (SDM), number of cloves per bulb (NCB), clove mass (CM), root dry mass (RDM), and irrigation (IRR). All these traits were sampled in a 90-point grid georeferenced. Data analysis using statistical and geostatistical techniques made it possible to verify that the production components and BY, TPM, NL, FTL, LL, LW, PD, SWM, SDM, CM, and IRR presented special dependence. The spatial correlation between BY and TPM, LW, and CM showed a moderate spatial dependence.</jats:p>

Spatial Autocorrelation of Physical Attributes of an Oxisol

“…Crosssemivariograms adjusted to the spherical and Gaussian models. Oliveira et al (2020a) also found the same adjustment models in a study performed with soil physical attributes.…”

“…Table 1 shows the descriptive analysis of the studied attributes. Oliveira et al (2020a) observed that the variability of an attribute can be classified according to the magnitude of its coefficient of variation (CV). The classes were determined as low (CV < 10%), medium (10% < CV < 20%), high (20% < CV < 30%), and very high (CV > 30%).…”

“…2021 A strong spatial dependence evaluator (SDE) occurs when semivariograms have a nugget effect < 25% of the sill, moderate when it is between 25 and 75%, and weak > 75%. According to this classification, which was used by Oliveira et al (2020aOliveira et al ( , 2020b, the values of the variables SD1, PW1, SD2, PW2, and TW2, TW1=f(SD1), PW1= f(FC1), PW2=f(PW1), SD1=f(TP1), and FP1=f(TW1), presented a strong SDE.…”

Spatial Variability of Ecophysiological and Production Components in Irrigated Noble Garlic

“…Due to the increase in the use of precision agriculture in Brazil, geostatistical studies on agronomic attributes related to productivity have been intensified. Precision agriculture is composed of a set of techniques that help farmers manage their crops, increasing production and income, as well as fertilization, harvesting, and spraying efficiencies, thus improving the final quality of the product (Oliveira et al, 2020).…”

Analise de trilha do teor de fósforo nos diferentes constituintes do milho irrigado

“…descreve as funções que este nutriente exerce nas plantas, tais como componentes dos fosfolipídios, ATP, DNA, RNA, açúcares fosfatos e outras moléculas fundamentais no crescimento dos vegetais e neste caso o desenvolvimento dos grãos.O coeficiente de determinação neste estudo foi de 0.9226 que pelo seu alto coeficiente pode ser agregado em próximas melhorias e desenvolvimento para a cultura do milho grão. Cultura muito importante em todo o mundo Oliveira et al, (2020),. e…”