Abstract
Decision support for nutrient application remains an enigma if based on soil nutrient analysis. If the crop could be used as an auxiliary indicator, the plant nutrient status during different growth stages could complement the soil test, improving the fertilizer recommendation. Nutrient absorption and partitioning in the plant are here studied and described with mathematical models. The objective of this study considers the temporal variation of the nutrient uptake rate, which should define crop needs as compared to the critical content in soil solution. A uniform maize crop was grown to observe dry matter accumulation and nutrient content in the plant. The dry matter accumulation followed a sigmoidal model and the macronutrient content a power model. The maximum nutrient absorption occurred at the R4 growth stage, for which the sap concentration was successfully calculated. It is hoped that this new approach of evaluating nutrient sap concentration will help to develop more rational ways to estimate crop fertilizer needs. This new approach has great potential for on-the-go crop sensor-based nutrient application methods and its sensitivity to soil tillage and management systems need to be examined in following studies. If mathematical model reflects management impact adequately, resources for experiments can be saved.
Highlights
Maize (Zea mays L.) is worldwide the most cultivated cereal, its economic importance being manifested by the different ways of consumption, going from human food and animal feed to the high technology industry (Edwards 2009)
This study aims to propose a methodology for characterizing the maize crop with respect to: (i) composition and dry matter production of the different organs during plant development, (ii) extraction and distribution of nutrients in these organs, and (iii) estimate the macronutrient concentration in the stalk sap
Maize crop water requirements for our conditions are in the range 350 to 600 mm, so that the total of 409.6 mm is within this range
Summary
Maize (Zea mays L.) is worldwide the most cultivated cereal, its economic importance being manifested by the different ways of consumption, going from human food and animal feed to the high technology industry (Edwards 2009). In the season 2014/2015 the average Brazil’s productivity was more than 3 times higher, i.e. 5,382 kg.ha-1 and the projection of the Brazilian agribusiness indicates that the harvest of 2023/2024 maize production. Productivity increases in time of the maize crop are due to the development of agriculture in relation to the breeding of plants and management practices, including the correction and fertilization of soils (Bender et al 2013, Ciampitti et al 2013). Crop sensors are being developed for other nutrients, based on optical physics to reveal spectra that reflect plant nutrient concentrations in vivo. In this way management decisions could be met much easier, added to solid scientific concepts and to models as presented here
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
