ABSTRACT
Sufficient nutrient application is one of the most important factors in producing quality citrus fruits. One of the main guides in planning citrus fertilizer programs is by directly monitoring the plant nutrient content. However, this requires analysis of a large number of leaf samples using expensive and time-consuming chemical techniques. Over the last 5 years, it has been demonstrated that it is possible to quantitatively estimate certain nutritional elements in citrus leaves by using the spectral reflectance values, obtained by using near infrared reflectance spectroscopy (NIRS). This technique is rapid, non-destructive, cost-effective and environmentally friendly. Therefore, the estimation of macro and micronutrients in citrus leaves by this method would be beneficial in identifying the mineral status of the trees. However, to be used effectively NIRS must be evaluated against the standard techniques across different cultivars. In this study, NIRS spectral analysis, and subsequent nutrient estimations for N, K, Ca, Mg, B, Fe, Cu, Mn, and Zn concentration, were performed using 217 leaf samples from different citrus trees species. Partial least square regression and different pre-processing signal treatments were used to generate the best estimation against the current best practice techniques. It was verified a high proficiency in the estimation of N (Rv = 0.99) and Ca (Rv = 0.98) as well as achieving acceptable estimation for K, Mg, Fe, and Zn. However, no successful calibrations were obtained for the estimation of B, Cu, and Mn.
ABSTRACT
Sewage sludge application to agricultural soils is a common practice in several countries in the European Union. Nevertheless, the application dose constitutes an essential aspect that must be taken into account in order to minimize environmental impacts. In this study, near infrared reflectance spectroscopy (NIRS) was used to estimate in sewage sludge samples several parameters related to agronomic and environmental issues, such as the contents in organic matter, nitrogen and other nutrients, metals and carbon fractions, among others. In our study (using 380 biosolid samples), two regression models were fitted: the common partial least square regression (PLSR) and the penalized signal regression (PSR). Using PLSR, NIRS became a feasible tool to estimate several parameters with good goodness of fit, such as total organic matter, total organic carbon, total nitrogen, water-soluble carbon, extractable organic carbon, fulvic acid-like carbon, electrical conductivity, Mg, Fe and Cr, among other parameters, in sewage sludge samples. For parameters such as C/N ratio, humic acid-like carbon, humification index, the percentage of humic acid-like carbon, the polymerization ratio, P, K, Cu, Pb, Zn, Ni and Hg, the performance of NIRS calibrations developed with PLSR was not sufficiently good. Nevertheless, the use of PSR provided successful calibrations for all parameters.
Subject(s)
Sewage , Spectroscopy, Near-Infrared/methods , Electric Conductivity , Metals, Heavy/analysisABSTRACT
BACKGROUND: Several tomato landraces are very popular in south-eastern Spain for their organoleptic fruit quality, but these cultivars are highly susceptible to several viruses. A breeding programme is being carried out for the introduction of virus resistances into these landraces. In the last steps of our breeding programme a high number of breeding lines must be evaluated for agronomic and organoleptic quality parameters. Near infrared reflectance spectroscopy (NIRS) technology shows considerable promise and is ideally suited to the requirements of breeders. RESULTS: Significant differences between a set of 35 tomato breeding lines, seven landraces and one commercial hybrid were observed for quality and mineral content parameters, suggesting that there are considerable levels of genetic diversity between the cultivar groups studied. Using NIRS on dry samples of tomato constitutes a feasible technique to estimate the content of several minerals (C, N, P, K, Ca, Na, Mn, Mg and Cu) according to the coefficient of determination for calibration (R(2) > 0.90). NIRS estimations of soluble solids content and titratable acidity obtained were considered useful only for general screening purposes. CONCLUSIONS: NIRS technology may be a useful tool in the selection of lines coming out of tomato breeding programs, allowing a quick estimation of mineral content. However, the estimation of soluble solids content and titratable acidity by NIRS must be improved.
