L. Sánchez de la Puente

Nutrient interaction in leaves, shoots, and ears in wheat at flowering

Abstract Winter wheat was grown in Mitscherlich pots on soils obtained from 12 fields from the provinces of Salamanca, Valladolid, and Zamora (Spain). The pots were fertilized with eight fertilizer treatments which were combinations of nitrogen, phosphorus, and potasium, and the crop was watered as necessary. Plants were harvested at flowering and plants were divided into different parts: leaves, ears, and the remaining vegetative matter. Dry weight was recorded and the mineral content determined. The relationships between the elements were fitted into straight line, potential, logarithmic, inverse, and quadratic functions. The results showed less relationship among elements in the leaf and their homologous in the shoot than among elements in the leaf and their homologous in the ears, although the former had greater significance especially for the cations. The potential function quantifies the relationship of the leaf‐shoot satisfactorily except for nitrogen and potassium for which potential and inverse, ...

Mineral nutrition of wheat: II Importance of leaves depending on their development and position on the stem

Abstract The frequency of a a highly significant relationship between mineral composition and the weight of wheat leaves indicates that leaf growth is substantially affected by the nutritional status of the plant. Nitrogen and calcium have an important influence on the nutritional status at flowering, while the other cations studied had an important influence at post‐anthesis. The regression coefficient for the mathematical models obtained may have a well‐defined value for each physiological stage of the plant or leaf development. Relationships between the mineral composition of wheat leaves and their wheight were most significant at flowering. Due to their close relationship with the yield parameter, i.e. grain, young leaves are suitable organs for this analysis. Eventually, a thorough study of the dynamics of leaf development and the use of leaves from different positions on the stem is suggested.

Analysis of nine mathematical functions as models for leaf diagnosis in wheat grown in fields

Abstract Winter wheat was grown at five different experimental sites using various nutrient combinations of two nitrogen (N) and three calcium (Ca) doses. The three youngest leaves, including the flag leaf were sampled at anthesis together with the flag leaf post‐anthesis and the grain at final harvest. The leaves were weighed and their mineral nutrient contents analyzed and the grain was also weighed. Of the nine equations that were fitted the potential (log y versus log x) most consistently had the best correlation and, thus, best represents the relationships between leaf dry weights, while the inverse in both variables was best for estimating grain weight from leaf weight. The nutrient content of the leaves was related to leaf dry weight according to the following sequence of maximum R: ? (R = 0.703), potassium (K) (R = 0.580), Ca (R = 0.444), phosphorus (P) (R = 0.359), iron (Fe) (R = 0.291), and magnesium (Mg) (R = 0.290). The square‐root and the quadratic equations best reflected the maximum and min...

Analysis of nine mathematical functions as models for the relationship between the chemical composition and dry weight of leaves, shoots, and ears of wheat

Abstract Winter wheat was grown in Mitscherlich pots on soils obtained from 12 sites from the provinces of Salamanca, Valladolid, and Zamora (Spain). The plants were fertilized with combinations of nitrogen, phosphorus, and potassium, and the crop was watered as necessary. Plants were harvested at flowering and were divided into leaves, ears, and the remaining above‐ground parts. Dry weight was recorded and the mineral content determined. The relationships between nutrient content and dry matter production were fitted by nine functions: quadratic, square‐root, inverse in x, inverse in y, inverse in both variables, and the straight line. Analysis showed that a square‐root function fitted the relationship between mineral content and dry matter production in the different parts of the plant better than the other equations. The quadratic function was also frequently significant and had large coefficients of correlation. However, the parameters of the square‐root functions had smaller standard than the quadrat...

Mineral nutrition of wheat: I. Organ and crop stage relationships

Abstract Winter wheat (Triticum aestivum L. cv. Astral) was grown under seven fertilizer treatments on five experimental sites. Regression analysis was performed to model the relationships between different organ weights in the same or consecutive stages. The frequency of highly significant relationships between weights was higher during flowering and shooting than during the other stages studied: i.e. tillering, post‐anthesis, and harvesting. The relationship between the plant weight and the weights of the flag leaf or the 2nd youngest leaf was closer than that between the plant weight and that of the third youngest leaf and plant weight. The coefficent of correlation was higher than when ear weight was related to the plant weight in post‐anthesis, where there was no 2nd or 3rd youngest leaves. This relationship was closer than in flowering. Plant growth before anthesis was more regular than after anthesis. It appeared that the development of the leaf and of the ear affected the relationships between the...

A simple mathematical model for diagnosis of nutrient content and dry matter production in wheat

The equation y = a + bx α + cx 2α proposed as a general function of nutrition to describe the relationship between the concentration of nutrients in a plant and the production of dry matter. The function has a maximum if b>0˜ and ˜c≤0, which corresponds to the optimal nutritional value; depending on the value of the parameter α it may have a point of inflexion which can occur before or after the maximum and at varying distances from it. The parameter a can be set to zero if necessary in which case the function passes through the origin. Hence its parametric form is flexible and suitable for describing the incidence of nutrients in dry matter production. Furthermore, it is very simple and easy to use. Its use in describing leaves of field-grown wheat at different stages of growth seems to indicate that it has some applicability compared with other commonly used functions, and given its flexibility it can offer advances in the understanding of mineral nutrition in plants. Although further assays are necessary, so that the physiological stage of the plant sample can be accurately defined, it seems that the value of α may define the physiological state of the plant, the particular circumstances of cultivation defining the parameters b and c. Thus, for example, in 1987, in experimental trials of wheat close to flowering, the value of α for nitrogen in the flag leaf was 1.75, for the second leaf 1.25, and 1.00 for the third. The corresponding stages of growth, although not very precisely defined, were close to the maximum for the first leaf, slightly declining in the second, but more so for the third. Post-anthesis, nitrogen in the first leaf had an α-value of 0.75; its physiological state now corresponding to a sharp decline in foliar weight. Other situations would give characteristic values of α, whose calibration over several carefully conducted trials would be used in plant nutrition diagnosis.

Square root and quadratic equations for the study of leaf diagnosis in wheat

Abstract Difficulties in the use of diagnosis in annual plants have led the authors to explore the quadratic and square‐root functions as models for nutritional status in wheat. These equations were chosen to explain more readily the physiological aspects that lie behind the relationship between nutrient content and yield. Ninety‐one equations were fitted using the results from five sets of experiments. In all equations x‐values were the mineral concentrations in the leafs and y‐values the dry weight of leaves, grain or aboveground matter. Although both equations represent the relationship well, the square‐root function is considered more suitable because its asymmetry reflects the observed behavior of growth with respect to nutrition.

Application of the “Delapuente” Equation in Field Trials of Wheat

Abstract The equation, y = bx α + cx 2α is used to describe the incidence of nutrients in the leaf at flowering in terms of dry matter production. The results for five fields of wheat were extremely satisfactory and gave the following results: of 15 possible combinations (five fields × three distinct leaves) the equation fitted well to 13 in the case of nitrogen, 11 for calcium and nine for iron; for phosphorus the results were good in seven cases, with six each for the nutrients potassium, magnesium and manganese. The best fits were for nitrogen, and declined in terms of goodness of fit in the order magnesium, calcium, potassium, manganese, iron, and phosphorus. Other forms of equation that are typically used in this work were less applicable and of poorer statistical significance. The action of a nutrient on the plant defines the parameters b (of positive sign, indicating stimulation) and c (usually negative implying inhibition) and the exponent α, responsible for the shape of the curve. In passing from leaf 1 to leaf 3, α generally declines, so that the first leaf (where the point of inflexion is closest to the maximum) is very close to its maximum development and at a late stage as a sink. The other leaves, particularly the third, are in a declining dry matter phase and therefore “source” organs. The different physiological state of the leaves is also reflected in the values of the parameters b and c; particularly well here in that large differences can be observed according to the different nutrients. Thus, in the case of nitrogen, both parameters increase (in absolute terms) according to leaf number thereby indicating greater effects, both stimulatory and inhibitory, on the dry matter content of the third leaf for a given nutrient concentration. The contrary is the case for calcium and magnesium. The high values of the parameters for magnesium indicate a strong influence on the plant. The three parameters, then, quantify the action of a nutrient, including all the conditions of the plant culture. However, the form of the curve will be more strictly related to the specific organ and its physiological state.