GENERAL INTRODUCTION
INTRODUCTION
For example, Khan et al. 2014) questioned soil K testing based on exchangeable K and indicated that more than 2100 investigated trials showed that crop yield response to KCl fertilization is unlikely. 2015) suggested modifications to soil K testing based on exchangeable K instead of rejecting soil K testing altogether.
JUSTIFICATION FOR THE STUDY
There have been suggestions to introduce modifiers based on K reserves and K binding capacity of soils when formulating fertilizer K recommendations (Haysom 1971; Studies examining the implications of including both K reserves and binding capacity in making fertilizers K recommendations examined, missing.
AIMS AND OBJECTIVES
Rapid measurements of both K reserves and fixation capacity will undoubtedly be useful in such efforts and thus techniques should be sought that will provide such rapid measurements. 4 2) Potassium reserves and fixation capacity vary widely across soils and within soil groups and their inclusion in the formulation of fertilizer K requirement will significantly change fertilizer recommendations.
THESIS OUTLINE
4 2) Potassium reserves and fixation capacity vary widely across soils and within soil groups and their inclusion in the formulation of fertilizer K requirement will significantly change fertilizer recommendations. 3) The mid-infrared spectroscopy (MIR) can successfully predict K reserves and fixation capacity of soils. Levels of reserve K and K fixation are characteristic of the soil and do not change significantly over long periods (Askegaard et al. 2004).
THE DYNAMICS OF SOIL POTASSIUM AND POTASSIUM SOIL
INTRODUCTION
However, most tests used to estimate levels of reserve K and K-fixation capacity are tedious and time-consuming. The remaining 15% of samples had a combination of high to very high reserve K and KRF.
FORMS OF K IN SOILS
TESTS USED TO ELUCIDATE K DYNAMICS IN SOILS
- Exchangeable K
- K fixation
- Isotherms
- Potassium recovery tests and bioassays
- Potassium requirement factor
- Reserve-K
- Boiling nitric acid
- Sodium tetraphenylboron
- Electro-ultrafiltration
- Bioassays and cation exchange resin
- Q/I relationships
FUTURE OF K SOIL TESTS
CONCLUSIONS
60 Figure 4.10 The potassium (K) status of different soil types as represented by (a) K requirements based on exchangeable K and corresponding changes in K requirements due to accounting for (b) levels of reserve K, (c) KRF values, and (d) both reserve-K and KRF. PREDICTION OF POTASSIUM RESERVES AND FIXATION IN SOILS OF THE SOUTH AFRICAN SUGAR INDUSTRY USING MULTIPLE LINEAR REGRESSION AND MID-INFRARED SPECTROSCOPY. The present study investigates the potential of MLR and MIR to predict reserve K and KRF for the soils of the South African sugar industry.
The potential of MLR models and MIR to predict exchangeable K, K reserves and fixation capacity (KRF) of soils of the South African sugar industry was investigated in this study.
SUGARCANE RESPONSE TO POTASSIUM FERTILIZATION ON
INTRODUCTION
Crops growing on soils with low reserve K were most likely to respond to K fertilization, whereas a response on soils with high reserve K was less likely. Regarding K fixation, Wood and Meyer (1986) recognized that soils such as Vertisols with high K fixation require more fertilizer K than soils with low K fixation. This study investigated the response of sugarcane stalk yield, sucrose yield, exchangeable K and sugarcane leaf K concentration to K application in two soils with contrasting levels of reserve K and K fixation.
They hypothesized that sucrose yield would increase in response to K fertilization for sugarcane grown on low K reserve soils but not on high K reserve soils, and that high K fixation would inhibit K uptake, lower K and sucrose in leaves.
MATERIALS AND METHODS
- Trial sites
- Soil characteristics
- Trial establishment and treatments
- Soil and leaf sampling
- Harvesting
- Statistical analysis
Treatments were applied at the beginning of the experiment and after each harvest as shown in Table 3.2. There were no interactions between K and N and P treatments for any of the parameters measured, and responses to N and P are not further discussed in this paper. The tops and bottoms of the leaves were cut off, leaving about 20-30 cm of the central part of the leaf blade.
Yield data could not be obtained for the first crop at Umfolozi due to flooding of the field following heavy rainfall.
RESULTS
40 Figure 3.4 Relationships between applied potassium (K) and exchangeable K after harvest of (a) second ratoon (R2), third ratoon (R3) and fourth ratoon (R4) in Cutaneous Acrisol at Umfolozi and after harvesting the plant (b). culture, first ratoon (R1) and second ratoon (R2), on umbric Acrisol at Doringkop. In contrast, there was a downward trend in exchangeable K with increasing cumulative K removal from the crop in the Acrisol umbric control (Figure 3.5b). Leaf K was not affected by treatments in umbric Acrisol, except in the case of the second raton, where leaf K at 240 kg K ha-1 was significantly higher than the control (Figure 3.6b).
41 Figure 3.5 Changes in topsoil exchangeable potassium (K) with time and cumulative K uptake by sugarcane crop after treatments with zero (untreated) K (a) cutan acrisol at Umfolozi and (b) umbric acrisol at Doringkop.
DISCUSSION
The exchangeable K in the cutaneous Acrisol control, which had a very high reserve K, did not drop below initial levels, but in the umbilical Acrisol it did drop below initial levels. The increase in exchangeable K with the zero K treatment of the cutaneous Acrisol over the years, despite K removal, is most likely explained by the release of reserve K. 44 results were found by Bar-Tal et al. 1991), where applied K was fixed by smectitic soils, but K was released from reserves at zero K treatment. Another aspect to consider is that the increase in exchangeable K in zero K treatments, despite K removal by the crop, occurred only in the cutaneous Acrisol, while there was a decrease in exchangeable K in the umbrian Acrisol.
Leaf K in the Umbrian Acrisol control was below 1.25% and significantly lower than that at 240 kg K ha-1 for the second ratoon.
CONCLUSIONS
45 The results of this study indicated that K reserves and fixation influence the response of exchangeable K, sugarcane stalks and sucrose yields to K application. Further studies are required to investigate the contribution of reserve K reserves and subsoil K reserves to K uptake. It is thought that levels of reserve K and K fixation control the rate of release, but this requires further investigation.
This study demonstrated the importance of including changes based on levels of reserve K and K fixation when calculating K requirements.
INTRODUCTION
MATERIALS AND METHODS
- Statistical analysis
The impact of introducing reserve K and KRF factors into fertilizer recommendations was evaluated by comparing K fertilizer requirements based on exchangeable K alone and those obtained by considering reserve K and KRF levels. 53 The changes in K fertilizer requirements due to the introduction of reserve K and KRF were also calculated (equation 4.3). Fertilizer K requirements based only on exchangeable K are considered original recommendations, and those that consider reserve K and KRF are modified recommendations.
Comparisons between K fertilizer requirements based on exchangeable K and those obtained after calculating K-reserve levels and KRF were made using Microsoft Excel's T-Test: paired two samples for means.
RESULTS
- Exchangeable K
- Reserve-K
- KRF values
- Combination of reserve-K and KRF
- Fertilizer K requirement
54 Figure 4.3 Changes in exchangeable potassium (K) for all soils included in the study, as shown by (a) boxplot and (b) frequency distributions of exchangeable K. 57 Figure 4.7 Changes in the potassium requirement factor (KRF, an indicator of the ability to fix K in ground) as shown by (a) boxplot and (b) KRF frequency distributions for different categories. The introduction of reserve K resulted in a significant reduction in K requirements for all soil types (Figure 4.10b), with an overall mean change of 20%.
Mean changes in K requirements due to the introduction of reserve K and soil KRF were similar to those observed when only reserve K was introduced with the exception of Arenosols and Luvisols (Figure 4.10b, 4.10d).
DISCUSSION
Potassium requirements based on the current approach would be overestimated due to overestimated K fixation for samples that had low to medium reserve K and low KRF. Similarly, K requirements would be overestimated for samples with a combination of high to very high reserve K and low KRF due to underestimation of reserve K and overestimation of K fixation capacity. Potassium requirements for samples with high to very high reserve K and medium KRF would also be overestimated due to underestimated reserve K.
There would be an underestimation of K requirements for samples with low to medium reserve K and high KRF due to underestimated K fixation capacity.
CONCLUSIONS
Literature reports suggest that such a test would reflect three components, namely: exchangeable K, reserve K and K fixation capacity in the soil. Samples with large standardized residuals were not included in the development of the MLR model. Based on the results of the field K response trials, it was clear that fertilizer recommendations need to be modified to account for K reserves and fixation capacity.
Proceedings of the International Symposium on Role of Potassium in Nutrient Management for Sustainable Crop Production in India.
PREDICTING POTASSIUM RESERVES AND FIXATION IN SOILS OF
INTRODUCTION
Traditionally, multiple linear regression (MLR) models have been used to estimate soil properties, the determination of which is time-consuming and laborious (Babaeian et al. 2015). In an attempt to incorporate K-fixing capacity into soil K testing Johnston et al. 1999) used MLR to predict potassium demand factor (KRF, a measure of soil capacity to fix added K) from routinely measured soil properties. Infrared techniques in soil analysis involve the interaction of incident radiation with soil components to produce a spectrum that contains information about the composition of the organic and inorganic phases of soils (Chakraborty et al. 2015).
It appears that little or no attempt has been made to predict reserve K and K fixation using MIR.
MATERIALS AND METHODS
- Materials
- Wet chemistry analysis
- Multiple linear regression models and mid-infrared calibration
This includes the development of MLR models and MIR calibrations for these properties and external validation using an independent set of soil samples. Similarly, some parameters were excluded when developing the MLR model and were identified using stepwise regression. The infrared spectrum is therefore a curve of wavelengths versus intensity of reflected radiation caused by the interaction of incident radiation with soil components.
The quality of the calibration was evaluated in terms of the classification suggested by Niederberger et al. 2015), which uses the coefficient of determination (r2) and the ratio of performance to deviation (RPD) as shown in Table 5.2.
RESULTS
- Multiple linear regression models
- Mid-infrared spectroscopy
71 Table 5.3 Regression models and their corresponding coefficient of determination (r2) and standard error of estimates (SEE) developed for reserve K and potassium requirement factor (KRF) using routinely measured and routinely plus soil properties. The red dashed lines represent 1:1 ratios, while R2 and SEP are the coefficient of determination and standard error of prediction, respectively. The quality of the calibrations is assessed based on the coefficient of determination (r2), ratio of performance to deviation (RPD) and root mean square error of estimation (RMSEE).
The dashed red line represents the 1:1 relationship while R2 and SEP are the coefficient of determination and standard error of prediction, respectively.
DISCUSSION
The poor prediction of reserve-K and KRF MIR calibrations for samples passed through a 0.5 mm sieve relative to a 1 mm sieve was unexpected. The results of this study show that 0.5 mm calibrations poorly predicted reserve K and KRF compared to calibrations from 1 mm samples. The modified criteria apply where mid-infrared is used to estimate reserve K and KRF.
Changes in K requirements due to the introduction of reserve K and KRF modifiers to be used for modified K determination categories.
CONCLUSIONS
The challenge is that measuring K-reserves and fixation capacity is laborious and time-consuming. The aim of this study was to investigate the feasibility of including K reserves and fixation capacity in the soil K test and when formulating fertilizer requirements. Potassium reserves and fixation capacity influenced the response of sugarcane to K fertilization.
In terms of variation, the current study revealed large variations in K reserves and fixation capacity.
GENERAL DISCUSSION AND CONCLUSIONS
INTRODUCTION
Much research has shown the importance of K reserves and fixation capacity in K dynamics in the soil-plant system, but their involvement in soil K testing remains relatively unexplored (Haysom 1971; Wood and Meyer 1986; Johnston et al. This included evaluating the response of sugarcane to K fertilization in soils with contrasting K reserves and fixation capacity; variation in soil K reserves and fixation capacity; and the potential of multiple linear regression (MLR) models and infrared spectroscopy medium (MIR) to predict K reserves and fixing capacity Incorporating these soil properties into soil testing and developing recommendations for fertilizer requirements is feasible if they vary greatly across soils, the variation affecting plant response to fertilization and they are easy to measure (Figure 6.1).
80 Figure 6.1 Three critical factors necessary to make the inclusion of soil properties in the development of fertilizer requirements feasible.
MAIN FINDINGS
It is therefore necessary to assess how the different combinations of K reserves and fixation capacity and the changed K requirements of fertilizer influence the crop response to K application. However, measuring K-reserves and fixation capacity is laborious and time-consuming, but can be estimated using MLR models or MIR. This implies that if the estimation of K reserves and fixation with MLR and MIR is successful, K-responsive soils can be distinguished from non-responsive soils.
Estimation of K reserves and KRF (fixation capacity) using MIR was better than that of MLR.
GENERAL CONLUSIONS
FUTURE RESEARCH
Binet P, el Guessabi L, Salette J (1984) Soil potassium status: the significance of the "Italian ryegrass test". Proceedings of the 22nd Colloquium of the International Potash Institute Bern Switzerland. Proc 22nd Coll of the Int Potash Inst, International Potash Institute Bern Switzerland.
Schroeder BL, Wood AW (2002 ) A re-evaluation of the basis for deriving potassium fertilizer recommendations in the Australian sugar industry.
