Fertilizer Recommendations Research Articles

DRIS norms for nutritional diagnosis of dwarf cashew

Nutritional evaluation of plants through leaf tissue analysis allows diagnosing the balance between nutrients and helps in the eventual recommendation of fertilization. The objective of this study was to apply DRIS norms and establish the appropriate nutrient contents in dwarf cashew leaves. In 248 plots with the dwarf cashew clones ‘CCP 76,’ ‘Embrapa 51,’ ‘BRS 189,’ ‘BRS 226,’ ‘BRS 265’ and ‘BRS 555’ leaves were collected for analysis of macro and micronutrients, in addition to sodium, and the respective nut yields (kg ha−1) were obtained. Of the total number of plots, 128 were considered to be high-yielding, which corresponded to 51.6% of the population. The decreasing order of nutrients (plus Na) with the highest frequency of limitation due to lack in the high-yielding subpopulation was: Na > Cu > S > P > K = Mg > B > N > Mn > Fe = Zn > Ca. Nutrients (plus Na) with the highest frequency of limitation due to excess, in descending order, were: Na > S > Cu > Mn > Ca = Mg > P = Fe > K > N > B = Zn. The appropriate ranges obtained by DRIS were: 13.0-15.5, 0.8-1.1, 7.6-9.3, 1.4-2.1, 1.3-1.7, 0.7-0.9 and 1.1-1.6 g kg−1 for N, P, K, Ca, Mg, S and Na, and 9.7-19.3, 5.4-7.4, 19.3-29.8, 39.6-70.8 and 11.7-17.3 mg kg−1 for B, Cu, Fe, Mn, and Zn, respectively.

Recommendations of N, P, and K site-spesific for maize cropping in the Jeneponto District of South Sulawesi

Abstract The incompatibility of N, P, and K rates for maize plants causes a decrease in plant productivity and farmer income. Therefore, there is a need for appropriate N, P, and K fertilizer recommendations based on agroecosystems that farmers can apply. This research aims to obtain location-specific N, P, and K fertilization recommendations for maize based on the agroecosystem in Jeneponto Regency, South Sulawesi. This research was conducted in Jeneponto District, South Sulawesi, from March to October 2021. The research used a survey method adapted to the questions in the Nutrient Expert (NE) program form. The research showed that the optimum fertilizer recommendation for maize in Jeneponto District was 170 – 190 kg N ha−1, 30 – 60 kg P2O5 ha−1, and 33 – 63 kg K2O ha−1, with a 9 – 10 t/ha yield. Using these recommendations, they will gain a higher profit and R-C ratio than the farmer’s existing fertilization, namely, a profit of RP. 30,499,400 (Rp. 30,276,000 – 30,697,000) with an R-C ratio of 4.05 (3.96 – 4.13), whereas if using existing fertilization at the farmer level, they will gain a profit of Rp. 19,397,000 (Rp. 14,215,000 – Rp. 25,735,000) with an R-C ratio of 2.20 (1.81 – 2.75).

Sunflower-nitrogen calibration based on the amount of mineral nitrogen in soil under rainfed conditions in thrace region

Sunflower is grown under both rainfed and irrigated conditions in all regions to meet the vegetable oil needs of Türkiye, however, in the Thrace region, it is the main rotation crop grown under rainfed conditions after wheat. This study was conducted in the Thrace Region between 2013 and 2016 in order to evaluate the parameters that can be used as an index for nitrogen fertilization recommendations for sunflower plant. For this purpose, organic matter and saturation were determined in soil samples taken from 0-20 cm depth before the experiment and ammonium and nitrate contents were determined in soil samples taken from 0-30 cm, 30-60 cm, and 60-90 cm depths. Within the scope of the study, 27 field trials were conducted over four years. Nitrogen levels of 0 (control), 3, 6, 9, and 12 kg da-1 were implemented in the trials conducted in a Latin square experimental design. In this study, log (279.9-y) = log279.9-0.090b1-0.117x Mitscherlich calibration equations were determined based on 0-30 cm ammonium+nitrate content in the soil.

Assessment of soil fertility in jute (Corchorus olitorius L.) cultivated land and nutritive value of its plant parts

The samples of soil, leaves, and shoots of jute were collected from twenty spots of jute (variety BJRI-Tossa-8) fields from different locations in the Narail district of Bangladesh under AEZ-12 during the year 2022. The study intended to evaluate the soil’s physicochemical properties and nutrient concentrations in jute leaves and shoots of 120 days old plants (at the harvesting time of the plant). The soil pH was neutral to slightly alkaline (6.6 to 7.4), with organic matter content from 1.03 to 1.71%. Electrical conductivity was found non-saline which was 40 to 150 μS/cm at 0 to 15 cm depth. The dominant soil textural class was clay. The total N, P, and S in soils were found to be 0.21 to 0.31%, 0.027 to 0.0283% and 0.0002 to 0.0023%, respectively and available N, P, and S were found to be 0.0058 to 0.0087%, 0.0007 to 0.0018%, and 0.0001 to 0.0006%. The nutritional values of N, P, and S in leaves ranged from 3.00 to 11.75%, 0.2281 to 0.5627%, and 0.0056 to 0.0197%, respectively. The total N, P, and S concentrations in the shoots were 0.17 to 5.07%, 0.0012 to 0.2935%, and 0.0002 to 0.0011%, respectively. The study indicated that jute leaves are enriched in nutrition and may be a good source of nourishment for human health. This research also illustrated that the jute field had low to medium fertility soil status. It is suggested that the farmers of AEZ-12 should follow the fertilizer recommendation doses in jute cultivation for higher fiber yield and allow sufficient decomposition of jute roots and debris to sustain succeeding crop production and soil fertility. The study has given new information and guidelines for the researcher for future investigation. Biodivers. Conserv. Bioresour. Manag. 2024, 10(1): 35-44

Impact of varied tillage practices and phosphorus fertilization regimes on wheat yield and grain quality parameters in a five-year corn-wheat rotation system

Choosing appropriate tillage methods and applying the right amount of chemical fertilizers are pivotal for optimizing wheat management and enhancing wheat quality. This study investigated the influence of conservation agriculture and phosphorus levels on nutrient content, yield components, and quality traits of wheat in a corn-wheat rotation. Conducted over five years in field conditions, the study employed a randomized complete block design with tillage treatments (conventional tillage, CT; minimum tillage, MT; and no tillage, NT) and phosphorus levels (no fertilizer use, P0; and 100% fertilizer recommendation, PR) as factors. Soil samples were collected during the fourth year (2021–2022). Results revealed significant impacts of tillage methods and phosphorus levels on wheat straw and grain nutrient composition, yield components, and quality traits. Conventional tillage yielded the highest values for protein content (12%), Zeleny sedimentation volume (20.33 mL), hardness index (45), water absorption (64.12%), and wet gluten content (25.83%). Additionally, phosphorus fertilizer application positively influenced protein percentage, gluten weight, and gluten index. The study highlights the potential of strategic soil management, particularly conventional tillage combined with phosphorus fertilization, to enhance wheat quality and yield. By elucidating these relationships, the findings contribute to optimizing wheat cultivation practices and advancing the development of superior wheat cultivars for baking applications.

Optimizing bioenergy sorghum productivity and nutrient removal in Illinois: Impact of nitrogen fertilization under diverse marginal conditions

Context or problemBioenergy sorghum (Sorghum bicolor L. Moench) is a promising crop for contributing to the United States bioenergy supply. However, the varying limitations of the marginal lands targeted for its cultivation present a management challenge. ObjectiveThis two-year study aimed to investigate how the limitations associated with marginal cropland impact the effects of nitrogen fertilization on the yield of bioenergy sorghum and the uptake of 11 macro- (N, P, K, Ca, Mg, and S) and micronutrients (Fe, Mn, Zn, Cu, and B). MethodsThe study contrasted prime cropland in central Illinois (Urbana) with three marginal cropland sites in southern (Ewing) and central Illinois (Fairbury and Pesotum). These marginal cropland sites are characterized by varying limitations, including low soil fertility (P and K limitations), leaching and erosion, and flooding, respectively. Four nitrogen rates (0, 56, 112, and 168 kg N ha−1) were tested under eight environments. ResultsThe average yields and ranges of sorghum biomass were 20.2 (17.0–23.2) Mg ha−1 in Urbana, 18.1 (13.1–19.8) Mg ha−1 in Ewing, 13.8 (9.0–17.3) Mg ha−1 in Fairbury, and 23.3 (14.6–33.0) Mg ha−1 in Pesotum. Optimal N rates were 56 N in Pesotum and 112 N in Urbana, Ewing, and Fairbury. Tissue macronutrient contents in Urbana were generally higher than in the marginal croplands, while micronutrient contents did not show discernible trends. Increasing N rate generally correlated with the macronutrient removal except in Ewing. ConclusionComparable sorghum biomass yields were observed between prime and marginal croplands (averaging 18.3 Mg ha−1), but optimal N rates varied between 56 N and 112 N. This suggests that yield gaps can be narrowed by applying the optimal N rates for the respective locations. However, increased removals of macronutrients, especially P and K, with increasing yields indicate the need to revise fertilizer recommendations, particularly for soils deficient in these nutrients. Implications or significanceOur study suggests that while sorghum production on marginal cropland is feasible, N management needs to be adapted to the unique limitations associated with various types of marginal cropland.

A better understanding of the effectiveness of placed phosphorus fertilisation with struvite for silage maize: A pot experiment

Struvite is emerging as a circular, slow-release phosphorus (P) fertiliser. However, its effectiveness for crops and its impact on soil P tests still remain largely unclear. We analysed the effectiveness of struvite as a row fertiliser in a pot experiment with maize in a sandy soil and a loamy soil, both exhibiting a low agronomic soil P status. Maize was seeded in both soils, amended with either granular struvite or water-soluble di-ammonium phosphate (DAP) as row fertilisers. A positive control received an excess of sodium phosphate, mixed homogeneously through both soils; a negative control did not receive additional P. We measured the agronomic maize performance at the end of the vegetative growth stage (V10) and assessed the suitability of two established agronomic soil P tests (i.e. P-CaCl2 and P-AL) to predict plant-available P in the soils amended with struvite. Furthermore, we performed an additional batch experiment to better understand the dissolution dynamics of struvite during a prolonged period of extraction of soil in 0.01 M CaCl2. Placed struvite application led to a lower performance of maize in comparison to DAP in terms of biomass production as well as P uptake (53 and 71 % lower, respectively). Yet the agronomic performance of struvite in general was higher than the performance of the negative control, confirming the potential of struvite as an emerging P fertiliser. Surprisingly, both soils fertilised with struvite showed a significantly higher soil P test than any other P treatment in our pot experiment. This was an artefact due to the dissolution of residual struvite granules during the soil extraction procedures. These results call for a reconsideration of how to interpret P-CaCl2 and P-AL as a basis for P fertiliser recommendations for soils receiving struvite as a P fertiliser.

A Portable Determination Method for the Soil Rapid Available Potassium via Enhanced NaBPh4 Turbidimetry

ABSTRACT Monitoring soil rapidly available potassium (RAK) reserves is extremely significant for developing precise fertilizer recommendations. The sodium tetraphenylborate (NaBPh4)-spectrophotometer method is applied to the detection of soil RAK content as a speedy, efficient and portable approach. However, the detection accuracy of this method is inferior to the ammonium acetate (NH4OAc)-flame photometer method. Here, the detection processes of the NaBPh4 turbidimetry were optimized to find the correlation with the NH4OAc method, further discussed the reasons for the different results by the two methods. The maximum relative error is 13% after conversion through the calibration curve. In addition, the accuracy of the calibration curve was verified by selecting non-fitting soil samples from two experimental sites. Therefore, our work proposes that the NaBPh4 turbidimetry, more convenient and rapid, can accurately detect the soil RAK content in the field. It provides an experimental guidance for the detection method of soil RAK content based on ultraviolet detection and on-site rapid detection devices.

Soil biological and physical measurements did not improve the predictability of corn response to phosphorus fertilization

AbstractIncluding soil health and physical measurements with traditional soil fertility measurements has the potential to improve corn (Zea mays L.) P fertilizer recommendations. The objectives for this study were to (1) evaluate the accuracy of current South Dakota corn P recommendations in predicting yield increases and (2) determine if the predictability of yield response to P fertilization improves by including selected soil biological, physical, and chemical measurements. This project was conducted in central and eastern South Dakota from 2019 to 2022 at 117 experimental sites that varied in management, landform, and soil type. A treatment of 48.9 kg P2O5‐P ha−1 was compared to a control with no P fertilizer. Soil samples (0–15 cm) collected before fertilization were analyzed for selected soil physical, chemical, and biological parameters. Analysis suggested that the current critical P value of 16 mg Olsen‐P kg−1 was still accurate as it was still within the 68% confidence interval for the linear (12–19 mg kg−1) and quadratic plateau (16–26 mg kg−1) models. Using the critical value of 16 mg Olsen‐P kg−1, we correctly predicted P responsiveness 70% of the time. The accuracy of predicting P responsiveness was not further improved by considering selected enzymes, permanganate oxidizable C, soil respiration, total C, or total N, but was improved by considering pH, soil organic matter, and apparent cation exchange capacity. Therefore, the use of typical soil fertility measurements without soil physical and biological measurements is currently the best option for predicting the responsiveness of corn to P fertilization in South Dakota.

Models and sufficiency interpretation for estimating critical soil test values for the Fertilizer Recommendation Support Tool

AbstractSoil test correlation determines whether a soil test can be used to predict the need for fertilization based on the critical soil test value (CSTV). Our objectives were to compare the CSTV estimated from five combinations of correlation models and yield sufficiency interpretations and to select one method for soil test correlation performed with the Fertilizer Recommendation Support Tool (FRST). Four models were fit to three datasets with strong (Mehlich‐1 K), moderate (Mehlich‐3 K), or weak (Olsen P) correlations between soil test P or K and crop relative yield. We tested the arcsine‐log calibration curve (ALCC), exponential (EXP), linear plateau (LP), and quadratic plateau (QP) models. The CSTV was defined as 95% of the maximum predicted yield for the ALCC and EXP methods, the join point for LP, and both the join point and 95% of the maximum for the QP providing five CSTV predictions. The five CSTVs ranged from 46 to 66 mg kg−1 for the Mehlich‐1 K dataset, 115 to 165 mg kg−1 for the Mehlich‐3 K dataset, and 7 to 16 mg kg−1 for the Olsen P dataset. Ten pairwise comparisons showed the estimated CSTV was numerically and sometimes statistically influenced by the model and sufficiency level interpretation. Despite differences among CSTVs, the frequency of significant yield responses above and below the predicted CSTV was generally comparable among the methods, with false‐negative errors occurring at 0%–18% of sites for a given dataset. The QP model with a CSTV at 95% of the predicted maximum was selected as the modeling approach for FRST.

Combined Effect of Potassium Fertiliser, Saline Irrigation Water and Humic Acids On Soil Acidity and Yield Components of Pepper (Capsicum annuum L)

A field experiment was conducted to adapt seedlings of sweet pepper, also called “California Wonder”, to salinity and the role of humic acid and potassium fertiliser in reducing the effect of salinity on the plant. A three-factorial field experiment was conducted according to the Complete Random Block Design, with three replications during the spring season of 2018 to study the humic acid and potassium fertiliser role in enhancing the salt tolerance of pepper plants. The first factor included four levels of saline water irrigation, namely 2, 4, 6 and 8 dS.m-1. The second factor included a foliar application of three levels of humic acids i.e., 0, 25 and 50 kg.h-1. The third factor represents the addition of three levels of potassium fertiliser (potassium sulphate of 50% K2O according to the fertiliser recommendation of 0, 75 and 150 kg. h-1. The considered plant and soil traits were branch per plant, stem diameter (mm), percentage of protein in the fruits and soil pH. The results obtained from the experiment can be summed up above the treatment of air conditioning at saline level 6 ds m-1 in branch per plant with 12.3 and the most significant results obtained from the experiment can be summed up above the treatment of air conditioning at saline level 4 ds m-1 in stem diameter 2.03 mm. The results showed a decrease in branch per plant and stem diameter (mm) by increasing the salinity of irrigation water by 8 ds m-1 and the increase in the addition of humic acid and potassium fertiliser. The results showed a decrease in soil acidity (pH) increasing the salinity of irrigation and increasing fruit protein content by increasing the salinity.

Ecophysiology of Soursop Seedlings Irrigated with Fish Farming Effluent under NPK Doses

Soursop (Annona muricata L.) is a tropical fruit grown in the semi-arid region of Brazil, where problems of quantitative and qualitative scarcity of water for irrigation are frequent. Using alternative water sources, such as fish farming effluents, can increase water availability; however, it presents risks due to its high salinity levels. We aimed to evaluate the effect of irrigation with saline fish farming effluent and NPK doses on soursop seedlings’ ecophysiology. We conducted a greenhouse experiment using a randomized complete block design with a 2 × 5 factorial scheme. The factors consisted of two irrigation water sources (local supply water with 0.5 dS m−1 and fish farming effluent with 3.5 dS m−1) and five doses of NPK (25%, 50%, 75%, 100%, and 125% of the fertilizer recommendation of 100:300:150 mg dm−3 of N:P2O5:K2O for soil). The soursop seedlings showed the best growth results for plant height, stem diameter, and shoot dry mass when irrigated with low-salinity water at 95% of the recommended NPK dose. However, under saline stress, the soursop seedlings showed optimal growth when fertilized with 69% of NPK dose. We recommend the following NPK fertilization for soursop seedlings: 95:285:143 mg dm−3 of N:P2O5:K2O for those irrigated with low-salinity water and 69:207:104 mg dm−3 for those irrigated with fish farm effluent. Irrigating with fish farm effluent can be a practical option for soursop seedlings as it can help save fertilizers and promote environmental sustainability.

Analisis Biaya Pemupukan Tanaman Menghasilkan Kelapa Sawit (Elaeis Guineensis Jacq.) Divisi I Kebun Langga Payung P.T. Tapian Nadenggan

Fertilizer is one of the main factors that determines plant productivity. One alternative fertilizer cost efficiency measure that can be taken is to increase the effectiveness of fertilizers in the field (Poeloengan et. al., 2000). The aim of fertilization in the field can be formulated in general policy as follows, the target of fertilizer application is to achieve 100% fertilizer application in the field with the correct application method and the right time of fertilization and each plant receives the amount of fertilizer according to the dose specified in the fertilizer recommendations to ensure adequate plant nutrients. and achieving high production for Producing Crops (PC) (Fathoni et. al., 2011). This research uses a descriptive analysis method regarding the costs of fertilization on high-yielding oil palm plants in Division I of Langga Payung Plantation P.T. Tapian Nadenggan. Observation indicators are data on recommendations for oil palm plant fertilization (type and dose of fertilizer in 2016-2018); Fertilization realization data for 2016-2018; Fertilization recommendations and fertilizer realization are made for a period of one year. Recommendation and realization data were analyzed using Student's t-Test at α = 5% to compare data per year. Cost of fertilizing plants producing oil palm (Elaeis guineensis Jacq.) Division I Langga Payung Plantation P.T. Tapian Nadenggan is influenced by 3 components, namely: Purchase of fertilizer, transportation and wages of sowers, which is based on research data that the components of fertilizer costs in 2018 are not significantly different from the components of fertilizer costs in 2017 and 2016. Likewise, the fertilization cost component in 2017 is not significantly different from the fertilization cost component in 2016.

Tree Leaves Based Disease Prediction and Fertilizer Recommendation Using Deep Learning Algorithm

Tree Leaves Based Disease Prediction and Fertilizer Recommendation Using Deep Learning Algorithm

Soil moisture and probe characteristics affect core integrity and soil test results

AbstractProper soil sampling is critical for accurate fertilizer recommendations. Samples collected in extremely wet or dry conditions may compromise the integrity of the sample and influence analytical results. We evaluated the effects of six soil moistures, two sampling depths (0–10 and 0–15 cm), and two soil probes on soil core uniformity and soil test results. Moisture treatments encompassed a range from dry (11.2%–18.5% moisture) to saturated conditions in Captina, Dewitt, Calhoun, and Calloway silt loam soils. Core depth and dry core weight were measured in all soils, and pH and Mehlich‐3 extractable P, K, S, and Zn were assessed for Calhoun and Calloway soils. Soil moisture, probe, or their interaction influenced core depth and weight, while chemical properties were significantly affected only by soil moisture. Sampling very dry or saturated soils compromised the collection of uniform cores mainly for the 0‐ to 15‐cm depth. Soil pH tended to increase with increasing moisture, but the mean values fluctuated only ±0.3 units. Across soils and depths, extractable S consistently decreased by 16%–48% as soil moisture at sampling time increased. Phosphorus was affected by soil moisture for 0–15 cm samples in both soils but showed no clear pattern. Soil moisture at the time of sampling affected soil test K for both soils and sample depths with individual cores varying up to 47 mg kg−1 (i.e., 59–106 mg kg−1). Greater soil test P and K variability occurred for very dry and wet conditions, which often prohibit collecting samples to the proper depth and could impact fertilizer rate recommendations.

Developing Vis–NIR libraries to predict cation exchange capacity (CEC) and pH in Australian sugarcane soil

In sugarcane growing areas of Queensland Australia, management of soil condition requires information about soil chemical properties (i.e., cation exchange capacity [CEC], and pH), because they are used to make fertiliser recommendations. While laboratory analysis is cost prohibitive the development of visible near–infrared (Vis–NIR) spectroscopy libraries might be useful. The aims of this study was to compare: i) linear (i.e., Partial least squares regression [PLSR]) and machine learning (i.e., Cubist, Random Forest [RF] and Support vector machine [SVM]) algorithms in terms of their calibration strength (i.e., coefficient of determination (R2); ii) depth-specific (i.e., topsoil [0 – 0.3 m], subsurface [0.3 – 0.6 m], subsoil [0.6 – 0.9 m] and deep subsoil [0.9 – 1.2 m]) and multi-depth libraries; iii) prediction R2, agreement (Lin’s concordance correlation coefficient [LCCC]) and accuracy (ratio of performance to interquartile [RPIQ]); and iv) minimum number of calibration sample locations (i.e., n = 400, 350, …, 50). For depth-specific calibration for CEC, strong calibration R2 was achieved for the subsurface (i.e., RF [0.95], Cubist [0.93], PLSR [0.88] and SVM [0.81]), and for pH, the largest R2 was for deep subsoil (i.e., RF [0.91], followed by PLSR [0.80], Cubist [0.79] and SVM [0.56]), with subsurface, and deep subsoil similar, with topsoil R2 smaller. In terms of model prediction of depth-specific, Cubist was superior to PLSR, RF and SVM for CEC, and PLSR was the best for pH. For example, agreement for topsoil CEC was substantial for Cubist (0.80) and PLSR (0.80), but moderate for RF (0.69) and poor for SVM (0.59). For subsurface (0.9), subsoil (0.91) and deep subsoil (0.92), the agreements were perfect for CEC using Cubist. In terms of multi-depth calibration for CEC it was strong for RF (R2 = 0.94), Cubist (0.92), PLSR (0.81) and SVM (0.72), but for prediction agreement, Cubist (LCCC = 0.92) was perfect, with PLSR (0.85), RF (0.84) and SVM (0.83) substantial. This was also the case for pH (0.84) substantial. However, there are efficiencies in developing a multi-depth calibration. Moreover, the minimum number of calibration sample sites required was 300 (i.e., 1,200 samples) (1.78 sites/ha). The results have implications for using a Vis–NIR library to replace traditional soil laboratory analysis and for fertiliser recommendations for sugarcane soil.

Analysis of Soil Health Parameters to Identify Important Soil Nutrients and Weights Using Feature Engineering for Multiple Agri-Advices

Introduction:: Identification of important soil nutrients is a very important task for precision farming and developing efficient machine learning models. Method:: The existing work shows that the patent is filed and published on a method and device for assessment of soil health parameters and recommendation of fertilizers. The existing work is done for one advice at a time not for several advices. Multiple advices that are taken into account for the task are appropriate crops, organic fertilizer, and combination 1 and combination 2 of fertilizers. objective: Apply feature selection techniques based on Chi-Square, ANOVA and Mutual Information Gain scoring functions such as Select K Best and Select Percentile for multiple agri-advice dataset of Pune District regions to identify important soil health features to reduce the complexity of classification models and in turn reduce space and the computational time of different classification models. Result:: This paper presented results of feature selection techniques based on Chi-Square, ANOVA and Mutual Information Gain scoring functions such as Select K Best and Select Percentile for multiple agri-advice datasets of Pune District regions to identify important soil health features. Conclusion:: As per Chi-Square, ANOVA and Mutual Information scoring functions with Select K Best and Select Percentile techniques ‘Mn’ was the most important parameter and Cu’ and ‘B’ were the least important parameters among all 11 parameters common in 4 agriculture advices. Whereas Ph, K, Fe, 'OC', 'N', 'S', 'Mn', and 'P' will be used for future research work on the development of an efficient classification algorithm for multi-advice generators.

P-chromophore stability of Mehlich-1 and Mehlich-3 under Braga & Defelipo or Murphy & Riley dosing methods

ABSTRACT The performance of colorimetric methods for P quantification has been overlooked by researchers for decades. We investigated the performance of two blue colorimetric methods for P quantification, Braga and Defelipo (B&D) and Murphy and Riley (M&R), using two commonly soil P extractants, Mehlich-1 (M1) and Mehlich-3 (M3). Specifically, we evaluated the color development time and its stability in different soil extractant solution proportions (1:1 or 1:4 v/v), the optimum wavelength, limits of detection, and element quantification. Our results indicate that M3 leads to lower limits of detection and quantification for both colorimetric methods, particularly for B&D. For M1, the volumetric ratio (1:1 or 1:4) did not influence color development and both B&D and M&R methods showed a fast color development. However, B&D showed greater color stability (from 5 to 600 min) and an optimum wavelength of 711 nm, while M&R was stable from 27 to 600 min an optimum wavelength of 889 nm. For M3 soil extractant, there are important issues, such as M&R being unstable and B&D presenting slow color development. In addition, the spectral profile obtained from soil extractant was different from the one obtained by the calibration curve without soil for both M&R and B&D. Therefore, the adoption of original methods on P quantification in M3 extracting solution represents a potential source of error, leading to wrong P fertilizer recommendations. Thus, the best option for P quantification in M3 extracts seems to be the use of Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES).

Characterization of Soils in Coffee Productive Areas in the Provinces of Cocle and Veraguas-Republic of Panama

The objective of the work was to characterize the properties of the soils of coffee-producing farms in the provinces of Cocle and Veraguas that allow the preparation of regionalized fertilization cards according to the edaphoclimatic characteristics of each area. Planting robusta coffee is gaining greater interest among Panamanian farmers as an alternative for soil conservation. On 16 farms in the province of Coclé and 18 in Veraguas, samples were taken (0-20 cm) to understand their properties and initiate a sustainable fertilization program that contributes to improving productivity. Digital maps were created using the Q-Gis v.3.32.1 program and regionalized fertilization cards for each zone. The soils of the province of Coclé presented a high percentage of aluminum saturation, 88% with low porosity problems, average pH of 4.9, low levels of organic matter and phosphorus (100%), and 75% low in potassium. 56% low in calcium. Imbalances were found in the Ca/Mg and Ca + Mg/K ratios, which causes nutritional problems. In Veraguas soils, 22% presented a high percentage of aluminum saturation, 67% average acid pH, 94% low organic matter and phosphorus content, 89% low in potassium, medium and high levels of magnesium and calcium. A positive and statistically significant correlation was found between % clay, organic matter, pH, and calcium. It is expected that this soil characterization and regionalized fertilization cards will contribute to improving soil properties and achieving sustainable production. Fertilization recommendation cards have been prepared for these two provinces and they take into account this entire situation and physical problems found in the soils. Much emphasis is also placed on organic fertilization of plantations as a complement to traditional fertilization, seeking more balanced nutrition.

Comparison of the Machigin and CAL Methods for Extraction of Plant Available P in Soils

ABSTRACT Fertilizer recommendations for phosphorus (P) are generally based on the soil content of plant available P and the amount of P exported by the harvested crop. In countries of the former Soviet Union (SU), a widespread method is the Machigin extraction. The relationships between soil P contents extracted with this and other European methods are not well established. Here, we compare the Machigin soil P extraction method with the Calcium Ammonium Lactate P(CAL) procedure that is commonly used in Central Europe. Both methods were tested with 94 soil samples originating from Kyrgyzstan, Ukraine, and Germany. Overall, the P amount extracted with the CAL method was 2.8 times higher than that extracted with the Machigin method. However, using results from all analyzed individual soil samples, the relation between P(CAL) and P(Machigin) showed large scatter and an R2 of only 0.364. Differing relations between P(CAL) and P(Machigin) were observed for soils with pH >7 and <7. However, these are overshadowed by differences between the three geographic groups of the soil samples. The estimated soil P fertility classes for the Machigin extraction were mostly higher than for the German (CAL) procedure, resulting in lower fertilizer recommendations for the Machigin method. To improve the accuracy of conversion between both methods, evaluation of laboratory proficiency tests (i.e. analysis of the same soil samples in different laboratories with the same methods) of the Machigin method should be useful.