Applied and Environmental Soil Science
Volume 2018 (2018), Article ID 2563293, 11 pages
https://doi.org/10.1155/2018/2563293

Research Article

Nutrient Budget and Economic Assessment of Blended Fertilizer Use in Kenya Tea Industry

Kibet Sitienei,1,2 Hellen W. Kamiri,³ Gilbert M. Nduru,¹ and David M. Kamau⁴

¹School of Natural Resources and Environmental Studies, Karatina University, P.O. Box 1957-10101, Karatina, Kenya
²KALRO, Tea Research Institute, P.O. Box 820-20200, Kericho, Kenya
³School of Agriculture and Biotechnology, Karatina University, P.O. Box 1957-10101, Karatina, Kenya
⁴Kenya Agricultural and Livestock Research Organization (KALRO), P.O. Box 57811-00200, Nairobi, Kenya

Correspondence should be addressed to Kibet Sitienei; sitnei@yahoo.com

Received 2 May 2018; Revised 1 October 2018; Accepted 22 October 2018; Published 18 November 2018

Academic Editor: Amaresh K. Nayak

Copyright © 2018 Kibet Sitienei et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Kenya’s tea industry depends predominantly on imported compound NPK fertilizers to replenish nutrients removed through plucking. These fertilizers cannot be easily manipulated for specific soils and tea clones. They also frequently become hazardous within tea-growing environments. In this respect, two fertilizer blends containing NPKS 25 : 5 : 5 : 4 + 9Ca + 2.62Mg and NPKS 23 : 5 : 5 : 4 + 10Ca + 3Mg with trace elements have been produced commercially in the country. However, the extent to which the blended fertilizers may contribute to optimal economic gains without degrading the environment has not been determined. This was the knowledge gap that this study seeks to address. The goal of this study was to evaluate the economic efficacy of fertilizer blends with the aim of identifying optimal levels of application which would maximize tea productivity with minimal negative impacts on the environment. The study hypothesized that blended fertilizers maximize productivity of tea clones with minimal environmental damage. The fertilizer blends were evaluated in two study sites, i.e., Timbilil Estate in Kericho and Kagochi farm in Nyeri. The sites were selected purposefully, one in the eastern and the other in the western tea-growing areas. The trial was laid out in randomized complete block design with two fertilizer blends and the standard NPK 26 : 5 : 5 as control. The treatments were applied at four fertilizer rates (0 (control), 75, 150, and 225 kg·N·ha⁻¹·yr⁻¹), replicated thrice. Leaf samples were collected and analyzed for nutrient uptake as well as associated yields and economic trends. The economic optimum nitrogen rate (EONR) was achieved at 75 kg·N·ha⁻¹·yr⁻¹ at Kagochi with all fertilizers, while at Timbilil, EONR was variable, between 75 and 225 kg·N·ha⁻¹·yr⁻¹ with fertilizer types. This study has shown that, based on the economic point of view, Blend “A” was the most efficient and consistent fertilizer in production and economic returns across the two sites.

1. Introduction

Tea is a major cash crop whose sustained productivity is highly desired by all stakeholders in its value chain. Nutrient requirements for commercial tea production are particularly high because the pluckable portions contain the largest percentage of nutrients in the plant [1]. Minimum concentration of nutrient required for fertilization of crops varies depending on factors such as type of crops, type of nutrients, soil conditions and composition, cropping season, and plant growth stage. However, excessive fertilization would increase soil acidity or salinity leading to plant toxicity [2], while unbalanced application has negative effects on crop physiology and yields [3]. Overapplication or excessive fertilization is also detrimental to the environment and is not economically sustainable [3]. These challenges require innovative ways of mitigation with minimal costs and environmental damage.

Chemical fertilizers with ability to replenish depleted nutrients in optimum quantities and forms have been recognized as an important component of sustainable soil fertility management [4]. Such fertilizers are available commercially in many physical and chemical forms. Each physical form has its own uses and limitations, which provide the basis for selecting the best fertilizer for specific crops or location [5]. Sources and rates of fertilizers recommended for tea production vary from region to region depending on soil types and weather conditions. In Kenya, the most popular formulation is the imported compound NPK 25 : 5 : 5 or NPK 20 : 10 : 10 based on nutrients removed in plucked leaves [6]. The government has identified a need of having locally manufactured fertilizers, which would address their shortage in the market and ensure timeliness in their applications. In response, some companies began the production of blended fertilizers whose possible negative impacts and mitigation measures had not been established. These developments and related fears constituted the basis of this study. The objectives were to assess the apparent nutrient budget of blended fertilizers application at different rates, determine economic optimum levels of blended fertilizers, and develop a soil replenishment model for the blended fertilizers. The study hypothesized that blended fertilizers maximize productivity of tea clones with minimal environmental damage.

Soil nutrients availability, their content, and degree of accessibility are very dynamic because of the various inorganic and biochemical processes in the soils [7] and biotic and abiotic factors including temperature, water content, soil reaction, and nutrient uptake, input, and losses [8]. Nitrogen (N) is the main nutrient [9] and energy input in cropping systems and the critical nutrient for tea production [10]. Response of nitrogen at any level depends on the availability of other nutrients. Although essential for achieving high crop yields, its abundant use makes fertilizer the dominant contributor to global nitrogen pollution, which poses substantial risks to climate, human health, and ecosystems [11].

Fertilizer recommendations are based on field input trials and their effects on crop yield (yield responses) in both agronomic and economic terms [12–15]. Data from the crop responses to nutrients should always be subjected to economic analysis in order to account for differences in input and output and to identify the economic optimum rates (EORs) [16]. Several methods have been developed to internalize environmental issues in economic assessments. The valuation of benefit or loss in money was in terms of the amount saved due to increased nutrient status or amount to be incurred for increasing the nutrient status, respectively [17].

2. Materials and Methods

2.1. Research Design

The trial was established using a factorial randomized completely block design (RCBD) with three fertilizer types (one is control) and four fertilizer application rates (one is control) replicated three times. The randomized complete block design (RCBD) is a standard design for agricultural experiments in which similar experimental units are grouped into blocks or replicates [18]. The defining feature of the RCBD is that each block sees each treatment exactly once.

2.2. Treatment Application

The trial was set using clone BBK 35 in Timbilil planted in 1988 at a spacing of 4 × 2.5 ft. and clone TRFK 6/8 in Kagochi planted in 1965 at a spacing of 5 × 2.5 ft. The plot size in Timbilil measured (7 × 12 M) inclusive of a net plot of 7 ∗ 10 M (70 plants), while in Kagochi, the plot size measured (8 × 8 M) with a net plot of 7 ∗ 8 M (56 plants). Variables used were three fertilizer types (one was control) and four fertilizer application rates (one was control).

(a)Fertilizer types:

(i)Blended NPKS 25 : 5 : 5 : 4 + 9Ca + 2.6Mg + trace elements (TE) as Blend A(ii)Blended NPKS 23 : 5 : 5 : 4 + 10Ca + 3Mg + trace elements (TE) as Blend B(iii)Standard NPK 26 : 5 : 5 as control

(b)Fertilizer application rates (0 (control), 75, 150, and 225 kg·N·ha⁻¹·yr⁻¹)

The fertilizer types were spread in rows as per characteristics and bush calculation based on spacing.

The areas receive the bimodal type of rainfall with peaks in April to May and October to November. Total annual precipitation in Timbilil estate is 2175 mm, while in Kangaita, annual rainfall is about 2040 mm. Temperature ranges from 12 to 20°C in Kangaita and 14 to 19°C in Timbilil.

2.3. Leaf Sampling and Analysis

Leaf samples (approximately 100 g of two leaves and a bud and mature leaf) were plucked in each plot and taken to laboratory. The samples were oven-dried at a temperature of 105°C for 72 hours before milling. Total nitrogen in the leaves was determined by the Kjeldahl method [19]. Phosphorus and potassium concentration in the leaves was determined using inductively coupled plasma emission (ICPE) spectroscopy [19].

2.4. Tea Yield Determination

Yield components of tea are described as the number of plucked shoots per unit land area and the mean weight per shoot [20]. Plucking of tea was done in conformity with the standard procedure. The fresh yield was converted to kilograms (kg) processed yield per hectare per year (kg·Mt·ha⁻¹·y⁻¹) using the following equation [21]:

where is the green leaf yield per plot, is the plant population per hectare, 0.225 is the factor converting green leaf to made tea, and is the number of plants per plot.

2.5. Data Analysis

Effect of treatments application on mean yields and leaf nutrients uptake data of mature tea clone BBK 35 in Timbilil and TRFK 6/8 in Kagochi was subjected to the analysis of variance (ANOVA) using the MSTAT C computer software package [1, 22].

2.6. NPK Dynamics and Budgeting

An estimated nutrient balance (inputs and outputs) was calculated by assuming that (i) soils existing nutritional status was minimal (ii) over the short-term, there were no nutrients recycled as plant prunings, and (iii) the amount of nutrients sequestered in the standing crop was generally small [23]. The mean for the nitrogen, phosphorus, and potassium contents of two leaves and a bud were multiplied by the yield dry matter weight to get N, P, and K removed through harvest [24]. The nutrients removed with the harvest were considered to be lost from the soil. These were then subtracted from the fertilizer applied to get approximate nutrients remnant in the soil. The nutrients residual in the soil could lead to environmental degradation. However, it is an incomplete indicator for sustainability with respect to soil fertility because it does not differentiate between nutrients in soil solution and in different types of organic matter [25]. Any fertilizer type or application rate with minimal residual effect is considered to be environmentally friendly. Although there were some shortcomings on the formula, it served as an effective tool for estimating the magnitude of nutrient loss/gain to the agroecosystems and to appraise their sustainability.

2.7. Economic Assessment

Economic appraisal of the blended fertilizers was determined using two simple approaches: productivity change approach (PCA) and replacement cost approach (RCA) [26].

For the productivity change approach, a function that stipulates a technical relationship between inputs and outputs was used. Market conditions and policy distortions affecting production decisions were taken into account [27]. They include the following:

(1)One (1) kg made tea is equivalent to 4 kg green leaves (GL)(2)Cost of plucking is average of KSh. 9 per kg GL(3)Cost of leaf collection and processing per kg made tea is KSh. 100(4)Cost of pruning and tipping is estimated at KSh. 4 per bush of a third of the farm per year(5)Cost of weeding is one man-day per two months (or six man-days in a year)(6)Average price of made tea per kg is KSh. 250(7)Cost of fertilizers is KSh. 2,150 and KSh. 2,300 per 50 kg fertilizer bag for compound and blended, respectively

The replacement cost approach (RCA) focuses on the additional input required to compensate for lost soil nutrients. Replenishment models were calculated only for the lost nutrient or the negative net nutrient balance bearing in mind that

(1)The nutrients can either be a limiting factor for growth or not(2)Available nutrients are supposed to replace, in part, nonavailable nutrients(3)Fertilizer efficiency is assumed(4)Likely side-effects of large fertilizer applications on micronutrient availability and soil acidity

3. Results and Discussion

3.1. NPK Dynamics and Budgeting

Nutrient pools measured in this study were total N, P₂O₅, and K₂O in harvested tea. Nutrient inputs were mainly from applied fertilizers. Other sources and losses were not determined in this study due to limitations of time and resources. Tables 1–3 show dynamics and apparent nutrient budgeting of NPK in tea arising from application of the Mavuno fertilizer blends versus standard NPK.

Table 1: Apparent nutrient budget of Blend A (NPKS 25 : 5 : 5 : 4 + 9Ca + 2.6Mg + trace elements) in Timbilil and Kagochi.

Site
NPK input as fertilizer (kg·ha⁻¹)
Yield (kg·Mt·ha⁻¹·yr⁻¹)
Mean NPK content in 2L + B (%)
Gross NPK removed through harvest (kg·ha⁻¹)
Nutrient budget (input as fertilizer and output as harvest) (kg·ha⁻¹)

N
P₂O₅
K₂O
N
P
K
N
P₂O₅
K₂O
N
P₂O₅
K₂O

Timbilil
0
0
0
2052
4.67
0.466
2.15
96
23
53
−96
−23
−53

75
15
15
2532
4.84
0.478
2.29
123
27
70
−48
−12
−55

150
30
30
2683
4.97
0.48
2.31
133
30
75
17
0
−45

225
45
45
2995
4.86
0.509
2.41
146
34
87
79
11
−42

Kagochi
0
0
0
1654
4.53
0.497
2.32
77
18
46
−77
−18
−46

75
15
15
1975
4.44
0.482
2.36
96
23
57
−21
−8
−42

150
30
30
1808
4.54
0.454
2.26
90
18
49
60
12
−19

225
45
45
1795
4.61
0.457
2.27
87
18
49
138
27
−4

“−” denotes a negative value.

Table 2: Apparent nutrient budget of Blend B (NPKS 23 : 5 : 5 : 4 + 10Ca + 3Mg + trace elements) in Timbilil and Kagochi.

Site
NPK input as fertilizer (kg·ha⁻¹)
Yield (kg·MT·ha⁻¹·yr⁻¹)
Mean NPK content in 2L + B (%)
Gross NPK removed through harvest (kg·ha⁻¹)
Nutrient budget (input as fertilizer and output as harvest) (kg·ha⁻¹)

N
P₂O₅
K₂O
N
P
K
N
P₂O₅
K₂O
N
P₂O₅
K₂O

Timbilil
0
0
0
2140
4.67
0.466
2.15
100
23
55
−100
−23
−55

75
15
15
2336
4.84
0.478
2.29
113
25
64
−38
−9
−48

150
30
30
2816
4.97
0.48
2.31
140
32
78
10
1
−45

225
45
45
2854
4.86
0.509
2.41
139
34
83
86
15
−34

Kagochi
0
0
0
1420
4.53
0.497
2.32
66
16
40
−66
−16
−40

75
15
15
1870
4.44
0.482
2.36
91
21
53
−16
−5
−37

150
30
30
1859
4.54
0.454
2.26
92
18
51
58
15
−18

225
45
45
1742
4.61
0.457
2.27
85
18
48
140
31
1

“−” denotes a negative value.

Table 3: Apparent nutrient budget of standard NPK in Timbilil and Kagochi.

Site
NPK input as fertilizer (kg·ha⁻¹)
Yield (kg·Mt·ha⁻¹·yr⁻¹)
Mean NPK content in 2L + B (%)
Gross NPK removed through harvest (kg·ha⁻¹)
Nutrient budget (input as fertilizer and output as harvest) (kg·ha⁻¹)

N
P₂O₅
K₂O
N
P
K
N
P₂O₅
K₂O
N
P₂O₅
K₂O

Timbilil
0
0
0
2132
4.67
0.466
2.15
100
23
55
−100
−23
−55

75
15
15
2329
4.84
0.478
2.29
113
25
64
−38
−11
−50

150
30
30
2679
4.97
0.48
2.31
133
30
75
17
−1
−46

225
45
45
3099
4.86
0.509
2.41
151
37
90
74
6
−47

Kagochi
0
0
0
1683
4.53
0.497
2.32
79
18
47
−79
−18
−47

75
15
15
1781
4.44
0.482
2.36
86
21
51
−11
−7
−37

150
30
30
1810
4.54
0.454
2.26
90
18
49
60
11
−20

225
45
45
1800
4.61
0.457
2.27
87
18
49
138
25
−6

“−” denotes a negative value.

Estimation of nutrient budgets showed that fertilizer Blend A when applied at the rate of 0 and 75 kg·N·ha⁻¹·yr⁻¹ resulted in negative nitrogen balances of 96 and 48 kg·ha⁻¹, respectively, in Timbilil. In Kagochi, N budgets for 0 rate were 77 kg·ha⁻¹ and 21 kg·ha⁻¹ for the 75 kg·N·ha⁻¹·yr⁻¹ rate. Fertilizer rates of 150 and 225 (kg·N·ha⁻¹·yr⁻¹) showed positive N balances of 17 and 79 kg·ha⁻¹, respectively, in Timbilil and 60 and 138 kg·ha⁻¹ in Kagochi as shown in Table 1. The first two N rates for P₂O₅ gave negative values while the last two resulted in positive values. K₂O in all the nitrogen rates were negative in both sites (Table 1).

Fertilizer Blend B showed negative apparent nutrient budgets in N, P₂O₅, and K₂O at rates of 0 and 75 kg·N·ha⁻¹·yr⁻¹ in both sites. However, the last N rates of 150 and 225 kg·N·ha⁻¹·yr⁻¹ resulted in negative K₂O balances of 45 and 38 kg·ha⁻¹, respectively, in Timbilil (Table 2). In Kagochi, 225 kg·N·ha⁻¹·yr⁻¹ rate resulted in positive K₂O balance of 1 (Table 2).

Apparent nutrient budgets for the standard tea fertilizer resulted in negative P₂O₅ balances of 23, 11, and 1 kg·ha⁻¹ in Timbilil when applied at rates of 0, 75, and 150 kg·N·ha⁻¹·yr⁻¹, respectively (Table 3). N for the first two N rates resulted in negative balances while the last two N rates resulted in positive balances for both sites as shown in Table 3. However, apparent nutrient budgets for K₂O were negative in both sites for all the N rates (Table 3).

From these findings, it was observed that, within the margin of error, the third rate for all the fertilizer types in Timbilil was almost in equilibrium. The same equilibrium was observed by Sitienei and Kamau [28] while working on fertilizer import versus processed tea export. The difference in potassium was negative in all the fertilizer types and rates except for the highest rate of Blend B in Kagochi. If NPK use agronomic and apparent recovery efficiencies were taken into consideration, the difference would be much higher. The negative nutrient balance is due to inadequate external inputs exacerbated by the loss of nutrients in harvested products, hence depletion and degradation of soils [29, 30]. This is the problem at lower rates of fertilizer application in tea-growing areas. The total net global flows of nitrogen (N), phosphorus (P), and potassium (K) in the form of commodities, estimated in the study of Sitienei and Kamau [28], will be 8.8 million tonnes in 2020. The nutrient balance approach allowed quantification and valuation of nutrient depletion and modelling [31].

Nitrogen is the most dynamic nutrient and after transformation, can move in the atmosphere, as well as in aquatic systems. The amounts of nitrogen (N) involved in transfers through trade are ecologically significant especially when the 2020 projections are considered. Potassium and phosphorus transfers are also significant and may provide opportunities for the eventual recycling of the important nutrients, especially given the high cost of potassium mining and transportation [32, 33]. It is therefore important for each country to consider the effects of nutrient flows in food trade on its own ecosystem.

3.2. Economics of Blended Fertilizers

The valuation of benefit or loss in money was in terms of the amount saved due to increased nutrient status or amount to be incurred for increasing the nutrient status, respectively [17].

3.3. Productivity Change Approach (PCA)

The method involves a two-step procedure. Firstly, the physical effects of changes in the environment on productive activity are determined, i.e., the value of productivity change is equal to the difference in crop yields with and without that nutrient change. The second step consists of valuing the resulting changes in production, usually using market prices. In this case, the PCA takes the reduction in the capitalized net annual income stream gained through agricultural production (i.e., loss of income through crop yields) as a substitute for the costs of nutrient depletion.

3.4. Gross Profit Analysis

The profitability of the three fertilizers under study was analyzed in Tables 4–6 by obtaining the gross profit ha⁻¹·yr⁻¹ for a particular rate. In order to determine the highest profit ratio or economic optimum ratio to use, the output was multiplied by the market price (long-term average annual price) of processed tea in Kenya minus the cost of input. The nutrient value is equal to the change in revenue or profit caused by nutrient change (changes in nutrient contents as a proxy for the value of the nutrients) [34].

Table 4: Economic evaluation of fertilizer Blend A application in Timbilil and Kagochi.

Site
N rates in kg·ha⁻¹
Bags of NPK(S) ha⁻¹ required
Total cost of fertilizer at KSh. 2,300/bag of 50 kg
kg·Mt·ha⁻¹·yr⁻¹ (TPP)
Production in kg of GL·ha⁻¹·yr⁻¹
Cost of plucking (KSh)
Cost of pruning (KSh)
Cost of weeding (KSh)
Cost of collection and processing (KSh)
Gross earnings from made tea ha⁻¹·yr⁻¹ (KSh)
Total cost of production (KSh)
Gross profit ha⁻¹·yr⁻¹ (KSh)
Average physical product (APP)
Marginal physical product (MPP)

Timbilil
0
0
0
2052
8,208
73,872
14355
4125
205,200
513,000
297,552
215,448
0
0

75
6
13,800
2532
10,128
91,152
14355
4125
253,200
633,000
376,632
256,368
422
80

150
12
27,600
2683
10,732
96,588
14355
4125
268,300
670,750
410,968
259,782
224
25

225
18
41,400
2995
11,980
107,820
14355
4125
299,500
748,750
467,200
281,550
166
52

Kagochi
0
0
0
1654
6,616
59,544
14355
4125
165,400
413,500
243,424
170,076
0
0

75
6
13,800
1975
7,900
71,100
14355
4125
197,500
493,750
300,880
192,870
329
54

150
12
27,600
1808
7,232
65,088
14355
4125
180,800
452,000
291,968
160,032
151
−28

225
18
41,400
1795
7,180
64,620
14355
4125
179,500
448,750
304,000
144,750
100
−2

TPP: total physical product, GL: green leaf, MPP: marginal physical product, and APP: average physical product.

Table 5: Economic evaluation of fertilizer Blend B application Timbilil and Kagochi sites.

Site
N rates in kg·ha⁻¹
Bags of NPK(S) ha⁻¹ required
Total cost of fertilizer at KSh 2,300/bag of 50 kg
kg·Mt·ha⁻¹·yr⁻¹ (TPP)
Production in kg of GL·ha⁻¹·yr⁻¹
Cost of plucking (KSh)
Cost of pruning (KSh)
Cost of weeding (KSh)
Cost of collection and processing (KSh)
Gross earnings from made tea ha⁻¹·yr⁻¹ (KSh)
Total cost of production (KSh)
Gross profit ha⁻¹·yr⁻¹ (KSh)
Average physical product (APP)
Marginal physical product (MPP)

Timbilil
0
0
0
2140
8,560
77,040
14355
4125
214,000
535,000
309,520
225,480
0
0

75
6
13,800
2336
9,344
84,096
14355
4125
233,600
584,000
349,976
234,024
389
33

150
12
27,600
2816
11,264
101,376
14355
4125
281,600
704,000
429,056
274,944
235
80

225
18
41,400
2854
11,416
102,744
14355
4125
285,400
713,500
448,024
265,476
159
6

Kagochi
0
0
0
1420
5,680
51,120
14355
4125
142,000
355,000
211,600
143,400
0
0

75
6
13,800
1870
7,480
67,320
14355
4125
187,000
467,500
286,600
180,900
312
75

150
12
27,600
1859
7,436
66,924
14355
4125
185,900
464,750
298,904
165,846
155
−2

225
18
41,400
1742
6,968
62,712
14355
4125
174,200
435,500
296,792
138,708
97
−20

“−” denotes a negative value.

Table 6: Economic evaluation of standard NPK applied to tea in Timbilil and Kagochi.

Site
N rates in kg·ha⁻¹
Bags of NPK(S) ha⁻¹ required
Total cost of fertilizer at KSh 2,300/bag of 50 kg
kg·Mt·ha⁻¹·yr⁻¹ (TPP)
Production in kg of GL·ha⁻¹·yr⁻¹
Cost of plucking (KSh)
Cost of pruning (KSh)
Cost of weeding (KSh)
Cost of collection and processing (KSh)
Gross earnings from made tea ha⁻¹·yr⁻¹ (KSh)
Total cost of production (KSh)
Gross profit ha⁻¹·yr⁻¹ (KSh)
Average physical product (APP)
Marginal physical product (MPP)

Timbilil
0
0
0
2132
8,528
76,752
14355
4125
213,200
533,000
308,432
224,568
0
0

75
5.8
12,470
2329
9,316
83,844
14355
4125
232,900
582,250
347,694
234,556
402
34

150
11.5
24,725
2679
10,716
96,444
14355
4125
267,900
669,750
407,549
262,201
233
61

225
17.3
37,195
3099
12,396
111,564
14355
4125
309,900
774,750
477,139
297,611
179
72

Kagochi
0
0
0
1683
6,732
60,588
14355
4125
168,300
420,750
247,368
173,382
0
0

75
5.8
12,470
1781
7,124
64,116
14355
4125
178,100
445,250
273,166
172,084
307
17

150
11.5
24,725
1810
7,240
65,160
14355
4125
181,000
452,500
289,365
163,135
157
5

225
17.3
37,195
1800
7,200
64,800
14355
4125
180,000
450,000
300,475
149,525
104
−2

“−” denotes a negative value.

Profitable rates fluctuated among the rates of the three fertilizers in the two sites. In Timbilil, profitable rates were 225 kg·N·ha⁻¹ for Blend A at KSh. 281,550 per hectare per year (Table 4) and standard NPK (KSh. 297,611 per hectare per year) (Table 6) while fertilizer Blend B was more profitable when applied at 150 kg·N·ha⁻¹ (Ksh. 274.944 per hectare per year) (Table 5). The reduction in gross profit for Blend A and standard NPK with the lower rates of fertilizer application was compensation for nutrients depletion. This is because tea is rarely adapted to growing under low nutrient conditions and fails to yield economically without the addition of fertilizers. However, the same rate for Blend B might have been excessive leading to negative effect. The application of high rates of N, P, and K allows for increased production. However, N and P application in excess of crop demands can lead to profound environmental consequences [35].

In Kagochi, the fertilizer rate of 75 kg·N·ha⁻¹ was the most profitable for all the three fertilizers (192,870, 180,900, 172,084 KSh.·ha⁻¹·yr⁻¹ for Blend A, Blend B, and NPK standard (Tables 4–6), respectively). The reduction in gross profit with fertilizer rates higher than 75 kg·N·ha⁻¹ means that the higher rate might have brought negative effects on various nutrients in the soil. This study attempted to quantify the economic value of soil productivity conservation and its economic cost by productivity losses.

These findings are consistent with those by Njogu et al. [16] that different clones have different nutritional needs and differ in their abilities to absorb nutrients even when the agronomic practices are similar, which is depicted in their yield response to varying fertilizer application rates and the fertilizer types applied. Different clones with different yield potentials require different fertilizer rates. For a high yielding clone like AHP S15/10, the most profitable production has been achieved by applying 200 kg·N·ha⁻¹·yr⁻¹ in Kericho [6].

3.5. Economic Optimum Nitrogen Application Rate

In the economic analysis studies, the economic optimum rate and the most profitable rate for each fertilizer in each site were determined. The economic optimum nitrogen rate (EONR) is realized when the cost of the last increment of additional N equals the value of tea yield increase. Tables 4–6 show the economic analysis of the different fertilizers in the two sites. From the data tabulation, the following were deduced:

(1)For Blend A, the EONR was achieved at 6 bags of fertilizer per hectare per year at both Timbilil and Kagochi(2)For Blend B, the EONR was achieved at 13 and 6.5 bags of fertilizer per hectare per year in Timbilil and Kagochi, respectively(3)For the standard NPK, the EONR was achieved at 19.6 and 5.8 bags of fertilizer per hectare per year in Timbilil and Kagochi, respectively(4)Kagochi had the least fertilizer requirement across all the fertilizer types

The magnitude of the increase in yield tended to diminish as the total level of nitrogen rate increased. As successive units of fertilizer were added to other costs, it reached a point where the value of the marginal product was less than the unit cost of N used to produce it. The economic implication of this trend is that the value of the additional crop at first exceeded the cost of applying fertilizer but eventually only marginal additional crop was obtained for each unit of additional fertilizer resulting in no achievement of monetary gain. A fertilizer type may do well agronomically but poorly in economic terms as a result of low commodity prices or high production costs.

With higher N prices, it becomes more important to fertilize at the most economic rate, which may differ from the agronomic rate. Kiprono et al. [36] found that the EONR changes as market costs and returns change.

The most economic fertilizer rate for fertilizer Blend A was 75 kg·N·ha⁻¹·yr⁻¹ for both sites. However, economic rates were different for Blend B and standard NPK in Timbilil and Kagochi. This shows that fertilizer recommendations vary widely for different tea-growing regions depending on the age of the bushes, pruning cycle, yield, and soil fertility as was found by Tshivhandekano et al. [10] and Namu et al. [37]. Several studies have revealed that lack of plant nutrients is one of the principal causes for low agricultural productivity in Africa [12, 15].

The findings here are in agreement with earlier findings that farming should be economically sustainable so that it can contribute to the economic security of key factors in the farm and in the food system as a whole [38]. Economic sustainability can be achieved through increased efficiencies in the use of farm inputs to lower the cost of production for farmers and thus providing savings which can be used to improve on other aspects of livelihood [38]. Such savings available for expenditure on other aspects of life beside food would create new industries in the community and new employment opportunities and hence better living standards for the society.

3.6. Replacement Cost Approach (RCA)

Figures 1 and 2 show soil replenishment models for mean of the three fertilizer types in Timbilil and Kagochi, respectively. The dependent variable represents the amount of input required to return the soil to optimum conditions. As an independent variable, the fertilizer rate indicated that the more the rate, the more the replenishment required later. Other variables were assumed to have no discernible effects in these models.

Figure 1: Soil nutrient replenishment model for Timbilil.

Figure 2: Soil nutrient replenishment model for Kagochi.

According to the results, it was confirmed that the replenishment model for Timbilil was linear while that of Kagochi was polynomial. In Timbilil, the mean soil replenishment model for the different fertilizer types was given by the following equation:

This shows that the amount of NPK fertilizer required to restock the soil was higher than applied N and it increased linearly with the N rates.

In Kagochi, the mean replenishment model was given by the following equation:

The model showed that the amount of input required increased initially up to 75 kg·N·ha⁻¹·yr⁻¹ then decreased with the N rates.

The models showed that replenishment is vital if tea productivity is to be sustained. The nutrient balance model proved to be a useful indicator of nutrient depletion and offers a biophysical base for its economic assessment via the replacement cost approach (RCA). Nutrients export from land with no capacity to replenish those nutrients represents long-term stripping of soil stocks, exposing developing countries to significant long-term risk of soil productive failure [35]. From the tea industry, models have been used to bring better understanding on how productivity and resource use of tea agroecosystem is influenced by associated agronomic factors [39, 40], hence exploring the most promising interventions for tea productivity improvement. Different authors have elaborated on nutrient balance calculations into decision support models that allow monitoring of the effects of changing land use and suggestions of interventions to improve the nutrient balance [31].

Researchers have shown that nutrient losses due to uptake by crops, erosion, leaching, and N volatilization are only partially compensated by crop residues left on the field, manure and fertilizer application, and atmospheric inputs; thus, the annual NPK balances for sub-Saharan Africa are negative with minus 22–26 kg·N, 6-7 kg P₂O₅, and 18–23 kg·K₂O·ha⁻¹ [41]. For the whole of SSA, nutrient mining accounts for about 7% of the subcontinental agricultural gross domestic product (AGDP). This amount (US$4 billion year⁻¹) exceeds the annual external assistance to the development of African agriculture in the past decade by about 30–50%, which gives an indication of the financial dimension [42].

The models like the NUTMON approach have been developed completely at the farm level. This means that they can also serve as tools for monitoring nutrient flows on farms [43]. To estimate it on a global level, a set of methodologies is usually employed as summarized by Van Ittersum et al. [44]. They are broadly categorized into statistical and crop-modelling approaches. Statistical approaches rely on yield census data of varying size, which are then combined with global data (e.g., climate, fertilizer inputs, and irrigation area). Based on climate binning techniques [45], they divide the world into contingent areas of similar growth environment, looking at main drivers of yield variation within.

As hypothesized, blended fertilizers were found to be capable of increasing productivity while conserving the environment. The positive findings lead to sustainable farming where productivity is raised with minimum negative impacts on the environment and also help in recovering already degraded soil [38].

4. Conclusion

The ultimate aim of this study was to optimize tea production, maximize positive interactions, maximize net returns, minimize the depletion of soil nutrients, and minimize nutrient losses or negative impact on the environment.

(1)As hypothesized, blended fertilizers were found to be capable of increasing productivity while conserving the environment. The positive findings could lead to sustainable farming where productivity is raised with minimum negative impacts on the environment and also help in recovering already degraded soil.(2)From an economic point of view, Blend A was the most efficient and consistent fertilizer in production, economic returns, and its environmental effects across the two sites.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

The authors are very grateful to Athi River Mining Ltd., KALRO Tea Research Institute, and KTDA for funding the research and Karatina University for providing technical support during the process of data collection.

References

K. Sitienei, P. G. Home, D. M. Kamau, and J. K. Wanyoko, “Nitrogen and potassium dynamics in tea cultivation as influenced by fertilizer type and application rates,” American Journal of Plant Sciences, vol. 4, no. 1, pp. 59–65, 2013.

S. Phuntsho, H. K. Shon, T. Majeed et al., “Blended fertilizers as draw solutions for fertilizer-drawn forward osmosis desalination,” Environmental Science and Technology, vol. 46, no. 8, pp. 4567–4575, 2012.

C. Pacheco, F. Calouro, S. Vieira et al., “Influence of nitrogen and potassium on yield, fruit quality and mineral composition of kiwifruit,” Energy and Environment, vol. 2, pp. 517–521, 2008.

D. S. Ogundijo, M. T. Adetunji, J. O. Azeez, T. A. Arowolo, N. O. Olla, and A. F. Adekunle, “Influence of organic and inorganic fertilizers on soil chemical properties and nutrient changes in an Alfisol of South Western Nigeria,” International Journal of Plant & Soil Science, vol. 7, no. 6, pp. 329–337, 2015.

S. L. Tisdale, W. L. Nelson, and J. D. Beaton, Soil Fertility and Fertilizers, Macmillan Publishing Company, NY, USA, 4th edition, 1985.

P. O. Owuor, C. O. Othieno, D. M. Kamau, and J. K. Wanyoko, “Effects of long-term fertilizer use on a high-yielding tea clone AHPS15/10: soil pH, mature leaf nitrogen, mature leaf and soil phosphorus and potassium,” International Journal of Tea Science, vol. 8, no. 1, pp. 15–51, 2011.

R. N. Roy, A. Finck, G. J. Blair, and H. L. S. Tandon, Plant Nutrition for food security. A guide for Integrated Nutrient Management, vol. 16 of FAO Fertilizer and Plant Nutrition Bulletin, Food and Agriculture Organization of the United Nations, Rome, Italy, 2006.

S. S. Virk, D. K. Mullenix, A. Sharda et al., “Case study: distribution uniformity of a blended fertilizer applied using a variable-rate spinner-disc spreader,” Applied Engineering in Agriculture, vol. 29, no. 5, pp. 627–636, 2013.

M. H. Ibrahim and H. Z. Jaafar, “Enhancement of leaf gas exchange and primary metabolites under carbon dioxide enrichment up-regulates the production of secondary metabolites in Labisia pumila seedlings,” Molecules, vol. 16, no. 5, pp. 3761–3777, 2011.

I. Tshivhandekano, F. N. Mudau, P. Soundy, and W. Ngezimana, “Effect of cultural practices and environmental conditions on yield and quality of herbal plants: prospects leading to research on influence of nitrogen fertilization, planting density and eco-physiological parameters on yield and quality of field-grown bush tea (Athrixia phylicoides DC.),” Journal of Medicinal Plants Research, vol. 7, no. 34, pp. 2489–2493, 2013.

J. W. Erisman, J. N. Galloway, S. Seitzinger et al., “Consequences of human modification of the global nitrogen cycle,” Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 368, no. 1621, Article ID 20130116, 2013.

X. Dai, Z. Ouyang, Y. Li, and H. Wang, “Variation in yield gap induced by nitrogen, phosphorus and potassium fertilizer in North China plain,” PLoS One, vol. 8, no. 12, Article ID e82147, 2013.

E. Duflo, M. Kremer, and J. Robinson, “How high are rates of return to fertilizer? Evidence from field experiments in Kenya,” American Economic Review, vol. 98, no. 2, pp. 482–488, 2008.

S. Takahashi and M. R. Anwar, “Wheat grain yield, phosphorus uptake and soil phosphorus fraction after 23 years of annual fertilizer application to an andosol,” Field Crops Research, vol. 101, no. 2, pp. 160–171, 2007.

C. Tonitto and J. E. Ricker-Gilbert, “Nutrient management in African sorghum cropping systems: applying meta-analysis to assess yield and profitability,” Agronomy for Sustainable Development, vol. 36, no. 1, pp. 1–19, 2016.

R. N. E. Njogu, D. K. Kariuki, D. M. Kamau, and F. N. Wachira, “Economic evaluation of foliar NPK fertilizer on tea yields in Kenya,” Journal of Plant Studies, vol. 4, no. 1, p. 35, 2015.

S. Rastgar, H. Barani, A. Darijani, V. Sheikh, J. Ghorbani, and M. Ghorbani, “Economic cost of soil nutrients loss from summer rangelands of nour-rud watershed in north of Iran,” Ecopersia, vol. 3, no. 2, pp. 945–958, 2015.

A. G. Clewer and D. H. Scarisbrick, Practical Statistics and Experimental Design for Plant and Crop Science, John Wiley & Sons, Hoboken, NJ, USA, 2013.

TRFK, Soil, Plant Tissue and Fertilizer Sampling and Analytical Methods Manual, TRFK, Kericho, Kenya, 2012.

W. A. De Costa, A. J. Mohotti, and M. A. Wijeratne, “Ecophysiology of tea,” Brazilian Journal of Plant Physiology, vol. 19, no. 4, pp. 299–332, 2007.

TRFK, Tea Growers Hand Book, Tea Research Foundation of Kenya, Elizer Services Publishers, Times Printing Services, Nairobi, Kenya, 5th edition, 2002.

F. Russel, MSTATC Computer Based Statistical Software Package, Michigan State University, East Lansing, MI, USA, 1995.

C. L. Van Beek, E. Elias, G. S. Yihenew et al., “Soil nutrient balances under diverse agro-ecological settings in Ethiopia,” Nutrient Cycling in Agroecosystems, vol. 106, no. 3, pp. 257–274, 2016.

M. Bekunda and G. Manzi, “Use of the partial nutrient budget as an indicator of nutrient depletion in the highlands of southwestern Uganda,” Nutrient Cycling in Agroecosystems, vol. 67, no. 2, pp. 187–195, 2003.

H. Van den Bosch, A. De Jager, and J. Vlaming, “Monitoring nutrient flows and economic performance in African farming systems (NUTMON): II. Tool development,” Agriculture, Ecosystems and Environment, vol. 71, no. 1–3, pp. 49–62, 1998.

P. Drechsel and L. A. Gyiele, The Economic Assessment of Soil Nutrient Depletion: Analytical Issues for Framework Development, International Board for Soil Research and Management, Bangkok, Thailand, 1999.

F. Nunan, K. Bird, and J. Bishop, Valuing Natural Resources: A Guide for Natural Resource Managers, International Development Department, School of Public Policy, University of Birmingham, Birmingham, UK, 1999.

K. Sitienei and D. M. Kamau, “Towards sustainable agriculture: the case of tea nutrient budgeting in the smallholder sub-sector in Kenya,” Journal of Tea Science Research, vol. 5, 2015.

G. K. MacDonald, E. M. Bennett, P. A. Potter, and N. Ramankutty, “Agronomic phosphorus imbalances across the world’s croplands,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 7, pp. 3086–3091, 2011.

N. D. Mueller, J. S. Gerber, M. Johnston, D. K. Ray, N. Ramankutty, and J. A. Foley, “Closing yield gaps through nutrient and water management,” Nature, vol. 490, no. 7419, pp. 254–257, 2012.

D. Chen, H. Shen, M. Hu, J. Wang, Y. Zhang, and R. A. Dahlgren, “Legacy nutrient dynamics at the watershed scale: principles, modeling, and implications,” in Advances in Agronomy, vol. 149, pp. 237–313, Academic Press, Cambridge, MA, USA, 2018.

E. H. Oelkers and E. Valsami-Jones, “Phosphate mineral reactivity and global sustainability,” Elements, vol. 4, no. 2, pp. 83–87, 2008.

D. O. Yawson, P. K. Kwakye, F. A. Armah, and K. A. Frimpong, “The dynamics of potassium (K) in representative soil series of Ghana,” ARPN Journal of Agricultural and Biological Science, vol. 6, no. 1, pp. 48–55, 2011.

P. Drechsel, M. Giordano, and L. Gyiele, Valuing Nutrients in Soil and Water: Concepts and Techniques with Examples from IWMI Studies in the Developing World, vol. 82, IWMI, Colombo, Sri Lanka, 2004.

D. L. Jones, P. Cross, P. J. Withers et al., “Nutrient stripping: the global disparity between food security and soil nutrient stocks,” Journal of Applied Ecology, vol. 50, no. 4, pp. 851–862, 2013.

K. P. Kiprono, J. K. Wanyoko, D. M. Kamau, and W. Chepng’eno, “Economics of nitrogen fertilizer use in tea,” Tea, vol. 31, no. 2, pp. 36–43, 2010.

N. N. Namu, G. K. Kaimba, D. K. Muriithi, and I. M. Nkari, “Impact of cost reduction strategies on performance of tea factories in Embu county, Kenya,” European Journal of Business and Social Sciences, vol. 3, no. 9, pp. 26–48, 2014.

FAO, Save and Grow: A Policymaker’s Guide to the Sustainable Intensification of Smallholder Crop Production, FAO, Rome, Italy, 2011.

J. E. Drinnan, Fertilizer Strategies for Mechanical Tea Production, Rural Industries Research and Development Corporation, Wagga Wagga, NSW, Australia, 2008.

D. M. Kamau, Productivity and Resource Use in Ageing Tea Plantations, Wageningen Universiteit, Wageningen, Netherlands, 2008.

S. T. Tadesse, O. Oenema, C. van Beek, and F. L. Ocho, “Diversity and nutrient balances of urban and peri-urban farms in Ethiopia,” Nutrient Cycling in Agroecosystems, vol. 111, no. 1, pp. 1–18, 2018.

D. J. Sobota, J. E. Compton, M. L. McCrackin, and S. Singh, “Cost of reactive nitrogen release from human activities to the environment in the United States,” Environmental Research Letters, vol. 10, no. 2, Article ID 025006, 2015.

M. Kvakić, S. Pellerin, P. Ciais et al., “Quantifying the limitation to world cereal production due to soil phosphorus status,” Global Biogeochemical Cycles, vol. 32, no. 1, pp. 143–157, 2018.

M. K. Van Ittersum, K. G. Cassman, P. Grassini, J. Wolf, P. Tittonell, and Z. Hochman, “Yield gap analysis with local to global relevance—a review,” Field Crops Research, vol. 143, pp. 4–17, 2013.

J. Van Wart, L. G. J. van Bussel, J. Wolf et al., “Use of agro-climatic zones to upscale simulated crop yield potential,” Field Crops Research, vol. 143, pp. 44–55, 2013.