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Efficiency of rice farming in flood-prone areas of East Java, Indonesia

  • Suci Warda Ramadani , Ernoiz Antriyandarti EMAIL logo and Raden Rara Aulia Qonita
Published/Copyright: April 20, 2024
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Open Agriculture
From the journal Open Agriculture Volume 9 Issue 1

Abstract

Improving rice production by increasing the efficiency of rice farming becomes the alternative strategy in Java Island, where half of the Indonesian populations live. Even though some areas are flood-prone, East Java Province is one of the leading rice producers in Indonesia. This study aims to estimate the level of technical efficiency in rice farming in flood-prone areas in East Java and some socio-economic factors that influence the efficiency. The efficiency of rice farming in this study was analyzed using a stochastic frontier production function approach. The results showed that rice farming in flood-prone areas in East Java has been efficient, with an average efficiency of 76.05%. The estimated parameters of farm size, labor, seed, urea fertilizer, and ZA fertilizer are positively significant to rice production, while tractor use is negatively significant to rice production. In addition, farm size, age of household head (HH), education of HH, land ownership, and off-farm jobs positively influence the efficiency of rice farming.

Keywords: rice farming; flood-prone; the efficiency of rice production

1 Introduction

Paddy is still regarded as the most critical and strategic commodity for the Indonesian economy, and based on the data from the Central Bureau of Statistics [1], East Java Province has the highest production in Indonesia, amounting to 10.54 million tons of dry-mill paddy in 2017. Lamongan District is the district that dominates and has the most immense contribution to the total rice production in East Java despite being a flood-prone area. Lamongan District has the highest production and harvest area in East Java, with 924,212 tons of the total output of paddy and 151,884 ha of harvested area.

The area of rice fields in Lamongan District was 87990.3 ha from the total available land of 167001.2 ha [2], while the rice farming system was pond rice fields. The land has the characteristics of being quite wet and was alternately used as rice fields or ponds. The rice planting system was monoculture with a shrimp (February-April), rice (June–September), and shrimp (November–January) planting pattern. The rice varieties that farmers in Lamongan District widely use are Inpari 32, Ciherang, and IR-64. In the meantime, the Lamongan farm households were dominated by men aged 50 as its head. The agricultural sector was still the primary source of income for farm households [3].

Rice farming is considered one of the riskiest businesses; this results from the impact of the combination of environmental conditions, unpredictable economic shocks, and, consequently, the financial situation of farm households. Therefore, in many areas, it is impossible to perform large-scale production [4]. The problem most often encountered by farmers in rice farming activities is related to using production inputs. Farmers cannot buy the production inputs because of the lack of capital accumulation owned by farmers [5].

Rice farming is how farmers manage their production factors effectively, efficiently, and sustainably to obtain high production and increase their income [6]. Regarding development, the most essential thing about farming is that rice farming should constantly change in size and structure to take advantage of the evolving farming period more efficiently.

The factors of production, such as land, labor, capital, and management, generally determine rice farming. The technical relationship between inputs and outputs can be expressed in a production function. A production function will explain the technical relationships that transform inputs or resources into outputs or commodities. The Cobb–Douglas production function is among the standard production functions discussed and used by most researchers [7]. The Cobb–Douglas production function is an equation that involves two or more variables, where one variable is called the dependent variable, which is described (Y), and the other is called the independent variable, which explains (X). The Cobb–Douglas production function is often used as a model for the analysis of farm production because it is simpler to use and more accessible to see the relationship between inputs and outputs [8].

Besides the production function, this study uses a stochastic frontier production function approach. This function mainly assessed the farm’s technical efficiency [9]. Coelli et al. [10] explain that efficiency comprises technical and allocative components. Technical efficiency shows the ability of farming to obtain maximum output from a certain number of inputs. At the same time, allocative efficiency allows a farm to use optimal input proportions according to price and production technology. Merging the two would be an economic efficiency. However, this study focused on the technical efficiency of rice farming in Lamongan District.

2 Materials and methods

The primary method used in this research is descriptive and analytics to give a general overview of the phenomenon, explain the relationship between variables, make predictions, examine historical data, and assess the importance and implications of the problem being solved [11]. The location was conducted purposive, which is the area chosen based on specific considerations following the aim of the study [12]. The consideration in determining this location is that East Java Province was one of the rice production centers in Indonesia and had the highest amount of rice production; meanwhile, the district/city with the highest harvested area and total production in East Java was Lamongan District. This study used 83 observations taken using a random sampling method, where all the individuals in the population, either individually or together, have the same chance to be selected as the sample members [13]. The characteristics of the respondents sought were farmers who cultivated rice in Lamongan District in 2017–2018. Data were obtained through observation and interviews using a questionnaire [14].

2.1 Rice production efficiency in flood-prone areas of Lamongan district

Rice production technical efficiency in Lamongan District is analyzed using a stochastic frontier production function following the model of the production function estimator by Coelli et al. [10] and Aigner et al. [15]. This analysis aims to determine farmers’ production and the efficiency of production factors that significantly affect the production frontier. The hypothesis formed is that crop production was influenced by land area [16,17], labor [16,18,19,20], seed [16,18,19,20], fertilizer [16,18,19,20], and tractor [20,21,22]. Thus, the model estimators of the stochastic frontier production function can be formulated as follows:

(1) ln Y = α 0 + α 1 ln X 1 + α 2 ln X 2 + α 3 ln X 3 + α 4 ln X 4 + α 5 ln X 5 + α 6 ln X 6 + ( v i − u i ) ,

where Y is the production of rice (kg), X 1 is the farm size (m2), X 2 is the number of labor used (PWD), X 3 is the number of rice seeds used (kg), X 4 is the number of urea fertilizer used (kg), X 5 is the number of ZA fertilizer used (kg), X 6 is the use of tractors (TWD), and (v i – u i ) is the error term. All variables were observed for one planting season using a questionnaire.

Stochastic frontier analysis from previous research is directed mainly at predicting the effects of inefficiency. Based on Coelli et al. [10], the output-oriented technical efficiency size is the most common output ratio observed with stochastic frontier output

(2) TE i = q i exp ( x i β + v i ) = exp ( x i β + v i − u i ) exp ( x i β + v i ) = exp ( − u i ) .

The analytical tool used to calculate the value of production efficiency with a stochastic frontier approach is Stata version 12 software. The value of the efficiency (TE i ) situated in the interval of 0 to 1 or 0 < TE < 1. The efficiency value, which is getting close to 1, is considered more efficient, and if TE i = 1, then the farming condition is technically efficient.

2.2 Factors that affect the efficiency of rice farming in flood-prone areas of Lamongan district

Factors that affect the efficiency of rice farming can be determined by identifying the sources that have caused the production efficiency of agriculture. Identification of the sources that generated the efficiency was analyzed with the estimation model similar to the previous research; the variables used were farm size [17,23,24], household head (HH)’s age [16,17,24,25], the length of the HH’s formal education [16,24,25,26], land tenure [16,24], and off-farm jobs [23,24,26]. The model was then adjusted to the needs of this study and expressed in a regression equation as follows:

(3) TE i = δ 0 + δ 1 Z 1 + δ 2 Z 2 + δ 3 Z 3 + δ 4 Z 4 + δ 5 D 1 + δ 6 D 2 + ε ,

where TE i is the technical efficiency value, Z 1 is the farm size (m2), Z 2 is the HH’s age (years), Z 3 is the length of the HH’s formal education (years), Z 4 is the distance between land and farmer’s house (m), D 1 is a dummy variable of land tenure (if owned land = 1; others = 0), D 2 is a dummy variable of off-farm jobs (engage in off-farm jobs = 1), and ε is an error term.

3 Results and discussion

3.1 Characteristics of rice farmers in the Lamongan district

It is crucial to provide background information about the sample respondents and model variables before moving on to the econometrics results. Descriptive statistics of the variables employed in this investigation are therefore shown in Table 1. According to Table 1, farmers in Lamongan District produced rice with an average of 2409.036 kg/planting season. Meanwhile, the average size of farmland in the research area was 4367.891 m2, so they can still increase the total output by increasing the land size. Labor includes family and outside labor, calculated in Person Working Days (PWD). The average labor used was 13.332 PWD. Farmers used rice seeds, urea (carbamide) fertilizer, and ZA (ammonium sulfate) fertilizer on an average of 13.602, 75.904, and 24.096 kg. The time a farmer uses a tractor in one planting season was measured in Tractor Working Days (TWD); the average tractor use in the research area was 0.384 TWD.

Table 1

Characteristics of rice farmers in Lamongan district

No. Variables Unit Min Max Mean Amount (%)
1. Production (Y) kg 250 9,000 2409.036
2. Farm size (X 1/Z 1) M2 500 14,250 4367.891
3. Labor (X 2) PWD 4 89.25 13.332
4. Seed (X 3) kg 5 50 13.602
5. Urea fertilizer (X 4) kg 10 250 75.904
6. ZA fertilizer (X 5) kg 0 100 24.096
7. Use of tractor (X 6) TWD 0 1.5 0.384
8. Age of HH (Z 2) Year 35 81 55.361
9. Formal education of HH (Z 3) Year 6 16 9.903
10. Land distance from house (Z 4) M 100 5,000 976.506
11 Land tenure (D 1) Plot 14 (16.867%)
69 (83.133%)

  1. Rented land

  1. Owned land
12. Off-farm jobs (D 2) Person s60 (72.289%)
23 (27.711%)

  1. Engaged

  1. Did not engage

Source: Primary data analysis, 2019.

The average age of HH was 55.361 years or classified as productive age [27], while their intermediate formal education was 9.903 years (senior high school). The average distance between the farmland and the farmer’s house was 976.506 m. Research shows that most farmers (69 people or 83.133%) owned rice fields, while only 14 farmers (16.867%) rented land (did not have their land). Sixty farmers (72.289%) worked outside the agriculture sector, while the remaining farmers (27.711%) were uninvolved.

3.2 Rice production efficiency analysis in flood-prone area of Lamongan district

Production function analysis describes the relationship between production and inputs, estimated using stochastic frontier production function models in this study. A production function analysis was conducted to examine the factors affecting rice production in the research area. The production function analysis was estimated by six variables: land area, number of labor, the number of rice seeds, the amount of urea fertilizer, the amount of ZA fertilizer, and the use of tractors. Results of the estimation prediction of the production function of rice farming in Lamongan District are presented in Table 2.

Table 2

Estimation result of stochastic frontier production function

No. Variables Coefficient SE p > |z|
1. Cons (α 0) −53.109*** 5692.857 0.993
2. Farm size (X 1) 0.298*** 0.079 0.000
3. Labor (X 2) 40.014*** 9.352 0.000
4. Seed (X 3) 52.184*** 16.956 0.002
5. Urea fertilizer (X 4) 9.465** 3.809 0.013
6. ZA fertilizer (X 5) 9.961*** 2.987 0.001
7. Tractors use (X 6) −2738.962*** 470.052 0.000
Number of observations 83
sigma_v 758.2059 Log likelihood −668.14116
sigma_u 0.0753994 Wald chi-squared (6) 315.32
sigma-squared 574876.2 Prob > chi-squared 0.0000

Source: Primary data analysis, 2019.

***Significant at 1% level; **Significant at 5% level.

The estimated parameters in the production function show the elasticity of the production frontier of inputs used. Based on the level of significance of variables expected to affect the production of rice farming, it can be seen that the variable farm size, number of labor, number of rice seeds, and the amount of urea and ZA fertilizer significantly has a natural effect on increased production of rice farming with the elasticity is positive. Variables in using tractors also significantly affect rice farming production but negatively affect total production.

The majority of farmers (69 people or 83.13%) in Lamongan District produced rice on a land with a size of ≤5,000 m2, while the remaining 14 farmers (16.87%) cultivated rice on a land of >5,000 m2. Land size or farm size (X 1) significantly affects rice farming production and positively affects the amount of rice production. The farm size has a coefficient value of 0.298, which means that for every increase of 1% of the farm size, the amount of rice production will increase by 0.298%. This result follows the results of Jamalludin [28], which states that land size is one of the variables significantly influencing farm production. The large land size means a plant population growth so that rice production can increase with increasing number of plants. The larger the rice farming land cultivated, the higher the rice production. The finding also aligns with a study in eastern China, which showed that official land certificates for farmers might enhance both tenure security and technical efficiency in grain production. Because annual and open-ended contracts have been found to impair technical efficiency, the length of a land leasing contract is also essential [29].

Forty farmers (48.19%) used >10 PWD for one planting season, while 43 farmers (51.81%) used ≤10 PWD. The number of labor (X 2) positively correlates with rice farming production (the coefficient value is 40.014). This result means that for every 1% PWD increase in the number of laborers, rice production will increase by 40.014%. The result of this study is consistent with Mahananto et al. [30] and Alam and Effendy [31], which state that the production factor of the amount of labor significantly affects increasing paddy rice production. The more labor employed, the more extensive farmland can be utilized; this shows that increasing the number of laborers (assuming that other inputs are fixed) can still increase rice farming production.

Seeds are the primary production input in farming activities because the production generated depends on the number of seeds used. A total of 43 farmers (51.81%) used seeds of ≤10 kg for one planting season, while 40 farmers (48.19%) used seeds >10 kg. Meanwhile, based on field research results, the average rice seeds per ha use was 13.602 kg or 0.0031 kg/m2. This amount was sufficient because it meets the government’s recommended rice seed use, around 0.0025 kg/m2. The analysis showed that the amount of rice seeds (X 3) significantly and positively affects rice farming production with a coefficient value of 52.184. This condition means that for every 1% increase in rice seeds, rice production will increase by 52.184%. Based on these results, the farmer still considered having an opportunity to increase the number of their farm production by increasing the number of seeds with the assumption that the other inputs are fixed. According to a study in Bangladesh, farmers who adopted high-yielding rice varieties between 2012 and 2015 saw a 35% increase in output during the monsoon season. Higher-yielding rice varieties meant more money for the farms that used them, as evidenced by this increased output [32]. Meanwhile, a study conducted in Côte d’Ivoire shows that rice farmers who utilize certified seeds experience higher yields and incomes than those who use farmers’ seeds [33].

The use of fertilizers aims to stimulate plant growth and increase crop production. There are two types of fertilizers used by farmers in the research area, namely, urea and ZA. All farmer respondents use urea fertilizer for rice cultivation in one planting season. The analysis showed that the amount of urea (X 4) significantly affects rice farming production with a positive coefficient. The coefficient of X 4 amounts to 9.465, which means that for every 1% increase in urea, rice production will increase by 9.465%. Consistent with the results of Kusnadi et al. [16], the elasticity of frontier production from nitrogen fertilizer (urea) variables significantly affected rice production. Urea is a nitrogen plant nutrient source that farmers widely use. Using urea fertilizer will spur the plant’s growth so that the output of the resulting crop will increase. On the contrary, Irawan and Antriyandarti [34] argued that using artificial fertilizers, such as urea, will boost rice yields in the short term but reduce them in the following seasons.

Only 33 farmers (39.76%) applied ZA fertilizer to paddy fields, while 50 farmers (60.24%) did not. The number of ZA fertilizers (X 5) significantly impacts farm production and positively affects rice farming production. The number of ZA fertilizers (X 5) has a coefficient value of 9.961. The result means that for every 1% increase in ZA, rice production will increase by 9.961%. Giving ZA fertilizer will increase plants’ nitrogen uptake. With a higher nitrogen content, the absorption of O will also increase. The fulfillment of plant nutrients can support plant growth. In other words, using this fertilizer can be improved if you want to increase rice farming production. According to Harahap [35], the ZA fertilizer application treatment increased the number of rice grains of the IR-64 variety by 4.58% compared to the standard fertilizer treatment. Meanwhile, the weight of milled dry grain per square meter increased by 2.14%. The research finding also aligns with a study in South Sulawesi Indonesia, where Keera Subdistrict farmers report that harvests of approximately 4–5 tons per ha occur when using improvised fertilizer, while output rises to 7–8 tons when complete fertilizer (200 kg of urea, 250 kg of NPK, 50 kg of ZA, and 100 kg of SP36) is used per ha per planting season [36].

As many as 71 farmers (85.54%) used tractors to cultivate rice fields in the research area, while the remaining 12 farmers (14.46%) did not use tractors. The tractor use (X 6) significantly affects rice farming production, but its relationship negatively affects production quantities. The use of tractors (X 6) has a coefficient value of 2738.962, which means that for every 1% increase in the use of tractors, rice production will decline by 2738.962%. This study’s results differ from those of Djamhari [37] and Herdiansyah et al. [21], which state that using tractors in farm management activities, besides reducing the use of labor, can also increase production. Although tractors are pretty beneficial, Ansar [38] states that the compacted soil that comes from rubber tire tractors can hinder the growth of plants. In the meantime, the rice field system in Lamongan District used pond land. Land for farming in the research area was quite wet, so using tractors was considered less efficient. Land did not need to be processed using the tractor because it would cause a decrease in the amount of rice production due to the land being too wet, so it was not easy to plant paddy.

Analysis of the stochastic frontier production function will also estimate the efficiency level that farmers have achieved (Table 3). Based on the analysis results, farmers’ efficiency level in flood-prone areas in Lamongan District is in the range of 0.05–0.98, with an average efficiency value of 0.76. The average efficiency value is in the efficient category because it is more significant than 0.70, which is the limit of the efficiency value [10]. Lamongan District is the largest rice production center in East Java and is one of the national granaries. Table 3 also shows the percentage of the number of farmers based on the efficiency level. Overall, rice farming in Lamongan has been in the category of efficient, as evidenced by 37.35% of the respondents who were in the efficiency range from 0.82 to 0.94.

Table 3

Group of respondents based on the level of efficiency

No. Efficiency Respondent (person) Percentage
1. 0.5–0.17 1 1.20
2. 0.18–0.29 4 4.82
3. 0.30–0.42 1 1.20
4. 0.43–0.55 3 3.61
5. 0.56–0.67 12 14.46
6. 0.68–0.82 21 25.30
7. 0.81–0.95 31 37.35
8. 0.94–0.98 10 12.05
Total 83 100.00
Mean efficiency 0.76
Minimum efficiency 0.05
Maximum efficiency 0.98

Source: Primary data analysis, 2019.

3.3 Factors that affect the efficiency of rice farming in flood-prone areas of Lamongan district

This analysis aims to identify the factors thought to be the cause of efficiency. Overall, the variables expected to affect the efficiency of rice farming significantly are as follows: The result of the efficiency variable estimation with stochastic frontier production function is more clearly seen in Table 4.

Table 4

Potential determinants of efficiency

No. Variable Coefficient SE p > |z|
1. Cons (α 0) −954.612*** 73.233 0.000
2. Farm size (Z 1) 0.465*** 0.003 0.000
3. Age of HH (Z 2) 1.617* 0.874 0.068
4. Formal education of HH (Z 3) 67.998*** 3.434 0.000
5. Land distance from house (Z 4) 0.001 0.111 0.938
6. Land tenure (D 1) 408.817*** 26.286 0.000
7. Off-farm jobs (D 2) 308.563*** 20.008 0.000
Number of observations 83
Prob > F 0.0000
R-squared 0.9968
Adj R-squared 0.9965
Root MSE 78.878

Source: Primary data analysis, 2019.

***Significant at 1% level; *Significant at 10% level.

The analysis showed the variable that does not significantly affect rice farming efficiency in flood-prone areas of Lamongan District, which is the distance between land and the farmer’s house (Z 4). Variables of land size (Z 1), formal education of HF (Z 3), the status of land ownership (D 1), and off-farm employment (D 2) indicate that the variables have a positive elasticity and are significantly efficient at a 1% level. The age of HH (Z 2) also showed positive efficiency elasticity, but it was significant at a 10% level.

Variable farm size (Z 1) has a positive coefficient (0.465) and significantly affects rice farming efficiency. The analysis shows that the farming efficiency achieved is positively associated with the size of land occupied by farmers. The results are consistent with Antriyandarti [24] and Lawalata et al. [39], which said land size significantly affects farming efficiency. More extensive land farming will increase the efficiency of rice farming due to increased farmland size, followed by the proper use of inputs and the principles of good management; then, the land will contribute to increased farming efficiency.

Age of HH (Z 2) significantly affects the efficiency of rice farming and has a marked positive coefficient (1.167) that states that the older the farmer’s age, the higher the efficiency of rice farming will be. The results are consistent with those of Noer et al. [40], who showed that the older the farmers, the more efficient their farming will be. Condition in the research area shows that most respondents (61 HH or 73.50%) were in the productive age range (<65 years), while 22 respondents (26.50%) were not. The age of farmers, which positively affects farm efficiency, is related to their experience in farming. Older farmers may become weaker than younger farmers, but older farmers are considered more experienced and able to make efficient decisions about their rice farming. In contrast, a negative correlation between HH age and producer technical efficiency was found in grain farming in Northwest Ethiopia, and this association was significant at the 1% level. Technical efficiency levels decrease with the increase in the producer age [17].

There were 29 farmers (34.94%) with an education of ≤6 years (primary school) in the research area. Then, as many as 12 farmers (14.46%) had 7–9 years of education (junior high school). Farmers with 10–12 years of education length (senior high school) numbered 33 people (39.76%). The remaining nine farmers (10.84%) took a diploma/bachelor’s degree (the length of education is >12 years). Formal education of HH (Z 3) indicates that the variable has a positive coefficient (67.998) and significantly affects the efficiency of rice farming. This condition means that the higher the education level of farmers, the more their farming efficiency will increase. These results are consistent with Maryanto et al. [41], which states that farmers’ low education level will influence their attitude toward accepting innovations in farming. Farmers who are highly educated are relatively faster in performing the recommended extension. Low education levels are generally less pleased with innovation, so the mental attitude to increase their knowledge, especially in agricultural science, is lesser. Meanwhile, a different situation was observed in northern Ghana, where more educated maize farmers had poorer technical efficiency [42].

Based on field research, 36 units of the land cultivated by farmers (43.37%) were 100–500 m from the farmer’s residence. In addition, 30 units of the land (36.14%) were 600–1,000 m away, and 13 units (15.66%) were 1,000–2,000 m from the farmer’s residence. Finally, four units of the land (4.82%) had a distance of 2,100–5,000 m from the farmer’s house. The result analysis shows that the variable land distance from the house (Z 4) did not significantly affect the efficiency of rice farming. Distance of land near or far from the farmer’s home did not considerably affect the efficiency of rice farming in Lamongan District. Widyawati and Pujiyono [43] and Santi Nikmatullah et al. [44] said that the distance of the land that is not so far from the location of the farmer’s house makes it easy for farmers to allocate their time related to the distance to reach their land so that the time they use on the land can be more efficient. The condition of roads in the research area is still in need of improvement. However, this condition still does not affect the farmers’ farming efficiency because their transportation access is sufficient. Most respondent farmers reach their land farm by motorcycle or simply walking because the location is not so far from home.

The dummy variable in land tenure (D 1) significantly affects rice farming efficiency with a positive coefficient (408.817), which means that the status of land “owner” will increase efficiency more than that of non-owners. Farming on owned land will have a better level of efficiency than status of non-owned land. According to Kusnadi et al. [16] it is natural because the farmers who work the land of their own will have a higher sense of belonging than the non-owners, so farmers will be performing the land as well as possible to produce with higher efficiency. The study’s results differ from those of Jamalludin [28], who contended that, given the prevalent factor of market inefficiencies in the region, the issuance of land certificates to rural households in Northwest China negatively affected the technical efficiency of agricultural productivity.

In Lamongan District, the jobs outside the agricultural industry consisted of traders (24 people or 40.00%), civil servants (10 people or 16.67%), private employees (6 people or 10.00%), livestock breeders (14 people or 23.33%), and other jobs (6 people or 10.00%). Meanwhile, the remaining 23 people only worked in agriculture. The dummy variable of off-farm jobs (D 2) has a positive coefficient of elasticity (308.563) and significantly affects the efficiency of rice farming. This result means farmers who have jobs outside agriculture tend to be more efficient. The results are consistent with those of Tijani [45], who found that farmers who also have jobs outside agriculture tend to have higher efficiency than farmers who do not. According to Susilowati and Tinaprilia [46], farmers with other side jobs are expected to provide inputs as necessary so that the farm’s efficiency will also be relatively high. Instead, farmers who only hang their farming as their main livelihood, the results of their farming simply utilizing existing resources due to limited production costs and the production curve, were unable to approach the frontier or, in other words, having a relatively low efficiency.

4 Conclusion

Analysis of the production function aims to describe the relationship between the total production and the input production, which is estimated in this study using a stochastic frontier production function model. Based on the results of the analysis, it can be seen that factors that affect rice production in a flood-prone area in Lamongan District are the farm size (X 1), the number of labor (X 2), the number of rice seeds (X 3), the amount of urea fertilizer (X 4), and the amount of ZA fertilizer (X 5). The use of tractors (X 6) has no significant effect on the production of rice farming because the type of land used by farmers is a wetland pond, so the use of tractors will cause the soil to be too wet, making it challenging to plant paddy. The identification result of the factors thought to be the cause of efficiency shows that variables that have positive elasticity and significantly affect the efficiency of rice farming in Lamongan District are the variables of farm size (Z 1), age of HH (Z 2), formal education of HH (Z 3), dummy of land tenure (D 1), and dummy of off-farm jobs (D 2). In contrast, the land distance from the farmer’s house (Z 4) does not significantly affect efficiency.

The implication is that farmers are still able to increase the amount of production by increasing the land size, number of employees, the number of rice seeds, and the amount of urea or ZA fertilizers they use (while assuming the other input are fixed), since this variable can still improve the results of their farm production to the limit of maximum efficiency. Land tenure has a coefficient of elasticity, which is the largest among the other predictor variables on the efficiency of rice farming, so farmers in Lamongan District advised farming with the status of their land. Farmers are also advised to have a job outside the farm as their complementary rice farming, considering that Lamongan District is prone to flooding, so the risk of crop failure tends to be more significant.

  1. Funding information: The authors state no funding involved.

  2. Conflict of interest: The authors state no conflict of interest.

  3. Data availability statement: The data is not available for sharing as per respondents decision.

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Received: 2024-01-09
Revised: 2024-02-29
Accepted: 2024-03-27
Published Online: 2024-04-20

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Regular Articles
  2. Supplementation of P-solubilizing purple nonsulfur bacteria, Rhodopseudomonas palustris improved soil fertility, P nutrient, growth, and yield of Cucumis melo L.
  3. Yield gap variation in rice cultivation in Indonesia
  4. Effects of co-inoculation of indole-3-acetic acid- and ammonia-producing bacteria on plant growth and nutrition, soil elements, and the relationships of soil microbiomes with soil physicochemical parameters
  5. Impact of mulching and planting time on spring-wheat (Triticum aestivum) growth: A combined field experiment and empirical modeling approach
  6. Morphological diversity, correlation studies, and multiple-traits selection for yield and yield components of local cowpea varieties
  7. Participatory on-farm evaluation of new orange-fleshed sweetpotato varieties in Southern Ethiopia
  8. Yield performance and stability analysis of three cultivars of Gayo Arabica coffee across six different environments
  9. Biology of Spodoptera frugiperda (Lepidoptera: Noctuidae) on different types of plants feeds: Potency as a pest on various agricultural plants
  10. Antidiabetic activity of methanolic extract of Hibiscus sabdariffa Linn. fruit in alloxan-induced Swiss albino diabetic mice
  11. Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance
  12. Nicotinamide as a biostimulant improves soybean growth and yield
  13. Farmer’s willingness to accept the sustainable zoning-based organic farming development plan: A lesson from Sleman District, Indonesia
  14. Uncovering hidden determinants of millennial farmers’ intentions in running conservation agriculture: An application of the Norm Activation Model
  15. Mediating role of leadership and group capital between human capital component and sustainability of horticultural agribusiness institutions in Indonesia
  16. Biochar technology to increase cassava crop productivity: A study of sustainable agriculture on degraded land
  17. Effect of struvite on the growth of green beans on Mars and Moon regolith simulants
  18. UrbanAgriKG: A knowledge graph on urban agriculture and its embeddings
  19. Provision of loans and credit by cocoa buyers under non-price competition: Cocoa beans market in Ghana
  20. Effectiveness of micro-dosing of lime on selected chemical properties of soil in Banja District, North West, Ethiopia
  21. Effect of weather, nitrogen fertilizer, and biostimulators on the root size and yield components of Hordeum vulgare
  22. Effects of selected biostimulants on qualitative and quantitative parameters of nine cultivars of the genus Capsicum spp.
  23. Growth, yield, and secondary metabolite responses of three shallot cultivars at different watering intervals
  24. Design of drainage channel for effective use of land on fully mechanized sugarcane plantations: A case study at Bone Sugarcane Plantation
  25. Technical feasibility and economic benefit of combined shallot seedlings techniques in Indonesia
  26. Control of Meloidogyne javanica in banana by endophytic bacteria
  27. Comparison of important quality components of red-flesh kiwifruit (Actinidia chinensis) in different locations
  28. Efficiency of rice farming in flood-prone areas of East Java, Indonesia
  29. Comparative analysis of alpine agritourism in Trentino, Tyrol, and South Tyrol: Regional variations and prospects
  30. Detection of Fusarium spp. infection in potato (Solanum tuberosum L.) during postharvest storage through visible–near-infrared and shortwave–near-infrared reflectance spectroscopy
  31. Forage yield, seed, and forage qualitative traits evaluation by determining the optimal forage harvesting stage in dual-purpose cultivation in safflower varieties (Carthamus tinctorius L.)
  32. The influence of tourism on the development of urban space: Comparison in Hanoi, Danang, and Ho Chi Minh City
  33. Optimum intra-row spacing and clove size for the economical production of garlic (Allium sativum L.) in Northwestern Highlands of Ethiopia
  34. The role of organic rice farm income on farmer household welfare: Evidence from Yogyakarta, Indonesia
  35. Exploring innovative food in a developing country: Edible insects as a sustainable option
  36. Genotype by environment interaction and performance stability of common bean (Phaseolus vulgaris L.) cultivars grown in Dawuro zone, Southwestern Ethiopia
  37. Factors influencing green, environmentally-friendly consumer behaviour
  38. Factors affecting coffee farmers’ access to financial institutions: The case of Bandung Regency, Indonesia
  39. Morphological and yield trait-based evaluation and selection of chili (Capsicum annuum L.) genotypes suitable for both summer and winter seasons
  40. Sustainability analysis and decision-making strategy for swamp buffalo (Bubalus bubalis carabauesis) conservation in Jambi Province, Indonesia
  41. Understanding factors affecting rice purchasing decisions in Indonesia: Does rice brand matter?
  42. An implementation of an extended theory of planned behavior to investigate consumer behavior on hygiene sanitation-certified livestock food products
  43. Information technology adoption in Indonesia’s small-scale dairy farms
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  46. Fostering cocoa industry resilience: A collaborative approach to managing farm gate price fluctuations in West Sulawesi, Indonesia
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  48. Near-infrared technology in agriculture: Rapid, simultaneous, and non-destructive determination of inner quality parameters on intact coffee beans
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  73. Evaluating agricultural yield and economic implications of varied irrigation depths on maize yield in semi-arid environments, at Birfarm, Upper Blue Nile, Ethiopia
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  77. Tourism in rural areas as a broader concept: Some insights from the Portuguese reality
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  98. Technical efficiency of sugarcane farming in East Java, Indonesia: A bootstrap data envelopment analysis
  99. Comparison between mycobiota diversity and fungi and mycotoxin contamination of maize and wheat
  100. Evaluation of cultivation technology package and corn variety based on agronomy characters and leaf green indices
  101. Exploring the association between the consumption of beverages, fast foods, sweets, fats, and oils and the risk of gastric and pancreatic cancers: Findings from case–control study
  102. Phytochemical composition and insecticidal activity of Acokanthera oblongifolia (Hochst.) Benth & Hook.f. ex B.D.Jacks. extract on life span and biological aspects of Spodoptera littoralis (Biosd.)
  103. Land use management solutions in response to climate change: Case study in the central coastal areas of Vietnam
  104. Evaluation of coffee pulp as a feed ingredient for ruminants: A meta-analysis
  105. Interannual variations of normalized difference vegetation index and potential evapotranspiration and their relationship in the Baghdad area
  106. Harnessing synthetic microbial communities with nitrogen-fixing activity to promote rice growth
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  108. Response of potato tuber as an effect of the N-fertilizer and paclobutrazol application in medium altitude
  109. Bridging the gap: The role of geographic proximity in enhancing seed sustainability in Bandung District
  110. Evaluation of Abrams curve in agricultural sector using the NARDL approach
  111. Challenges and opportunities for young farmers in the implementation of the Rural Development Program 2014–2020 of the Republic of Croatia
  112. Yield stability of ten common bean (Phaseolus vulgaris L.) genotypes at different sowing dates in Lubumbashi, South-East of DR Congo
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  114. Phytochemical analysis of Bienertia sinuspersici extract and its antioxidant and antimicrobial activities
  115. Evaluation of relative drought tolerance of grapevines by leaf fluorescence parameters
  116. Yield assessment of new streak-resistant topcross maize hybrids in Benin
  117. Improvement of cocoa powder properties through ultrasonic- and microwave-assisted alkalization
  118. Potential of ecoenzymes made from nutmeg (Myristica fragrans) leaf and pulp waste as bioinsecticides for Periplaneta americana
  119. Analysis of farm performance to realize the sustainability of organic cabbage vegetable farming in Getasan Semarang, Indonesia
  120. Revealing the influences of organic amendment-derived dissolved organic matter on growth and nutrient accumulation in lettuce seedlings (Lactuca sativa L.)
  121. Identification of viruses infecting sweetpotato (Ipomoea batatas Lam.) in Benin
  122. Assessing the soil physical and chemical properties of long-term pomelo orchard based on tree growth
  123. Investigating access and use of digital tools for agriculture among rural farmers: A case study of Nkomazi Municipality, South Africa
  124. Does sex influence the impact of dietary vitD3 and UVB light on performance parameters and welfare indicators of broilers?
  125. Design of intelligent sprayer control for an autonomous farming drone using a multiclass support vector machine
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  127. Review Articles
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  129. Role of dietary fats in reproductive, health, and nutritional benefits in farm animals: A review
  130. Climate change and adaptive strategies on viticulture (Vitis spp.)
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  132. A systematic review on potential analogy of phytobiomass and soil carbon evaluation methods: Ethiopia insights
  133. A review of storage temperature and relative humidity effects on shelf life and quality of mango (Mangifera indica L.) fruit and implications for nutrition insecurity in Ethiopia
  134. Green extraction of nutmeg (Myristica fragrans) phytochemicals: Prospective strategies and roadblocks
  135. Potential influence of nitrogen fertilizer rates on yield and yield components of carrot (Dacus carota L.) in Ethiopia: Systematic review
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  137. State and contours of research on roselle (Hibiscus sabdariffa L.) in Africa
  138. The potential of phosphorus-solubilizing purple nonsulfur bacteria in agriculture: Present and future perspectives
  139. Minor millets: Processing techniques and their nutritional and health benefits
  140. Meta-analysis of reproductive performance of improved dairy cattle under Ethiopian environmental conditions
  141. Review on enhancing the efficiency of fertilizer utilization: Strategies for optimal nutrient management
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  145. Short Communications
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  149. Corrigendum to “Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance”
  150. Corrigendum to “Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types”
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https://doi.org/10.1515/opag-2022-0284
Keywords for this article
rice farming; flood-prone; the efficiency of rice production
Creative Commons
BY 4.0

Articles in the same Issue

  1. Regular Articles
  2. Supplementation of P-solubilizing purple nonsulfur bacteria, Rhodopseudomonas palustris improved soil fertility, P nutrient, growth, and yield of Cucumis melo L.
  3. Yield gap variation in rice cultivation in Indonesia
  4. Effects of co-inoculation of indole-3-acetic acid- and ammonia-producing bacteria on plant growth and nutrition, soil elements, and the relationships of soil microbiomes with soil physicochemical parameters
  5. Impact of mulching and planting time on spring-wheat (Triticum aestivum) growth: A combined field experiment and empirical modeling approach
  6. Morphological diversity, correlation studies, and multiple-traits selection for yield and yield components of local cowpea varieties
  7. Participatory on-farm evaluation of new orange-fleshed sweetpotato varieties in Southern Ethiopia
  8. Yield performance and stability analysis of three cultivars of Gayo Arabica coffee across six different environments
  9. Biology of Spodoptera frugiperda (Lepidoptera: Noctuidae) on different types of plants feeds: Potency as a pest on various agricultural plants
  10. Antidiabetic activity of methanolic extract of Hibiscus sabdariffa Linn. fruit in alloxan-induced Swiss albino diabetic mice
  11. Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance
  12. Nicotinamide as a biostimulant improves soybean growth and yield
  13. Farmer’s willingness to accept the sustainable zoning-based organic farming development plan: A lesson from Sleman District, Indonesia
  14. Uncovering hidden determinants of millennial farmers’ intentions in running conservation agriculture: An application of the Norm Activation Model
  15. Mediating role of leadership and group capital between human capital component and sustainability of horticultural agribusiness institutions in Indonesia
  16. Biochar technology to increase cassava crop productivity: A study of sustainable agriculture on degraded land
  17. Effect of struvite on the growth of green beans on Mars and Moon regolith simulants
  18. UrbanAgriKG: A knowledge graph on urban agriculture and its embeddings
  19. Provision of loans and credit by cocoa buyers under non-price competition: Cocoa beans market in Ghana
  20. Effectiveness of micro-dosing of lime on selected chemical properties of soil in Banja District, North West, Ethiopia
  21. Effect of weather, nitrogen fertilizer, and biostimulators on the root size and yield components of Hordeum vulgare
  22. Effects of selected biostimulants on qualitative and quantitative parameters of nine cultivars of the genus Capsicum spp.
  23. Growth, yield, and secondary metabolite responses of three shallot cultivars at different watering intervals
  24. Design of drainage channel for effective use of land on fully mechanized sugarcane plantations: A case study at Bone Sugarcane Plantation
  25. Technical feasibility and economic benefit of combined shallot seedlings techniques in Indonesia
  26. Control of Meloidogyne javanica in banana by endophytic bacteria
  27. Comparison of important quality components of red-flesh kiwifruit (Actinidia chinensis) in different locations
  28. Efficiency of rice farming in flood-prone areas of East Java, Indonesia
  29. Comparative analysis of alpine agritourism in Trentino, Tyrol, and South Tyrol: Regional variations and prospects
  30. Detection of Fusarium spp. infection in potato (Solanum tuberosum L.) during postharvest storage through visible–near-infrared and shortwave–near-infrared reflectance spectroscopy
  31. Forage yield, seed, and forage qualitative traits evaluation by determining the optimal forage harvesting stage in dual-purpose cultivation in safflower varieties (Carthamus tinctorius L.)
  32. The influence of tourism on the development of urban space: Comparison in Hanoi, Danang, and Ho Chi Minh City
  33. Optimum intra-row spacing and clove size for the economical production of garlic (Allium sativum L.) in Northwestern Highlands of Ethiopia
  34. The role of organic rice farm income on farmer household welfare: Evidence from Yogyakarta, Indonesia
  35. Exploring innovative food in a developing country: Edible insects as a sustainable option
  36. Genotype by environment interaction and performance stability of common bean (Phaseolus vulgaris L.) cultivars grown in Dawuro zone, Southwestern Ethiopia
  37. Factors influencing green, environmentally-friendly consumer behaviour
  38. Factors affecting coffee farmers’ access to financial institutions: The case of Bandung Regency, Indonesia
  39. Morphological and yield trait-based evaluation and selection of chili (Capsicum annuum L.) genotypes suitable for both summer and winter seasons
  40. Sustainability analysis and decision-making strategy for swamp buffalo (Bubalus bubalis carabauesis) conservation in Jambi Province, Indonesia
  41. Understanding factors affecting rice purchasing decisions in Indonesia: Does rice brand matter?
  42. An implementation of an extended theory of planned behavior to investigate consumer behavior on hygiene sanitation-certified livestock food products
  43. Information technology adoption in Indonesia’s small-scale dairy farms
  44. Draft genome of a biological control agent against Bipolaris sorokiniana, the causal phytopathogen of spot blotch in wheat (Triticum turgidum L. subsp. durum): Bacillus inaquosorum TSO22
  45. Assessment of the recurrent mutagenesis efficacy of sesame crosses followed by isolation and evaluation of promising genetic resources for use in future breeding programs
  46. Fostering cocoa industry resilience: A collaborative approach to managing farm gate price fluctuations in West Sulawesi, Indonesia
  47. Field investigation of component failures for selected farm machinery used in small rice farming operations
  48. Near-infrared technology in agriculture: Rapid, simultaneous, and non-destructive determination of inner quality parameters on intact coffee beans
  49. The synergistic application of sucrose and various LED light exposures to enhance the in vitro growth of Stevia rebaudiana (Bertoni)
  50. Weather index-based agricultural insurance for flower farmers: Willingness to pay, sales, and profitability perspectives
  51. Meta-analysis of dietary Bacillus spp. on serum biochemical and antioxidant status and egg quality of laying hens
  52. Biochemical characterization of trypsin from Indonesian skipjack tuna (Katsuwonus pelamis) viscera
  53. Determination of C-factor for conventional cultivation and soil conservation technique used in hop gardens
  54. Empowering farmers: Unveiling the economic impacts of contract farming on red chilli farmers’ income in Magelang District, Indonesia
  55. Evaluating salt tolerance in fodder crops: A field experiment in the dry land
  56. Labor productivity of lowland rice (Oryza sativa L.) farmers in Central Java Province, Indonesia
  57. Cropping systems and production assessment in southern Myanmar: Informing strategic interventions
  58. The effect of biostimulants and red mud on the growth and yield of shallots in post-unlicensed gold mining soil
  59. Effects of dietary Adansonia digitata L. (baobab) seed meal on growth performance and carcass characteristics of broiler chickens: A systematic review and meta-analysis
  60. Analysis and structural characterization of the vid-pisco market
  61. Pseudomonas fluorescens SP007s enhances defense responses against the soybean bacterial pustule caused by Xanthomonas axonopodis pv. glycines
  62. A brief investigation on the prospective of co-composted biochar as a fertilizer for Zucchini plants cultivated in arid sandy soil
  63. Supply chain efficiency of red chilies in the production center of Sleman Indonesia based on performance measurement system
  64. Investment development path for developed economies: Is agriculture different?
  65. Power relations among actors in laying hen business in Indonesia: A MACTOR analysis
  66. High-throughput digital imaging and detection of morpho-physiological traits in tomato plants under drought
  67. Converting compression ignition engine to dual-fuel (diesel + CNG) engine and experimentally investigating its performance and emissions
  68. Structuration, risk management, and institutional dynamics in resolving palm oil conflicts
  69. Spacing strategies for enhancing drought resilience and yield in maize agriculture
  70. Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types
  71. Investigating Spodoptera spp. diversity, percentage of attack, and control strategies in the West Java, Indonesia, corn cultivation
  72. Yield stability of biofertilizer treatments to soybean in the rainy season based on the GGE biplot
  73. Evaluating agricultural yield and economic implications of varied irrigation depths on maize yield in semi-arid environments, at Birfarm, Upper Blue Nile, Ethiopia
  74. Chemometrics for mapping the spatial nitrate distribution on the leaf lamina of fenugreek grown under varying nitrogenous fertilizer doses
  75. Pomegranate peel ethanolic extract: A promising natural antioxidant, antimicrobial agent, and novel approach to mitigate rancidity in used edible oils
  76. Transformative learning and engagement with organic farming: Lessons learned from Indonesia
  77. Tourism in rural areas as a broader concept: Some insights from the Portuguese reality
  78. Assessment enhancing drought tolerance in henna (Lawsonia inermis L.) ecotypes through sodium nitroprusside foliar application
  79. Edible insects: A survey about perceptions regarding possible beneficial health effects and safety concerns among adult citizens from Portugal and Romania
  80. Phenological stages analysis in peach trees using electronic nose
  81. Harvest date and salicylic acid impact on peanut (Arachis hypogaea L.) properties under different humidity conditions
  82. Hibiscus sabdariffa L. petal biomass: A green source of nanoparticles of multifarious potential
  83. Use of different vegetation indices for the evaluation of the kinetics of the cherry tomato (Solanum lycopersicum var. cerasiforme) growth based on multispectral images by UAV
  84. First evidence of microplastic pollution in mangrove sediments and its ingestion by coral reef fish: Case study in Biawak Island, Indonesia
  85. Physical and textural properties and sensory acceptability of wheat bread partially incorporated with unripe non-commercial banana cultivars
  86. Cereibacter sphaeroides ST16 and ST26 were used to solubilize insoluble P forms to improve P uptake, growth, and yield of rice in acidic and extreme saline soil
  87. Avocado peel by-product in cattle diets and supplementation with oregano oil and effects on production, carcass, and meat quality
  88. Optimizing inorganic blended fertilizer application for the maximum grain yield and profitability of bread wheat and food barley in Dawuro Zone, Southwest Ethiopia
  89. The acceptance of social media as a channel of communication and livestock information for sheep farmers
  90. Adaptation of rice farmers to aging in Thailand
  91. Combined use of improved maize hybrids and nitrogen application increases grain yield of maize, under natural Striga hermonthica infestation
  92. From aquatic to terrestrial: An examination of plant diversity and ecological shifts
  93. Statistical modelling of a tractor tractive performance during ploughing operation on a tropical Alfisol
  94. Participation in artisanal diamond mining and food security: A case study of Kasai Oriental in DR Congo
  95. Assessment and multi-scenario simulation of ecosystem service values in Southwest China’s mountainous and hilly region
  96. Analysis of agricultural emissions and economic growth in Europe in search of ecological balance
  97. Bacillus thuringiensis strains with high insecticidal activity against insect larvae of the orders Coleoptera and Lepidoptera
  98. Technical efficiency of sugarcane farming in East Java, Indonesia: A bootstrap data envelopment analysis
  99. Comparison between mycobiota diversity and fungi and mycotoxin contamination of maize and wheat
  100. Evaluation of cultivation technology package and corn variety based on agronomy characters and leaf green indices
  101. Exploring the association between the consumption of beverages, fast foods, sweets, fats, and oils and the risk of gastric and pancreatic cancers: Findings from case–control study
  102. Phytochemical composition and insecticidal activity of Acokanthera oblongifolia (Hochst.) Benth & Hook.f. ex B.D.Jacks. extract on life span and biological aspects of Spodoptera littoralis (Biosd.)
  103. Land use management solutions in response to climate change: Case study in the central coastal areas of Vietnam
  104. Evaluation of coffee pulp as a feed ingredient for ruminants: A meta-analysis
  105. Interannual variations of normalized difference vegetation index and potential evapotranspiration and their relationship in the Baghdad area
  106. Harnessing synthetic microbial communities with nitrogen-fixing activity to promote rice growth
  107. Agronomic and economic benefits of rice–sweetpotato rotation in lowland rice cropping systems in Uganda
  108. Response of potato tuber as an effect of the N-fertilizer and paclobutrazol application in medium altitude
  109. Bridging the gap: The role of geographic proximity in enhancing seed sustainability in Bandung District
  110. Evaluation of Abrams curve in agricultural sector using the NARDL approach
  111. Challenges and opportunities for young farmers in the implementation of the Rural Development Program 2014–2020 of the Republic of Croatia
  112. Yield stability of ten common bean (Phaseolus vulgaris L.) genotypes at different sowing dates in Lubumbashi, South-East of DR Congo
  113. Effects of encapsulation and combining probiotics with different nitrate forms on methane emission and in vitro rumen fermentation characteristics
  114. Phytochemical analysis of Bienertia sinuspersici extract and its antioxidant and antimicrobial activities
  115. Evaluation of relative drought tolerance of grapevines by leaf fluorescence parameters
  116. Yield assessment of new streak-resistant topcross maize hybrids in Benin
  117. Improvement of cocoa powder properties through ultrasonic- and microwave-assisted alkalization
  118. Potential of ecoenzymes made from nutmeg (Myristica fragrans) leaf and pulp waste as bioinsecticides for Periplaneta americana
  119. Analysis of farm performance to realize the sustainability of organic cabbage vegetable farming in Getasan Semarang, Indonesia
  120. Revealing the influences of organic amendment-derived dissolved organic matter on growth and nutrient accumulation in lettuce seedlings (Lactuca sativa L.)
  121. Identification of viruses infecting sweetpotato (Ipomoea batatas Lam.) in Benin
  122. Assessing the soil physical and chemical properties of long-term pomelo orchard based on tree growth
  123. Investigating access and use of digital tools for agriculture among rural farmers: A case study of Nkomazi Municipality, South Africa
  124. Does sex influence the impact of dietary vitD3 and UVB light on performance parameters and welfare indicators of broilers?
  125. Design of intelligent sprayer control for an autonomous farming drone using a multiclass support vector machine
  126. Deciphering salt-responsive NB-ARC genes in rice transcriptomic data: A bioinformatics approach with gene expression validation
  127. Review Articles
  128. Impact of nematode infestation in livestock production and the role of natural feed additives – A review
  129. Role of dietary fats in reproductive, health, and nutritional benefits in farm animals: A review
  130. Climate change and adaptive strategies on viticulture (Vitis spp.)
  131. The false tiger of almond, Monosteira unicostata (Hemiptera: Tingidae): Biology, ecology, and control methods
  132. A systematic review on potential analogy of phytobiomass and soil carbon evaluation methods: Ethiopia insights
  133. A review of storage temperature and relative humidity effects on shelf life and quality of mango (Mangifera indica L.) fruit and implications for nutrition insecurity in Ethiopia
  134. Green extraction of nutmeg (Myristica fragrans) phytochemicals: Prospective strategies and roadblocks
  135. Potential influence of nitrogen fertilizer rates on yield and yield components of carrot (Dacus carota L.) in Ethiopia: Systematic review
  136. Corn silk: A promising source of antimicrobial compounds for health and wellness
  137. State and contours of research on roselle (Hibiscus sabdariffa L.) in Africa
  138. The potential of phosphorus-solubilizing purple nonsulfur bacteria in agriculture: Present and future perspectives
  139. Minor millets: Processing techniques and their nutritional and health benefits
  140. Meta-analysis of reproductive performance of improved dairy cattle under Ethiopian environmental conditions
  141. Review on enhancing the efficiency of fertilizer utilization: Strategies for optimal nutrient management
  142. The nutritional, phytochemical composition, and utilisation of different parts of maize: A comparative analysis
  143. Motivations for farmers’ participation in agri-environmental scheme in the EU, literature review
  144. Evolution of climate-smart agriculture research: A science mapping exploration and network analysis
  145. Short Communications
  146. Music enrichment improves the behavior and leukocyte profile of dairy cattle
  147. Effect of pruning height and organic fertilization on the morphological and productive characteristics of Moringa oleifera Lam. in the Peruvian dry tropics
  148. Corrigendum
  149. Corrigendum to “Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance”
  150. Corrigendum to “Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types”
  151. Special issue: Smart Agriculture System for Sustainable Development: Methods and Practices
  152. Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy
  153. FruitVision: A deep learning based automatic fruit grading system
  154. Energy harvesting and ANFIS modeling of a PVDF/GO-ZNO piezoelectric nanogenerator on a UAV
  155. Effects of stress hormones on digestibility and performance in cattle: A review
  156. Special Issue of The 4th International Conference on Food Science and Engineering (ICFSE) 2022 - Part II
  157. Assessment of omega-3 and omega-6 fatty acid profiles and ratio of omega-6/omega-3 of white eggs produced by laying hens fed diets enriched with omega-3 rich vegetable oil
  158. Special Issue on FCEM - International Web Conference on Food Choice & Eating Motivation - Part II
  159. Special Issue on FCEM – International Web Conference on Food Choice & Eating Motivation: Message from the editor
  160. Fruit and vegetable consumption: Study involving Portuguese and French consumers
  161. Knowledge about consumption of milk: Study involving consumers from two European Countries – France and Portugal
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