Forecasting the Optimal Sustainable Development of the Romanian Ecological Agriculture

Abstract

Organic farming is an important objective of the European Commission, translated into the European Green Pact through the Farm to Fork Strategy and the Biodiversity Strategy, with EU member countries having to find solutions to meet the target of at least 25% of agricultural land being used for organic cultivation by 2030. The aim for Romania can be achieved by modelling the distribution of crops in terms of cultivated areas and production yields obtained in organic and conventional systems according to the population size. Applying quantitative and qualitative analysis of EUROSTAT data for the above-mentioned indicators, the geomean function, linear programming, and the simplex method were used, depending on the set objectives. To demonstrate that organic farming can be sustainable and in line with the three pillars of sustainability, economic, social and environmental, we related the agricultural area to the population of Romania to highlight the average annual growth rate for the 2020–2030 tine horizon. The results showed an increase in agricultural area per capita of 0.708 ha (4.91%), compared to 0.69 ha as the average for the period 2012–2020, which correlated with organic production yields 32% lower than conventional agriculture. Through modelling, the reduction in organic farm yield was found to be less than or equal to the increase in area per capita, thus reaching the proposed target. The results of this study have long-term implications for supporting the transition to organic farming in the sense that the study argues that reaching the target of 25% of agricultural land that can enter organic farming is in line with the sustainability trilogy. The approach used can be followed and replicated according to national agricultural policies.

1. Introduction

Agriculture is an important sector for Romania, with an average utilised agricultural area (UAA) of 13.6 million hectares [1]. Agriculture contributes 3.8% toward Romanian GDP (in 2020). Agriculture is an activity that competes for land, so any policy change that affects one land use has the potential to induce changes in the other [2]. Sustainable land use involves considering the range of social, economic and environmental goods and services provided in a given region [3]. Sustainable land use also involves careful consideration of the long-term attributes of resilience and robustness that maintain the underlying ecosystem processes. Population density and GDP are useful indicators in relation to the two dimensions of human activity, the social and economic aspects, which are connected to land use characteristics. The presence of a larger population density requires a higher intensity of land use. On the other hand, increasing economic production requires more intervention on the land [4]. To carry out this study and in line with the set target of increasing arable land in organic farming by 25% by 2030, we analysed the input indicators established for analysis and modelling.

1.1. Conventional Agriculture

The utilised agricultural area (UAA) decreased by 4.98% in 2020 (13,048.80 thousand ha) compared to 2012 (13,733.14 thousand ha), with Romania ranking 6th in the EU-27, after France, Spain, Germany, Poland and Italy (

Table 1. The breakdown of the Romanian utilized agricultural area (UAA).

	2012	2013	2014	2015	2016	2017	2018	2019	2020	Avg. (%)
Utilised agricultural area (1000 ha)	13,733	13,905	13,830	13,858	13,521	13,378	13,414	13,826	13,049	100.0
Arable land (%)	64.1	62.9	63.5	63.3	63.5	63.9	64.8	64.8	65.0	64.0
Permanent grassland (%)	32.7	33.9	33.5	33.6	33.4	33.0	32.0	32.2	31.9	32.9
Permanent crops (%)	2.4	2.4	2.2	2.3	2.4	2.4	2.5	2.3	2.3	2.3
Kitchen gardens (%)	0.8	0.8	0.8	0.8	0.7	0.7	0.7	0.7	0.8	0.8

Source: Calculations based on EUROSTAT data series, years 2012–2022 https://ec.europa.eu/eurostat/databrowser/product/page/TAG00025__custom_3351494 (accessed on 14 September 2022) Utilised agricultural area by categories [TAG00025__custom_3351494].

). Within the structure of land use categories, the largest share, 64%, is occupied by arable land, with a decrease recorded in 2020 (8482.86 thousand ha) of 3.6% compared to 2012 (8797.65 thousand ha). Romania ranks 5th in the EU-27 in this indicator, after France, Spain, Germany and Poland.

Although Romania is among the top EU countries in terms of cultivated areas, it has lower production yields per ha. The extremely severe 2020 and 2022 droughts have worsened these deficits [5]. The relative economic performance of organic and conventional agriculture is determined by the ratio of production costs to production value. Both organic and conventional farmers are vulnerable to fluctuations in input and output prices. The future of material prices is uncertain. However, changes in commodity prices may have a greater impact on conventional farmers [6].

1.2. Organic Farming

Organic farming has been present in Romania since 2000 (17,388 ha) and the land area in production was relatively constant until 2007 (131,529 ha). Since 2007 and until now both the area and the number of organic operators has increased, at a variable pace. In the National Rural Development Plan (NRDP) 2007–2013, Romania did not benefit from compensatory payments, because no measure was implemented in the programme [7]. In the National Rural Development Plan (NRDP) 2014–2020, organic farming benefited from Measure 11- Organic farming, with support being directed towards conversion, methods and maintenance of organic farming practices.

Data presented by “[8]” on organic farming in the EU reveal that at the end of 2020, there were 14.9 million ha (9.2% of total production) of organic land in the European Union managed by more than 349 thousand producers (

Table 2. Organic land use in Europe, 2020.

Country	Organic Land Area (1000 ha)	Percentage of Organic Agricultural Land (%)	Organic Land Use								Producers (nr)	Processors (nr)
			Grassland (ha)	%	Arable Crops (ha)	%	Permanent Crops (ha)	%	Other (ha)	%
Austria	680	26.5	392,168	58	275,403	41	12,301	2	No d	0	24,480	22,689
Italy	2095	16.0	583,781	28	1,016,287	49	495,296	24	No d	0	71,590	20,087
Spain	2438	10.0	1,273,392	52	502,074	21	662,425	27	No d	0	44,493	5561
Germany	1702	10.2	880,000	54	735,727	49	25,132	2	No d	0	53,255	19,311
EU-27	14,900	9.2	6,290,847	42	6,750,565	46	1,680,385	11	84,525	1	349,551	778,416
France	2549	8.8	879,244	34	1,445,221	57	193,731	8	30,481	0	41,632	16,651
Hungary	301	6.0	180,961	60	105,562	35	14,907	5	No d	0	5128	521
Polonia	509	3.5	85,741	17	375,939	74	47,615	9	No d	0	18,598	668
Romania	469	3.5	155,038	33	291,628	62	22,221	5	No d	0	9647	201
Bulgaria	116	2.3	30,154	26	61,269	53	24,849	21	No d	0	5942	249
Ireland	75	1.7	66,488	89	8103	11	75	0	No d	0	1777	180
Malta	0.1	0.6	No d	0	41	61	26	39	No d	0	25	8

Source: Austrian Federal Ministry of Agriculture Forestry—Environment and Water Management—Eurostat. Research Institute of Organic Agriculture (FiBL) and Agricultural Market Information Company (AM). Data compiled by Fibl based on Eurostat and national data sources. https://www.organicseurope.bio/about-us/organic-in-europe/ (accessed on 14 September 2022).

, col 2 and col 12). The countries with the largest organic agricultural areas are France (2.5 million ha), Spain (2.4 million ha), Italy (2.1 million ha), and Germany (1.7 million ha). Romania has an organic agricultural area of over 469 thousand ha (3.5%) managed by 9647 producers. The organic areas, for the countries mentioned, are composed of grassland (minimum 26% (Bulgaria) and maximum 89% (Ireland)), arable crops (minimum 21% (Spain) and maximum 74% (Poland)), permanent crops (0% (Ireland) and maximum 39% (Malta)) (Table 2).

From a policy perspective, the Farm to Fork strategy target of having “at least 25% of EU farmland in organic farming by 2030” is seen as a challenge, with many stakeholders questioning whether this ambition can be achieved. According to the data presented in Table 2, the lowest proportions of organic land in the EU are found in Romania (3.5%), Bulgaria (2.3%), Ireland (1.7%) and Malta (0.6%).

1.3. The Population of Romania

Romania has an area of 238,369 km² and a population recorded in 2020 of 19,281,118 inhabitants, representing approximately 4.3% of the EU-27 population [9].

Rural areas have substantial sources of development, representing 87% of the national territory, and the rural population in 2020 was 8.9 million, approximately 46.4% of the Romanian population.

The rural population decreased (measured in number of inhabitants) by 4.3% due to negative changes in the main demographic indicators: population ageing, declining birth rate and migration of the labour force, especially young people, from villages to cities and especially abroad. It is predicted that some countries in Europe will lose more than 15% of their population by 2050 due to international migration, Romania being one of these countries [10,11].

1.4. Policies and Strategies

The 2030 Agenda includes global objectives to guide the actions of international communities until 2030, and is relevant for both developed and developing countries. The transition to sustainable food production and agriculture will require major improvements in resource efficiency, environmental protection and system resilience [12].

Increasing the share of organic agriculture in the EU is part of the Action Plan for the development of organic production, with the objective of having “at least 25% of the EU’s agricultural land in organic agriculture and a significant increase in organic aquaculture by 2030”, contained within the From Farm to Consumer Strategy [13,14].

Organic agriculture is one of the many approaches and paradigms found to fulfil the objectives of sustainable development of agriculture [15,16].

According to IFOAM EU, reaching 25% of organic agricultural land area in the EU by 2030 is achievable if the CAP provides the necessary remuneration for the benefits of ecological conversion and maintenance through existing rural development policies or innovative instruments such as ecological schemes [17].

1.5. The Purpose and Hypothesis of the Research

In view of the above, the aim of this paper is to determine how organic farming can be developed sustainably, i.e., to determine the size of the areas that can be converted to organic farming so that, on the one hand, the share specified by EU strategies is achieved and, on the other hand, low yields do not affect food security and thus sustainable development objectives.

Based on the information, data and literature, the research hypothesis can be concretized. We believe that in Romania, the ecological agricultural system can be developed, given that the loss of yield can be balanced or cushioned by the fact that the population is decreasing, so there is a possibility that the agricultural area per capita can increase.

In relation to the share of organic farming in the total agricultural area and its expansion, we believe that large areas of grassland and meadows can be converted, as they contribute essentially to this objective.

2. Literature Review

Studies reveal a multitude of approaches regarding sustainability and ecological agriculture. The dynamics of organic agriculture certification in Romania was studied, starting from the hypothesis that the slow pace of certifications is due to some subjective barriers that can be eliminated if incentive measures are applied to support certification [18].

Regarding the EU Action Plan for organic agriculture, axis 1, stimulating and ensuring consumer confidence in the context of the sustainability and competitiveness of organic farms [19], proposes the implementation of ecological marketing strategies that would stimulate both consumption and production, thus contributing to sustainability and business development.

Another research study [20] addressed the issue of the limiting factors on the development of the organic food sector. The study used the qualitative analysis method with semi-structured interviews applied to 10 large and medium-sized companies active in the ecological sector. The limiting factors indicated by the managers refer not only to the legislation, the lack of constant supply of organic raw materials and increased competition on the domestic and international markets, but also to the instability of the financial situation, regarding financial liquidity, costs, capital and credits [20].

Rasche and Steinhauser [21], investigated how an increase agricultural area would affect yield differences between conventional and organic systems. Through the accounting tool FABLE, they evaluated the changes in consumption of available calories per person-year/day and the extent of cultivated lands, pastures and areas where natural processes predominate, until the year 2050. It was concluded that by increasing the ecological surface, there will be a caloric deficit of 7–80 kcal/person/day, corresponding to a surface of 1000–5000 km² of land cultivated. It was also estimated that the deficit would disappear without any changes to the system by 2045 due to demographic and technological development, and that would be no need for additional cultivated land at all if crop productivity were to increase.

Eneizen [22], used exploratory qualitative analysis combined with empirical research results to determine the main obstacles that must be solved for the expansion of ecological agriculture. The findings of the study, based upon interviews with organic farmers, suggest that obstacles to adoption of organic farming are: the absence of an organization to certify organic products, high cost of certification, lack of financing sources, low yield, high price, lack of specific markets for organic food, the low awareness of farmers, unsuccessful agricultural reforms, and lack of coordination between interested parties and institutional changes. The authors recommend that organic farming be carried out by qualified farmers using modern organic farming techniques that can contribute to increasing production yields and cost efficiency. The authors also recommend improving communication between the interested parties of organic agriculture, from farms to markets, including any relevant intergovernmental departments, to develop organic agriculture.

To answer the question of what the contribution of ecological agriculture to the sustainable development of agriculture is, Kilker [23] refers to the trilogy of sustainability, socio-economic and environmental development, which would help producers and exporters to improve their incomes and living conditions, especially in poorer countries. From an economic and social point of view, organic farming reduces the risk of production failure, stabilises profits and improves the quality of life of small farmers’ families, while from an ecological point of view, it improves soil fertility and preserves biodiversity, leading to ecosystem stability, reduced susceptibility to drought and pest attack. These benefits appear if production methods adapted to local conditions are applied, synthetic chemical pesticides and fertilizers are avoided, and crop diversity is maximized [24].

In another case study, organic farming is seen as a multi-functional business through which sustainable profits can be obtained, creating economic opportunities for people which can help society develop in a sustainable manner. The research was based on visits to organic farms and organic markets, as well as interviews with farmers. This was a model for the local community and for wider communities, thus contributing to the fulfilment of some among the objectives of sustainable development [25].

Sher [26] investigated the barriers to adopting green entrepreneurial agriculture to obtain economic growth through the minimal use of resources. Of the 34 barriers identified, 20 were considered critical barriers. Based on factor analysis, the 20 barriers were grouped into six major categories: training and development, entrepreneurial orientation, market orientation, customer orientation, innovation orientation, and barriers related to the provision of ecological support. The dominant barrier was training and development, as well as the marginal role of the government in carrying out such efforts.

For Romania, organic farming can become a technological alternative to conventional agriculture, as land conversion is within the reach of managers, and this opportunity is further enhanced by the high level of land fragmentation and the high number of small farms in agriculture [27,28].

3. Materials and Methods

The focus of this study was to determine the areas cultivated in an ecological system for each crop in Romania in order to reach the threshold imposed by the European Union regulations, regarding the share of organic agriculture in the total agricultural area of 25%. It is desired that development of ecological agriculture results in as little damage as possible in terms of yield and productivity; thus, a sustainable expansion of this farming system is desired.

For this purpose, data taken from European databases (Eurostat) on areas, production, and crop yields in Romania, both for organic and conventional agriculture, were analysed quantitatively and qualitatively in order to determine yield differences.

For the expansion of organic farming to be sustainable, the agricultural area per capita, especially its dynamics, was determined and forecasted for the year 2030, when each Member State must contribute to 25% of the agricultural area being farmed organically. This will compare the potential increase in agricultural area per capita (given the demographic decline in Romania) with the reduction in yields on the organic area (the 25%), so that the reduction in productivity is less than or equal to the increase in area per capita.

The forecast agricultural area per capita will be determined by relating the agricultural area to the population forecast by FAOSTAT, which is forecast using the average annual rate method, this indicator having the following formula [29]:

$$\overline{R}=\left(\overline{I}-1\right)\times 100$$

and

$$\overline{I}=\sqrt[n-1]{\prod I_{t/t-1}}$$

where: $\overline{R}$—average rate; $\overline{I}$—average index; I—individual levels of chain-based indices.

Linear programming and the Simplex method were used to determine an optimum yield (tending towards the minimum point), with certain conditions that satisfy both the requirements of European Union regulations and the soil and crop structure specific to Romania.

Programming problems involve the efficient use or allocation of limited resources to achieve desired goals. These problems are characterized by many solutions that satisfy the basic conditions of each problem. Choosing a specific solution as the best solution to a problem depends on the goals or overall objectives contained in the problem statement. The solution that satisfies both the problem conditions and the given objective is called the optimal solution [30].

Linear programming is an important cornerstone of optimization theory. Many real-world problems can be formulated with linear mathematical models. The simplex algorithm is the most used tool for solving linear programming [31].

Maximum efficiency means minimizing effort and maximizing output, and the concept of optimal is defined as a program that minimizes or maximizes an objective function while satisfying all techno-economic constraints.

Assuming that each component of the line vector “c” measures the efficiency of one unit of the output of an activity, then the linear function can be introduced [32]:

$$f_{\left(X\right)}=c_1\times X_1+c_2\times X_2+c_3\times X_3+\dots +c_n\times X_n$$

Summarizing, we obtain the following linear programming equations:

$$\left\{\begin{array}{c}optimum \left[f_{\left(X\right)}\right] \left(A\right)\\ \sum _{j=1}^n{a}_{ij}\times x_j\le b_i \left(B\right)\\ \sum _{j=1}^n{a}_{kj}\times x_j\le b_k \left(C\right)\\ x_j\ge 0 \left(D\right)\\ j=1,n\end{array}\right\}$$

Relations A–D together constitute the general model of a linear programming problem, each having a specific role: Relation (A) is called the efficiency objective function of the problem, relation B represents resource constraints, and relation C refers to techno-economic constraints.

Constructing the model of the linear programming problem led to the following system of equations. The objective function was minimising yield losses, i.e., losses in organic production compared to conventional production:

$$f_{{\left(X\right)}_{\left(min\right)}}=\frac{{\sum }_{i=1}^n\Delta \%\overline{Q}\times X_i}{{\sum }_{i=1}^n{X}_i}$$

Xi—The variables taken into account (areas of organic crops cultivated in Romania);

$\Delta \%\overline{Q}$—Relative yield differences for each organic crop compared to the same crop in a conventional system.

For the objective function, it was desired that the weighted average of the yield differences be as small as possible, so each (relative) yield difference between organic and conventional farming for each variable (crop) was multiplied by the area cultivated relative to the total area cultivated organically.

This objective function was conditioned by a series of equations in order to make the expansion of areas sustainable and to be able to determine as correctly as possible the extent of organic crops. Together, the following equations form the system of conditions for the linear programming problem.

$$\left\{\begin{array}{c}\begin{array}{c}\frac{{\sum }_{i=1}^n{X}_i}{UUA}=0.25\\ \frac{{\sum }_{i=1}^n\Delta \%\overline{Q}\times X_i}{{\sum }_{i=1}^n{X}_i}\times 0.25 \le 4.91\%\\ X_i\ge X_{i2020}\\ \frac{X_i^{\prime }}{UAA}\le 0.25\\ {(}^{\prime }for X_i with \Delta \%\overline{Q}>0)\end{array}\end{array}\right\}$$

The first condition in the previous system of equations refers to the main target of the European Union strategy, i.e., that the share of organic crops should reach 25%, so that the sum of the organic areas to be established for the year 2030, in relation to the utilised agricultural area (the projected one) should reach 25%.

The second condition is the one that provides a sustainable direction for this expansion of organic areas, i.e., the relative yield gap between organic and conventional agriculture for the 25% of the agricultural area to be less than or equal to 4.91%, which is the potential degree by which the agricultural area per inhabitant will increase by 2030, given that Romania’s population is decreasing faster than the agricultural area.

The third equation requires that the organic areas should start from the year 2020, i.e., the last year for which data have been recorded in European statistics, and the last equation requires that the areas of organic crops with positive differences in rankings should not exceed 25%, i.e., the average increase in areas in order to avoid situations in which the development of organic farming is based on 2–3 crops, which currently have very low proportions.

Therefore, the research stages to be presented will start with the determination and forecast of the dynamics of the agricultural area per inhabitant, so that on the basis of the expected increase in the indicator, it will be possible to determine the percentage that Romania can assume in terms of productivity losses on the 25% of the organic areas. Subsequently, the data on yield loss for each crop will be entered into the linear programming model and these conditions related to the proportion of area and the correlation of losses with agricultural area per capita will be introduced in order to determine the exact size of the ecological area for each crop analysed.

4. Results

To identify the areas that should be extended for each organic crop in Romania to reach the threshold of 25% of the agricultural area, we started with a quantitative analysis of statistical data on both organic and conventional agriculture.

It can be assumed that organic farming is in its infancy, even if there are data as early as 2012, or perhaps organic farming existed in practice before this period, but this statement is based on the proportion of organic areas in the total utilised agricultural area, as shown in

Table 3. Dynamics of total area under organic farming in Romania, hectares.

Time	2012	2013	2014	2015	2016	2017	2018	2019	2020
UAA Eco	103,093	138,125	190,430	175,571	149,613	149,106	171,594	211,487	275,965
%	0.75%	0.99%	1.38%	1.27%	1.11%	1.11%	1.28%	1.53%	2.11%

Source: processing based on Eurostat data.

.

The area cultivated organically in Romania increased from 103 thousand hectares in 2012 to approximately 276 thousand hectares in 2020, which represents an increase of 168%. We also observed an average annual growth of 13.1% during the period analysed. However, it can be seen that the expansion of the organic land area has not been constant and strictly increasing; there is a decrease in the middle of the period, with 2016 and 2017 recording slightly smaller areas. These years coincided with the interval between the two programming periods of the Common Agricultural Policy. The subsidies and funds for agriculture were lower in this period. The standard deviation was approximately 50 thousand hectares, a variation of ±28%.

Table 3 shows the proportion of organic area in the total agricultural area in Romania, which increased from 0.75% to 2.11%. However, as mentioned above, this proportion is low compared to other EU countries, so the development of organic farming up to 25% of the agricultural area will be a challenge.

In order for this development to be sustainable, without economic (drastic reduction in yields), social (transition to food insecurity) and environmental (high resource consumption) implications, it is hoped that there is a possible situation in which the difference in yield and decrease in productivity for that 25% of the agricultural area is covered by the increase in agricultural area per capita, given the demographic decline in Romania.

This will determine the agricultural area per inhabitant by 2030, the deadline for meeting the EU biodiversity strategy target.

From Figure 1 it can be seen that utilised agricultural area and population are both decreasing, but by analysing the trend equation of the two indicators, we found that population is decreasing faster than the utilised agricultural area. Over the period 2012–2020, the utilised agricultural area decreased from 13.73 million hectares to approximately 13.05 million hectares, representing a decrease of 4.95% and an average annual rate of change of −0.64%.

Based on the average annual rate of change in utilised agricultural area, as well as FAOSTAT population forecasts, which estimate that the population will reach 18.3 million in 2030, it was possible to determine and forecast the agricultural area per capita and the dynamics of this indicator.

In regard to the period 2012–2020, for which precise data have been recorded for both utilised agricultural area and population, there were no increases as perhaps expected, given the steady decrease in population, because the utilised agricultural area has also fluctuated with both negative and positive variations. The utilised agricultural area per capita ranged from 0.68 hectares per capita to 0.71 hectares per capita, with an average of 0.69 hectares per capita over the period and a standard deviation of 0.01 hectares per capita from this average, giving a variation of ±1.6%. (Figure 2).

Forecasting this indicator on the basis of the utilised agricultural area determined on the basis of the average annual rate of change and on the basis of the population according to the FAO forecast, it is estimated that the agricultural area per capita will follow an increasing trend until 2030, reaching a level of 0.71 hectares per capita.

In order to determine the degree of sustainability in terms of yield reduction for organic farming, the dynamics of the agricultural area per capita was determined, i.e., the relative difference between the target year (2030) and the last year with exact data, i.e., 2020, the agricultural area per capita will be expected to increase by 4.91%, which allows for a slight decrease in agricultural productivity given the characteristics of the organic farming system.

Next, the areas and yields for all crops recorded in the Eurostat databases, both for organic and conventional farming, were researched in order to finally determine the yield differences, which are essential in the second part of the work on minimizing the decrease in agricultural productivity in organic versus conventional farming, depending on the areas of the crops studied. The determination of the yields for the two cropping systems in agriculture and their levels can be seen in

Table A1. Conventional crop yield (t/ha).

Conventional Yield	2012	2013	2014	2015	2016	2017	2018	2019	2020
Apples	8.195	8.344	8.951	8.330	8.228	6.107	11.768	9.342	10.269
Apricots	11.128	9.511	14.191	11.340	13.395	15.469	17.477	14.422	13.187
Aromatic, medicinal and culinary plants	0.741	0.936	1.319	1.318	1.280	1.279	1.213	1.114	1.159
Barley	2.325	3.111	3.319	3.461	3.773	4.186	4.417	4.188	2.582
Berries (excluding strawberries)	1.105	1.382	1.149	1.239	1.155	1.436	1.915	2.414	2.365
Brassicas	19.739	18.604	23.178	21.386	21.371	22.640	23.331	20.543	27.218
Cereals (excluding rice) for the production of grain (including seed)	2.352	3.853	4.055	3.532	3.963	5.224	5.998	5.458	3.398
Cereals for the production of grain (including seed)	2.357	3.854	4.054	3.534	3.964	5.224	5.997	5.458	3.399
Cherries	9.946	10.927	12.360	11.468	11.535	9.218	12.333	12.061	11.971
Citrus fruits	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Common wheat and spelt	2.653	3.469	3.587	3.781	3.945	4.890	4.796	4.754	2.967
Cotton seed	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Cultivated mushrooms	465.500	439.500	488.000	1096.000	726.000	758.500	172.333	173.375	716.000
Dry pulses and protein crops for the production of grain (including seed and mixtures of cereals and pulses)	1.139	1.377	1.427	1.394	1.646	2.510	1.426	2.023	1.124
Durum wheat	2.476	3.000	4.889	2.845	3.511	4.305	3.687	2.885	2.501
Fibre crops	0.667	0.467	5.921	4.300	5.435	1.544	1.870	2.210	2.488
Fresh pulses	3.251	4.160	4.090	4.173	4.008	4.104	4.339	3.949	5.209
Fresh vegetables (including melons)	14.523	16.336	17.659	16.546	16.091	17.835	18.632	16.632	20.379
Fresh vegetables (including melons) and strawberries	14.420	16.244	17.525	16.410	15.946	17.617	18.389	16.413	19.998
Fruits from subtropical and tropical climate zones	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Fruits, berries and nuts (excluding citrus fruits, grapes and strawberries)	7.602	8.418	8.827	8.428	8.593	7.176	12.726	10.556	11.233
Grain maize and corn-cob-mix	2.180	4.488	4.770	3.459	4.158	5.956	7.637	6.500	3.974
Grapes	4.205	5.586	4.465	4.514	4.209	6.065	6.601	5.523	5.633
Hops	0.739	0.708	1.125	0.957	0.808	0.522	0.846	0.880	0.840
Industrial crops	1.320	2.072	2.307	0.000	0.000	0.000	0.000	0.000	0.000
Leafy and stalked vegetables (excluding brassicas)	9.442	11.064	12.208	12.674	13.522	14.395	15.372	10.197	8.945
Linseed (flax)	1.203	1.332	1.567	1.670	1.646	1.676	1.538	2.013	1.199
Nectarines	6.750	5.909	7.417	7.333	6.083	5.000	5.571	5.250	6.143
Nuts	18.025	18.110	14.711	15.191	13.910	19.034	23.827	19.857	19.004
Oats and spring cereal mixtures (mixed grain other than maslin)	1.743	2.051	2.124	1.999	2.239	2.460	2.376	2.243	1.941
Oilseeds	1.322	2.079	2.312	1.964	2.207	2.823	2.835	2.662	1.923
Olives	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Other fresh vegetables n.e.c.	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Other oilseed crops n.e.c.	0.667	0.896	0.920	0.870	1.144	1.234	0.841	0.816	0.680
Other permanent crops for human consumption n.e.c.	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Other pome fruits n.e.c.	14.603	13.855	17.736	17.000	16.817	21.209	25.630	22.890	22.339
Other root crops n.e.c.	22.502	28.457	29.766	30.625	25.268	28.250	28.272	23.879	21.878
Other stone fruits n.e.c	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Peaches	8.426	9.321	13.893	12.355	13.357	11.204	13.262	9.994	9.549
Pears	13.267	16.379	16.910	14.643	15.810	14.756	18.439	14.987	15.094
Permanent crops for human consumption	5.722	6.876	6.416	6.240	6.148	6.558	9.319	7.712	8.165
Plants harvested green from arable land	5.906	6.713	6.995	6.423	5.847	6.371	7.029	6.201	5.553
Plums	6.031	7.367	7.278	7.397	7.713	6.515	12.594	10.562	11.310
Pome fruits	8.686	8.960	9.610	8.819	8.808	6.906	12.425	9.946	10.802
Potatoes (including seed potatoes)	10.752	15.846	17.365	13.769	14.442	18.186	17.442	15.086	15.849
Rape and turnip rape seeds	1.496	2.408	2.604	2.499	2.835	2.798	2.546	2.264	2.150
Rice	4.450	4.528	3.509	4.428	4.569	4.689	5.195	5.320	4.112
Root crops	12.968	18.913	21.516	17.606	17.989	21.834	20.495	18.305	19.181
Root, tuber and bulb vegetables	10.156	12.314	13.301	11.552	10.767	11.873	12.012	11.365	12.884
Rye and winter cereal mixtures (maslin)	2.104	2.217	2.395	2.533	2.479	2.936	2.791	2.797	2.532
Soya	1.384	2.344	2.687	2.164	2.190	2.521	2.908	2.783	2.018
Stone fruits	6.584	7.804	8.107	7.978	8.314	7.070	12.705	10.772	11.370
Strawberries	6.771	9.784	9.079	8.398	8.434	8.305	7.976	6.855	6.979
Sugar beet (excluding seed)	26.366	36.575	44.711	39.129	40.618	41.649	38.035	40.350	33.684
Sunflower seed	1.310	1.993	2.187	1.765	1.955	2.917	3.041	2.783	1.858
Tobacco	1.063	1.447	1.640	1.440	1.785	1.525	1.370	1.344	1.307
Vegetables cultivated for fruit (including melons)	15.519	18.196	18.769	18.049	17.560	20.083	21.105	18.784	23.987
Wheat and spelt	2.652	3.468	3.590	3.780	3.944	4.888	4.793	4.749	2.966

Source: authors’ calculations.

and

Table A2. Organic crop yield (t/ha).

Organic Yield	2012	2013	2014	2015	2016	2017	2018	2019	2020
Apples	4.497	4.502	5.333	2.450	4.863	5.219	5.002	6.774	3.079
Apricots	x	2.385	0.143	2.125	1.635	2.733	0.188	0.788	0.403
Aromatic, medicinal and culinary plants	x	0.650	1.396	1.160	2.237	1.311	0.906	1.051	0.919
Barley	1.582	2.000	3.207	2.928	3.444	3.488	2.288	2.438	2.173
Berries (excluding strawberries)	x	1.117	7.074	1.754	9.157	1.233	1.430	3.401	3.096
Brassicas	x	14.231	8.222	1.256	6.051	0.265	11.500	12.000	6.571
Cereals (excluding rice) for the production of grain (including seed)	x	2.525	4.152	4.291	3.915	4.348	3.696	3.723	2.350
Cereals for the production of grain (including seed)	x	2.546	4.204	4.339	3.884	4.366	3.713	3.750	2.388
Cherries	x	2.750	1.805	1.743	3.438	5.456	1.688	1.796	0.869
Citrus fruits	x	x	x	x	x	x	x	x	x
Common wheat and spelt	x	x	4.065	4.032	3.933	4.019	3.278	3.439	2.085
Cotton seed	x	x	1.500	x	x	x	x	x	x
Cultivated mushrooms	x	x	x	x	x	x	x	x	x
Dry pulses and protein crops for the production of grain (including seed and mixtures of cereals and pulses)	x	1.100	1.999	1.605	1.272	2.497	1.408	2.055	1.089
Durum wheat	x	x	2.968	2.970	2.744	2.453	1.852	4.081	1.973
Fibre crops	x	x	1.836	0.079	8.000	2.000	2.054	1.947	0.214
Fresh pulses	x	3.413	0.511	1.711	2.085	0.734	1.228	6.261	7.792
Fresh vegetables (including melons)	x	x	1.664	5.244	4.141	2.780	2.903	4.570	6.785
Fresh vegetables (including melons) and strawberries	x	x	1.675	5.225	4.128	2.865	2.898	4.488	6.761
Fruits from subtropical and tropical climate zones	x	x	x	x	x	x	x	x	x
Fruits from temperate climate zones	x	3.959	4.219	1.646	2.781	3.147	2.855	3.838	2.280
Fruits, berries and nuts (excluding citrus fruits, grapes and strawberries)	x	x	4.247	1.540	3.213	2.587	2.239	3.091	1.889
Grain maize and corn-cob-mix	2.587	3.100	5.352	5.743	4.930	6.004	5.917	5.100	3.040
Grapes	3.497	3.900	2.664	4.931	1.724	4.644	9.982	4.577	3.523
Hops	x		1.613	1.000	2.000
Industrial crops	x	1.477	2.351	2.203	2.283	2.140	2.054	1.875	1.806
Leafy and stalked vegetables (excluding brassicas)	x	6.429	5.222	1.000	4.857	5.195	1.333	9.500	2.857
Linseed (flax)	x		1.569	1.460	2.200	1.758	1.430	1.513	1.226
Nectarines	x	x	x	x	x	x	x	x	x
Nuts	x	1.895	0.646	0.282	0.514	0.174	0.630	0.288	0.321
Oats and spring cereal mixtures (mixed grain other than maslin)	2.980	1.500	2.239	4.016	2.674	1.714	1.742	2.241	1.367
Oilseeds	x	1.500	2.383	2.251	2.283	2.167	2.080	1.886	1.820
Olives	x	x	x	x	x	x	x	x	x
Other cereals (including triticale and sorghum)	3.199	1.557	2.484	1.575	0.978	2.383	1.814	1.183	1.562
Other fresh vegetables n.e.c.	x	x	0.910	21.610	3.262	3.695	1.937	1.283	5.778
Other industrial crops including energy crops n.e.c.	x	x	0.000	3.800	0.000	1.346	1.503	0.000	0.000
Other oilseed crops n.e.c.	x	x	1.455	0.765	1.112	0.500	0.258	0.941	1.161
Other permanent crops for human consumption n.e.c.	x	x	0.000	0.838	0.000	0.353	0.862	0.040	0.064
Other pome fruits n.e.c.	x	x	0.000	0.781	1.117	1.663	1.144	2.190	2.567
Other root crops n.e.c.		9.250	9.667	6.000	4.000	7.250	8.000	7.000	1.000
Other stone fruits n.e.c	x	x	3.409	2.000	8.607	5.988	1.522	1.158	1.774
Peaches	x	7.600	5.933	9.063	4.000	4.267	1.833	3.833	1.563
Pears	x	4.147	2.263	1.500	3.557	3.400	1.000	2.406	2.672
Permanent crops for human consumption	x	x	3.773	2.257	2.797	3.050	3.717	3.356	2.140
Plants harvested green from arable land	x	x	4.282	4.652	5.566	5.148	4.570	5.181	4.001
Plums	x	3.076	2.926	1.067	1.530	1.672	1.396	1.356	1.758
Pome fruits	x		5.019	2.008	3.654	4.312	4.627	6.469	3.021
Potatoes (including seed potatoes)	x	8.982	11.640	7.481	9.038	7.675	4.952	6.415	9.952
Rape and turnip rape seeds	x	x	2.384	2.548	2.528	2.273	2.117	2.191	1.719
Rice	3.501	3.199	5.829	5.254	3.383	4.701	4.234	4.923	4.916
Root crops	x	10.670	17.338	15.753	18.400	12.328	11.716	16.185	23.275
Root, tuber and bulb vegetables	x	9.160	2.229	7.821	4.917	2.287	4.273	5.706	6.248
Rye and winter cereal mixtures (maslin)	3.000	1.757	1.935	2.444	2.387	1.577	1.272	2.121	2.504
Soya	x	x	2.713	2.220	2.047	2.081	2.027	1.892	1.737
Stone fruits	x	x	2.907	1.230	1.837	2.063	1.378	1.370	1.600
Strawberries	x	x	5.000	3.833	3.444	12.500	2.500	2.611	6.150
Sugar beet (excluding seed)	x	20.200	40.743	28.431	25.684	14.336	14.026	18.216	39.638
Sunflower seed	x	x	2.348	2.192	2.353	2.230	2.184	1.869	1.900
Tobacco	x	0.966	x	x	x	x	x	x	x
Vegetables cultivated for fruit (including melons)	x	11.090	9.206	5.709	7.142	6.225	4.805	4.874	7.494
Wheat and spelt	2.586	2.400	4.035	4.001	3.869	3.991	3.250	3.441	2.082

Source: authors’ calculations, x—no data available.

.

Table 4. Determination of yield differences for each organic crop in Romania compared to the yield in the conventional system (%).

Relative Differences [Eco–Conv (%)]	2012	2013	2014	2015	2016	2017	2018	2019	2020	Average
Apples	−45.13	–46.05	–40.42	–70.59	–40.89	–14.55	–57.50	–27.49	–70.02	–45.85
Apricots	x	–74.93	–98.99	–81.26	–87.80	–82.33	–98.92	–94.53	–96.94	–89.46
Aromatic, medicinal and culinary plants	x	–30.62	5.84	–12.01	74.84	2.47	–25.37	–5.72	–20.74	–1.41
Barley	–31.95	–35.72	–3.38	–15.39	–8.72	–16.67	–48.21	–41.78	–15.82	–24.18
Berries (excluding strawberries)	x	–19.17	515.72	41.55	692.70	–14.13	–25.32	40.91	30.93	157.90
Brassicas	x	–23.51	–64.53	–94.13	–71.68	–98.83	–50.71	–41.59	–75.86	–65.10
Cereals (excluding rice) for the production of grain (including seed)	x	–34.47	2.38	21.49	–1.21	–16.78	–38.38	–31.78	–30.84	–16.20
Cereals for the production of grain (including seed)	x	–33.94	3.69	22.79	–2.02	–16.43	–38.09	–31.28	–29.74	–15.63
Cherries	x	–74.83	–85.40	–84.80	–70.20	–40.81	–86.32	–85.11	–92.74	–77.53
Common wheat and spelt	x		13.31	6.64	–0.30	–17.80	–31.66	–27.66	–29.71	–12.46
Dry pulses and protein crops for the production of grain (including seed and mixtures of cereals and pulses)	x	–20.09	40.10	15.10	–22.74	–0.51	–1.25	1.59	–3.14	1.13
Durum wheat	x	x	–39.29	4.38	–21.84	–43.04	–49.78	41.48	–21.10	–18.45
Fibre crops	x	x	–68.99	–98.17	47.20	29.50	9.83	–11.88	–91.41	–26.27
Fresh pulses	x	–17.97	–87.51	–58.99	–47.98	–82.12	–71.71	58.55	49.57	–32.27
Fresh vegetables (including melons)	x	x	–90.58	–68.31	–74.27	–84.41	–84.42	–72.52	–66.71	–77.32
Fresh vegetables (including melons) and strawberries	x	x	–90.44	–68.16	–74.11	–83.74	–84.24	–72.65	–66.19	–77.08
Fruits, berries and nuts (excluding citrus fruits, grapes and strawberries)	x	x	–51.88	–81.73	–62.61	–63.95	–82.40	–70.72	–83.18	–70.92
Grain maize and corn–cob–mix	18.70	–30.93	12.22	66.02	18.56	0.81	–22.52	–21.54	–23.51	1.98
Grapes	–16.83	–30.19	–40.35	9.24	–59.03	–23.43	51.24	–17.14	–37.46	–18.22
Hops	x	x	43.37	4.55	147.62	x	x	x	x	65.18
Industrial crops	x	–28.73	1.91	x	x	x	x	x	x	–13.41
Leafy and stalked vegetables (excluding brassicas)	x	–41.90	–57.22	–92.11	–64.08	–63.91	–91.33	–6.83	–68.06	–60.68
Linseed (flax)	x	x	0.14	–12.56	33.68	4.89	–7.03	–24.83	2.28	–0.49
Nuts	x	–89.54	–95.61	–98.14	–96.30	–99.09	–97.36	–98.55	–98.31	–96.61
Oats and spring cereal mixtures (mixed grain other than maslin)	71.03	–26.85	5.42	100.94	19.45	–30.34	–26.71	–0.09	–29.57	9.26
Oilseeds	x	–27.85	3.07	14.57	3.45	–23.22	–26.64	–29.16	–5.37	–11.39
Other oilseed crops n.e.c.	x	x	58.17	–12.06	–2.77	–59.48	–69.35	15.33	70.71	0.08
Other pome fruits n.e.c.	x	x	x	–95.41	–93.36	–92.16	–95.54	–90.43	–88.51	–92.57
Other root crops n.e.c.	x	–67.49	–67.52	–80.41	–84.17	–74.34	–71.70	–70.69	–95.43	–76.47
Peaches	x	–18.47	–57.29	–26.65	–70.05	–61.92	–86.18	–61.64	–83.64	–58.23
Pears	x	–74.68	–86.62	–89.76	–77.50	–76.96	–94.58	–83.94	–82.29	–83.29
Permanent crops for human consumption	x	x	–41.20	–63.83	–54.51	–53.49	–60.12	–56.48	–73.79	–57.63
Plants harvested green from arable land	x	x	–38.79	–27.58	–4.81	–19.20	–34.98	–16.45	–27.94	–24.25
Plums	x	–58.25	–59.80	–85.58	–80.16	–74.34	–88.92	–87.16	–84.46	–77.33
Pome fruits	x	x	–47.77	–77.23	–58.52	–37.55	–62.76	–34.96	–72.03	–55.83
Potatoes (including seed potatoes)	x	–43.32	–32.97	–45.67	–37.42	–57.79	–71.61	–57.48	–37.21	–47.93
Rape and turnip rape seeds	x	x	–8.46	1.93	–10.83	–18.78	–16.87	–3.20	–20.06	–10.90
Rice	–21.33	–29.35	66.10	18.64	–25.96	0.26	–18.50	–7.46	19.56	0.22
Root crops	x	–43.58	–19.42	–10.53	2.28	–43.54	–42.84	–11.58	21.34	–18.48
Root, tuber and bulb vegetables	x	–25.61	–83.24	–32.29	–54.34	–80.74	–64.43	–49.79	–51.51	–55.24
Rye and winter cereal mixtures (maslin)	42.60	–20.74	–19.21	–3.51	–3.72	–46.30	–54.44	–24.18	–1.13	–14.51
Soya	x	x	0.99	2.58	–6.52	–17.45	–30.30	–32.02	–13.92	–13.80
Stone fruits	x	x	–64.14	–84.58	–77.91	–70.82	–89.15	–87.28	–85.93	–79.97
Strawberries	x	x	–44.93	–54.36	–59.16	50.52	–68.65	–61.91	–11.88	–35.77
Sugar beet (excluding seed)	x	–44.77	–8.87	–27.34	–36.77	–65.58	–63.12	–54.86	17.68	–35.45
Sunflower seed	x	x	7.36	24.18	20.39	–23.55	–28.18	–32.83	2.27	–4.34
Tobacco	x	–33.27	x	x	x	x	x	x	x	–33.27
Vegetables cultivated for fruit (including melons)	x	–39.05	–50.95	–68.37	–59.33	–69.00	–77.23	–74.05	–68.76	–63.34
Wheat and spelt	–2.47	–30.79	12.41	5.85	–1.89	–18.35	–32.20	–27.54	–29.80	–13.87

Source: authors’ calculations, x—no data available.

presents the percent yield differences for each crop in Romania grown organically, according to the Eurostat data, compared to conventional yields, for the period 2012–2020, where data were available. Analysing the average percent differences across years, there are organic crops for which yields are higher than in the conventional system. These crops include berries (excluding strawberries), whose yield in organic system was 158% higher; a second crop is hops, but the average was determined over a short period of time, so there is a larger margin of error. The average yield of organic hops is 65% higher. Oats and spring cereal mixtures had yields in organic system higher by 9.26%. While all these crops were higher yielding in organic systems, their area share was not very high. The situation is different for grain maize and corn-cob-mix, which is only 2% higher yielding in organic systems, but the area cultivated is about 19% of the total organic area, being the largest single crop.

However, for the most part, organic crop yields are lower than conventional yields; among the closest but still lower yields are sunflower (−4.34%), oilseed rape (−10.9%) and common wheat (−12.46%). At the other end of the scale, there are crops whose organic yields are much lower, more than half, especially for fruit and vegetables, where organic yields are more than 70% lower than conventional ones.

On average, for all the organic crops analysed, there was a yield gap of 32% against organic compared to conventional farming. However, it should be noted that this is a simple arithmetic average; without considering the share of cultivated areas, by taking this average weighted by the areas of the main crops, the yield in organic farming was about 10% lower than in conventional farms, so, as is natural, farmers turned to crops with potential to risk as little as possible and eliminate losses. However, given that Romania must expand its organic farming area, farmers will no longer be able to focus on certain crops, and expansion will most likely widen the gap between weighted yields.

At the same time, in addition to determining the yield differences, which will represent the coefficients of each variable of the linear programming function, the weight of each crop will also be used (Figure 3), given that, until now, there are areas cultivated in an organic system, these will have to be extended from now on, so the values of the variables will have to be higher than or at least equal to those at present.

As mentioned above, the area under organic maize has a significant share, but this crop is in first place, with a share of 19% of the total area under organic cultivation, followed by wheat and spelt, with 15.7%, then sunflower with 8.1%, followed by plants harvested green from arable land with 6.5%, barley with 3.4%, rapeseed with 3%, and then hops with only 0.002%.

Therefore, having created this context with which we can realize and determine the areas that should be cultivated in 2030 in order to reach the European Union target, we constructed a linear programming model that led to the following system of equations.

The variables considered and the main coefficients of the variables or equations are presented in

Table A3. Definition of variables and initial coefficients.

Crt. No.	Organic Farming (Area)	Variable	Relative Difference in Yield $(\Delta \%\overline{\mathit{Q}})$	Share of Ecological Area in UAA
1	Apples	X1	–45.85	0.408%
2	Apricots	X2	–89.46	0.016%
3	Aromatic, medicinal and culinary plants	X3	–1.41	0.023%
4	Barley	X4	–24.18	3.417%
5	Berries (excluding strawberries)	X5	157.90	0.004%
6	Brassicas	X6	–65.10	0.205%
7	Cherries	X7	–77.53	0.043%
8	Dry pulses and protein crops for the production of grain (including seed and mixtures of cereals and pulses)	X8	1.13	0.621%
9	Durum wheat	X9	–18.45	0.042%
10	Fresh pulses	X10	–32.27	0.051%
11	Fresh vegetables (including melons) and strawberries	X11	–77.08	0.972%
12	Grain maize and corn–cob–mix	X12	1.98	18.956%
13	Grapes	X13	–18.22	1.162%
14	Hops	X14	65.18	0.002%
15	Leafy and stalked vegetables (excluding brassicas)	X15	–60.68	0.003%
16	Linseed (flax)	X16	–0.49	0.017%
17	Nuts	X17	–96.61	0.015%
18	Oats and spring cereal mixtures (mixed grain other than maslin)	X18	9.26	1.112%
19	Other oilseed crops n.e.c.	X19	0.08	0.032%
20	Other pome fruits n.e.c.	X20	–92.57	0.009%
21	Other root crops n.e.c.	X21	–76.47	0.084%
22	Peaches	X22	–58.23	0.012%
23	Pears	X23	–83.29	0.024%
24	Permanent crops for human consumption	X24	–57.63	2.099%
25	Plants harvested green from arable land	X25	–24.25	6.484%
26	Plums	X26	–77.33	0.446%
27	Pome fruits	X27	–55.83	0.401%
28	Potatoes (including seed potatoes)	X28	–47.93	1.211%
29	Rape and turnip rape seeds	X29	–10.90	3.036%
30	Rice	X30	0.22	0.066%
31	Root, tuber and bulb vegetables	X31	–55.24	0.222%
32	Rye and winter cereal mixtures (maslin)	X32	–14.51	0.074%
33	Soya	X33	–13.80	0.964%
34	Stone fruits	X34	–79.97	0.517%
35	Strawberries	X35	–35.77	0.019%
36	Sugar beet (excluding seed)	X36	–35.45	0.185%
37	Sunflower seed	X37	–4.34	8.091%
38	Tobacco	X38	–33.27	0.006%
39	Vegetables cultivated for fruit (including melons)	X39	–63.34	0.472%
40	Wheat and spelt	X40	–13.87	15.659%

.

Table A3 shows the 40 variables, i.e., the 40 crops grown organically in Romania, for which data were available, with the related coefficients, i.e., the relative difference in yield between organic and conventional farming, and the share of each crop in the total agricultural area used. All these crops will be included in the Simplex method, and the change in each area for each crop will fulfil both the conditions presented above and the objective function.

Following the application of the simplex method, which led to the optimal solution that fulfils both the objective function (

Table 5. Solution of the objective function as a function of each variable.

Crt. No.	Crop	Variable	Values Xi (ha)	Proportion in Organic Area	Proportion in UAA
1	Apples	X1	7994.49	0.247%	0.06%
2	Apricots	X2	300.80	0.009%	0.00%
3	Aromatic, medicinal and culinary plants	X3	738.00	0.023%	0.01%
4	Barley	X4	363,833.67	11.225%	2.81%
5	Berries (excluding strawberries)	X5	1660.00	0.051%	0.01%
6	Brassicas	X6	14.45	0.000%	0.00%
7	Cherries	X7	315.30	0.010%	0.00%
8	Dry pulses and protein crops for the production of grain (including seed and mixtures of cereals and pulses)	X8	4173.00	0.129%	0.03%
9	Durum wheat	X9	1732.00	0.053%	0.01%
10	Fresh pulses	X10	24.27	0.001%	0.00%
11	Fresh vegetables (including melons) and strawberries	X11	1330.45	0.041%	0.01%
12	Grain maize and corn-cob-mix	X12	614,446.52	18.956%	4.74%
13	Grapes	X13	1867.00	0.058%	0.01%
14	Hops	X14	0.00	0.000%	0.00%
15	Leafy and stalked vegetables (excluding brassicas)	X15	7.10	0.000%	0.00%
16	Linseed (flax)	X16	1252.00	0.039%	0.01%
17	Nuts	X17	29,288.03	0.904%	0.23%
18	Oats and spring cereal mixtures (mixed grain other than maslin)	X18	1118.00	0.034%	0.01%
19	Other oilseed crops n.e.c.	X19	478.00	0.015%	0.00%
20	Other pome fruits n.e.c.	X20	299.34	0.009%	0.00%
21	Other root crops n.e.c.	X21	1.00	0.000%	0.00%
22	Peaches	X22	33.96	0.001%	0.00%
23	Pears	X23	160.58	0.005%	0.00%
24	Permanent crops for human consumption	X24	254,849.78	7.862%	1.97%
25	Plants harvested green from arable land	X25	1014,334.26	31.293%	7.82%
26	Plums	X26	17,385.66	0.536%	0.13%
27	Pome fruits	X27	13,371.47	0.413%	0.10%
28	Potatoes (including seed potatoes)	X28	92.26	0.003%	0.00%
29	Rape and turnip rape seeds	X29	98,396.75	3.036%	0.76%
30	Rice	X30	1424.00	0.044%	0.01%
31	Root, tuber and bulb vegetables	X31	135.36	0.004%	0.00%
32	Rye and winter cereal mixtures (maslin)	X32	127.00	0.004%	0.00%
33	Soya	X33	14,536.00	0.448%	0.11%
34	Stone fruits	X34	25,398.29	0.784%	0.20%
35	Strawberries	X35	20.27	0.001%	0.00%
36	Sugar beet (excluding seed)	X36	72.09	0.002%	0.00%
37	Sunflower seed	X37	262,274.88	8.091%	2.02%
38	Tobacco	X38	0.00	0.000%	0.00%
39	Vegetables cultivated for fruit (including melons)	X39	360.68	0.011%	0.00%
40	Wheat and spelt	X40	507,576.02	15.659%	3.91%
41	TOTAL		3241,422.74	100%	25%

Source: authors’ calculations.

), where productivity do not decrease very much, and the set of conditions imposed, the areas for the 40 organic crops were identified for which Romania would reach the share of 25% of the utilised agricultural area.

As can be seen from Table 5, the total organic area would need to be 3.241 million hectares to reach the 25% share. Of this total, the largest and most extensive crop share should be plants harvested green from arable land with 1.014 million hectares, which represents 31.29% of the organic area and 7.8% of the total utilised agricultural area.

Grain maize and corn-cob-mix is the second most important crop, with an area of 614.4 thousand hectares, i.e., a share of 4.7% of the utilised agricultural area. Wheat and spelt is in third place with an organic area of 507.5 thousand hectares, representing 3.9% of the utilised agricultural area.

According to the optimal solution, i.e., according to the values of the 40 variables, this results in an objective function value of −19.64%, i.e., the smallest difference in yield/productivity between organic and conventional farming according to the organic crop structure shown in Table 5 and Figure 4. With this organic crop structure, the first condition is met, i.e., the organic area is 25% of the utilised agricultural area; the second condition is also met at the limit, but it can be seen that this yield decrease of 19.64% applied to 25% of the agricultural area results in a fixed total decrease in agricultural production of 4.91%, which does not exceed the increase of agricultural area per capita, so we can consider that this extension of agricultural area can be considered as sustainable. The other conditions have also been met.

5. Discussion

The study was based on the premise that the share of agricultural land cultivated organically should reach 25% of the country’s agricultural land by 2030, and the aim of the study was to determine the amount of each crop that should be cultivated organically in order to reach this share with certain sustainability restrictions.

Given that the average yield of organic crops is just over 30% lower, this would negatively affect food security and sustainable development goals. Thus, in determining the size of the areas cultivated for each crop, it was decided to minimise productivity losses so that, applying these losses to the 25% of the area, the total loss of production would be less than or equal to the gain in agricultural area per inhabitant determined by the decrease in Romania’s population.

After identifying the optimal solution, when the crop structure and the size of the crop areas resulting in the smallest loss of productivity, which is about 20%, are applied to the 25% area, then a total loss of 5% of agricultural production results, which is recovered by increasing the agricultural area per capita.

Furthermore, following the identification of the optimal solution, it is observed that the hypothesis becomes true, namely that the main crop to be cultivated in the highest proportion will be the one related to green plants, thus leading us to the idea of cultivating and converting the cultivated areas to grassland and meadows.

The economic impact, not just the technical one, must also be discussed. Given the loss of yield and the high cost of inputs in organic farming, the final cost per unit of product will be higher, and this will be reflected in the market price. As the price of organic products is higher than conventional products, this means a higher value for organic products per unit of product, but this price aspect has not been taken into account, as this is the only technical condition of the European Union’s area ratio strategies. If the price of products, the value of production and the price difference between the two systems had been taken into account, the crop structure would probably have looked different, with uncertainty as to whether the main condition of area assurance would still be met. Unfortunately, however, this analysis could not be carried out due to the limitations of the static data, as there are no price data for organic products.

6. Conclusions

In this paper, the aim was to determine the ecological areas that should be cultivated in Romania by 2030, so that their share meets the targets of the European Union strategy for biodiversity, namely 25%. Although this share represents the EU average of organic crop area in the total agricultural land, this paper assumes that Romania should ensure this share in a sustainable way.

Given that organic crop yields are lower than conventional ones, in order to achieve sustainable growth, the agricultural area per capita in Romania was determined, so even if the dynamics of agricultural area and population are decreasing, the rate of population decline is faster, so the indicator of agricultural area per capita is expected to increase in the period 2020–2030, with a forecasted increase of up to 5%. This would therefore be considered as the upper limit of yield losses in organic farming for the 25% of the area.

In order to determine as accurately and optimally as possible the areas of organic crops to be sown, the average yields per hectare for the intersection of crops recorded in Romania between the two systems were analysed, thus determining the relative differences in productivity between the organic and conventional systems for each crop and the average relative difference, which was 32% against organic farming.

In addition, we mention the fulfilment of the proportion of 25% of the total agricultural area as organic cultivation, as well as the difference in yield for the section of 25% of the agricultural area as less than or equal to the growth rate of agricultural area per capita, so that sustainable growth of organic agriculture will be present in Romania.

It was concluded that the organic area would have to increase by 11.7 times, i.e., to reach a size of 3.24 million ha, to ensure the proportion recommended in the EU strategy. Solving the linear programming problem led to the determination of the size of the areas to be cultivated organically for each crop in order to fulfil the objective function of minimising yield loss. This gives the smallest yield loss in organic farming compared to conventional farming, 16.94%. At the same time, this yield decrease, applied to 25% of the agricultural area, leads to a loss of up to 5% of production, which is sustainably covered by the increase in agricultural area per capita due to the decrease in population.