A Review of Industrial Crop Yield Performances on Unfavorable Soil Types

Industrial crop cultivation on marginal agricultural land limits indirect land-use change effects that pose a threat to food security. This review compiles results from 91 published crop-specific field trial datasets spanning 12 relevant industrial crops and discusses their suitability for cultivation on unfavorable soil types (USTs). It was shown that the perennial species Miscanthus (Miscanthus Andersson) and reed canary grass (Phalaris arundinacea L.) performed well on USTs with both high clay and/or high sand contents. Information on stoniness (particles sizes > 2 mm), where mentioned, was limited. It was found to have only a small impact on biological yield potential, though it was not possible to assess the impact on mechanization as would be used at a commercial scale. For soils with extreme clay or sand contents, half of the crops showed moderate suitability. The large yield variations within and between crops revealed large knowledge gaps in the combined effects of crop type and agronomy on USTs. Therefore, more field trials are needed on diverse USTs in different climates with better equipment and more consistent measurements to improve the accuracy of potential yield predictions spatially and temporally. Additionally, larger trials are needed to optimize cultivation and harvesting.

Potential Areas in Poland for Forestry Plantation

Plantations have many advantages when compared to natural or semi-natural forests, such as shortening production cycles, the production of wood with specific characteristics, and near-market production concentrations. The intensive development of this form of industrial wood production is practiced all over the world. The wood industry in Poland struggles in recent years, with a large shortage of wood. The deficit of wood has been accumulated for several years and is steadily increasing. One of the possibilities to change this trend can be development of fast-growing trees plantations. The main aim of this study was to determine the potential of land in Poland, which could be used for the cultivation of fast-growing trees plantations. The analyses took into account the area and marginal agricultural land. The potential plantation land areas were determined for poplar cultivar “Hybrid 275” and European larch (Larix decidua Mill.). The results show a possibility to generate a considerable area that can be developed into plantations of fast-growing trees in Poland. According to the analyses carried out for the purpose of this study, with only 5% use of the sown area and 5% use of forest lands, as well as the boscage (wooded land and bushy land), it is possible to obtain approximately 0.6 MM ha of land for fast-growing tree plantations. In the case of planting 50% of these lands with larch and 50% with poplar, and if a 50% capacity of the plantation is assumed, it will be possible to obtain nearly 6 MM m3 of wood per year.

Biomass Yield of Selected Herbaceous and Woody Industrial Crops across Marginal Agricultural Sites with Shallow Soil

Agricultural land in Europe is affected by low rooting depth (LRD) on 27.9 Mha. This marginal agricultural land can potentially be used to grow industrial crops without directly threatening food security or biodiversity conservation. However, little is known about the yield performance of industrial crops at LRD conditions. This study therefore compiles and discusses the meaningful data available in scientific literature. Twelve relevant industrial crops were identified for Europe. Currently, robust information on good growth suitability for LRD conditions is available for only one industrial crop, namely reed canary grass (RCG). Because this information was taken from field trial results from a single site, it remains unclear what role other growing conditions such as soil quality and climate play on both the yield level and the biomass quality of RCG under LRD conditions. These uncertainties about the quantitative as well as qualitative performance of industrial crop cultivation on marginal agricultural land characterized by LRD represent a major agronomic knowledge gap. Here, more knowledge needs to be compiled through both expanded crop science activities and improved international information exchange to make more optimal use of the large LRD areas available for the transition to a bioeconomy.

Mapping of Sub-Optimal Land Based on NDVI Sentinel 2a Value: Preliminary Study

Normalised Difference Vegetation Index (NDVI) is one of the vegetation indices used to analyse vegetation density. This study presents the potential use of NDVI to map dry-marginal-agricultural land (Dry-MAL). The study conducted in the eastern part of Situbondo, which includes three districts, namely, Arjasa, Asembagus and Jangkar. Sentinel-2A (recorded in 2018) and 450 Control points (GCPs) are used as the primary input. The region is an area with distinctive climate characteristics, where the dry season is longer than the rainy season. Analysis using "SNAP plug-ins" and "QGIS". Research procedures include (1) data inventory, (2) data pre-processing, (3) data processing and (4) accuracy testing. The NDVI classification can distinguish six (6) classes of land-use, i.e., water bodies, residential areas, dry MAL, non-irrigated rural area, irrigated paddy fields, forest-plantations. The NDVI classification produces Overall and Kappa accuracy values = 66,9% and 61,6%. Although the overall and kappa accuracy is below the standard, however, the result will benefit for further research of index vegetation or soil more applied for the identification of Dry-MAL

Economic Comparison between Pasture-Based Beef Production and Afforestation of Abandoned Land in Swedish Forest Districts

Large areas of agricultural land have been abandoned or are at risk of being abandoned such as small scattered fields and pastures in forest-dominated landscapes are unsuitable for modern mechanized agriculture and cost-efficient grazing. These areas have therefore become unprofitable to cultivate and graze. Spruce planting has been seen as the obvious alternative on these lands but is today questioned from landscape points of view. Now most abandoned land is left for natural afforestation. This study aims to compare the profitability in use of abandoned or marginal agricultural land in Swedish forest districts for spruce planting, natural birch afforestation, or organic beef cattle grazing large pasture-forest mosaics. The pastures consist of remaining semi-natural pastures, abandoned and marginal agricultural land, and adjacent forest land. Calculations of contribution to land, management, and risk suggest that, given present supports and environmental payments, organic beef production with herds of more than 20 suckler cows in large pasture-forest mosaics could be more profitable than forestry, except for in the most fertile areas of southern Sweden, where spruce planting has the highest contribution. Future tree breeding progress and possible decrease of livestock-related support and environmental payments would however increase the competitiveness of resumed afforestation relative to beef production.

Marginal Agricultural Land Low-Input Systems for Biomass Production

This study deals with approaches for a social-ecological friendly European bioeconomy based on biomass from industrial crops cultivated on marginal agricultural land. The selected crops to be investigated are: Biomass sorghum, camelina, cardoon, castor, crambe, Ethiopian mustard, giant reed, hemp, lupin, miscanthus, pennycress, poplar, reed canary grass, safflower, Siberian elm, switchgrass, tall wheatgrass, wild sugarcane, and willow. The research question focused on the overall crop growth suitability under low-input management. The study assessed: (i) How the growth suitability of industrial crops can be defined under the given natural constraints of European marginal agricultural lands; and (ii) which agricultural practices are required for marginal agricultural land low-input systems (MALLIS). For the growth-suitability analysis, available thresholds and growth requirements of the selected industrial crops were defined. The marginal agricultural land was categorized according to the agro-ecological zone (AEZ) concept in combination with the marginality constraints, so-called ‘marginal agro-ecological zones’ (M-AEZ). It was found that both large marginal agricultural areas and numerous agricultural practices are available for industrial crop cultivation on European marginal agricultural lands. These results help to further describe the suitability of industrial crops for the development of social-ecologically friendly MALLIS in Europe.

MAPPING TREES ON FARMLANDS USING OBIA METHOD AND HIGH RESOLUTION SATELLITE DATA: A CASE STUDY OF KORAPUT DISTRICT, ODISHA

<p><strong>Abstract.</strong> Agroforestry is an integrated self-sustainable land use management system that is not only capable of producing food from marginal agricultural land but also capable of maintaining and improving the quality of environment. Accurate assessment of trees on farmlands i.e. agroforestry would help in determining their contribution in meeting timber demand and also in carbon sequestration vis-a-vis climate change mitigation. In the present, high resolution multispectral satellite imagery (LISS-IV) has been used for mapping and estimating agroforestry area in Koraput district of Odisha. Both supervised and Object based Image Analysis (OBIA) classifications methods have been applied. In case of supervised maximum likelihood method, those pixels are fully captured where trees exist, whereas in OBIA captures trees according to their crown shapes. This proved OBIA method to be better in identification of trees on farmlands (scattered trees, boundary, and block plantations) than supervised method. This can lead to accurate estimation of area under trees in scattered form, in linear form and also in patch form. Improved results were obtained in case of OBIA classification with more than 90% accuracy. This research implies that remote sensing provide promising tools for evaluating and mapping of agroforestry at district level. Hence, the proposed approach of using high resolution remote sensing data in conjunction with OBIA method would be promising for mapping agroforestry area.</p>