Short-Term Impact of Multi-Cropping on Some Soil Physical Properties and Respiration

Growing as much crop biomass as possible in the shortest possible time is the target for most bio-energy producers. However, according to the requirements of the Green Deal, the consumption of fertilizers and crop protection products will have to be significantly reduced between 2023 and 2027. In order to meet all the necessary conditions for the production of biomass, a stationary field experiment was carried out at the Experimental Station of Vytautas Magnus University, Lithuania, in 2020–2021. Multi-cultivations of maize, hemp and faba bean were investigated. The aim of this study was to ascertain the impact of multi-cropping intensity on soil structural composition, stability, penetration resistance and gas concentration–respiration. As expected, multi-cropping stabilized the gas concentration and emission from the soil and decreased the proportion of micro-structures in the top soil layers. However, the stability of the soil decreased in all the experimental plots. Gas concentration and respiration mainly depended on soil structural composition, temperature and moisture content. The results of the experiment suggest performing investigations at a long-term scale because the intensive variation of meteorological conditions had a higher impact on the soil properties than the multi-cropping systems.

Crop Intensity Mapping Using Dynamic Time Warping and Machine Learning from Multi-Temporal PlanetScope Data

Crop intensity information describes the productivity and the sustainability of agricultural land. This information can be used to determine which agricultural lands should be prioritized for intensification or protection. Time-series data from remote sensing can be used to derive the crop intensity information; however, this application is limited when using medium to coarse resolution data. This study aims to use 3.7 m-PlanetScope™ Dove constellation data, which provides daily observations, to map crop intensity information for agricultural land in Magelang District, Indonesia. Two-stage histogram matching, before and after the monthly median composites, is used to normalize the PlanetScope data and to generate monthly data to map crop intensity information. Several methods including Time-Weighted Dynamic Time Warping (TWDTW) and the machine-learning algorithms: Random Forest (RF), Extremely Randomized Trees (ET), and Extreme Gradient Boosting (XGB) are employed in this study, and the results are validated using field survey data. Our results show that XGB generated the highest overall accuracy (OA) (95 ± 4%), followed by RF (92 ± 5%), ET (87 ± 6%), and TWDTW (81 ± 8%), for mapping four-classes of cropping intensity, with the near-infrared (NIR) band being the most important variable for identifying cropping intensity. This study demonstrates the potential of PlanetScope data for the production of cropping intensity maps at detailed resolutions.

Active-passive and passive-passive configurations of combined tillage implements for improved tillage and tractive performance: A review

Proper selection of energy-efficient agricultural machinery helps to reduce drudgery, increase cropping intensity and reduce time required for field preparation. With conventional tillage implements, multiple passes are required to obtain desired seedbed which increase soil compaction due to repeated movement of tractor in field. With combined tillage implements two or more tillage implements are combined to reduce time and fuel energy required for seedbed preparation. In this paper, various researches on active-passive and passive-passive configurations of combined tillage implements have been discussed along with their working principles. It was found that these were associated with less draft, specific energy, and tire slippage compared to conventional implements which provides a sound basis for using them with suitable engine power to improve the power utilization of tractors. Hence, use of these implements could help to reduce soil compaction, labour, fuel cost as well as save time in preparing seedbed. More analytical studies and classical approaches are needed to predict energy requirements of these implements from the knowledge of individual energy requirements of conventional implements to help in proper matching of tractor-implement and also to develop decision support systems. Considering their promising outcomes, they will emerge as effective tools to improve agricultural mechanization.

Characterisation of rice fallow period for increasing cropping intensity in Khordha district of Odisha

The possibility of increasing the cropping intensity in Khordha district was assessed by block-wise characterisation of rainfall, soil texture, available water holding capacity of soil and district level temperature during the rice fallow period as well as deciding the appropriate sowing window for both kharif and rabi crops. More than 50% chances of occurrence of wet weeks at the beginning of the kharif season (20-22 SMW) indicated that the summer ploughing and initial seed bed preparation could be taken up during the period followed by sowing of rice from 23 SMW. The 42-43 SMW with greater than 30% initial probability of wet week at 20 mm threshold limit. Considering the length of growing period (LGP) available, the adjustment of rice variety duration by 10-15 days in medium land and advancement of pulse sowing almost by 15 days before harvest of the rice crop (Pira crop) in low land was registered as the best su suitable option for rabi pulses to ensure better utilisation of rice fallow. In addition to these, harvesting surplus water during kharif and storing in farm ponds for judicious utilisation during rabi season further enhanced the possibility of utilisation of rice fallow and increasing the cropping intensity. In the event of delayed monsoon the rice duration has to be adjusted accordingly not to sacrifice the designated suitable period for rabi pulses.

PENGARUH PROGRAM UPAYA KHUSUS (UPSUS) TERHADAP PRODUKTIVITAS, BIAYA POKOK PRODUKSI DAN PENDAPATAN USAHATANI PADI DI KABUPATEN PRINGSEWU

Rice is the staple food of Indonesian people. In 2014, its production was less than its need including its losses. Therefore, during 2015-2020, in order to increase the production through increasing its yield and its cropping intensity, the Ministry of Agriculture had been implementing the program of Upaya Khusus, called Upsus. The Upsus could be success if the farmers who participated in this program spent less the rice standard cost and obtained bigger profit. The question was whether the Upsus could increase yield, decrease standard cost and increase profit. Accordingly, the objective of this study was to answer this question. There were 30 respondents chosen by the simple random sampling method from six villages of three subdistricts. Each respondent was interviewed his farming budget in four seasons, i.e. rainy season 2014/2015, dry season 2015, rainy season 2017/2018, and dry season 2018. Consequently, the number of observation was 120. The data farming budget were used for getting the three following variables, i.e. yield (ton/ha), production standard cost (Rp/kg), and profit (Rp million/ha). The data were analyzed by using three multiple regression models. This study revealed that the Upsus was statistically significant on increasing its yield, decreasing its standard cost and increasing its profit. By implementing the Upsus, the increment in yield and profit of rice farming were 3 percent and 30 percent, respectively. The decrease in standard cost was 6 percent. The average yield, the standard cost and the profit of rice farming in Upsus were as follows 5,20 ton/ha, Rp4.154,-/kg and Rp6,82 million/haKeywords: profit, standard cost, upsus, yield

Assessing the Impact of Rythu Bandhu Scheme in Warangal District of Telangana

Rythu Bandhu Scheme (RBS) also Farmers investment Support Scheme is a welfare program to support farmer investment for two crops a year where the cash is paid directly by the Government of Telangana. A sample of 60 beneficiaries were selected from Warangal district of Telangana state. In order to find out the impact of RBS on beneficiaries - inputs purchasing power, continuity in farming, rural indebtedness, productivity, farm income(in Rs.) and cropping intensity were studied before and after implementation of RBS i.e., in 2016-17 and 2020-21 for beneficiaries. Based on the results in respective year, “Z” test was applied to find out the difference after the implementation of scheme. From the analysis, it was found that significant difference was observed among respondents with respect to inputs purchasing power (6.74*), continuity in farming (2.93*), rural indebtedness (4.02*), productivity (3.72*), farm income (4.53*). RBS is increasing the beneficiaries capacity to purchase inputs with timely performing agricultural activities, their likeliness to continue farming and better coping with debt.

Annual dynamic dataset of global cropping intensity from 2001 to 2019

The cropping intensity has received growing concern in the agriculture field in applications such as harvest area research. Notwithstanding the significant amount of existing literature on local cropping intensities, research considering global datasets appears to be limited in spatial resolution and precision. In this paper, we present an annual dynamic global cropping intensity dataset covering the period from 2001 to 2019 at a 250-m resolution with an average overall accuracy of 89%, exceeding the accuracy of the current annual dynamic global cropping intensity data at a 500-m resolution. We used the enhanced vegetation index (EVI) of MOD13Q1 as the database via a sixth-order polynomial function to calculate the cropping intensity. The global cropping intensity dataset was packaged in the GeoTIFF file type, with the quality control band in the same format. The dataset fills the vacancy of medium-resolution, global-scale annual cropping intensity data and provides an improved map for further global yield estimations and food security analyses.