Rhododendron is a well-known genus consisting of commercially valuable ornamental woody plant species.  Heat stress is a major environmental factor that affects rhododendron growth.  Melatonin was recently reported to alleviate the effects of abiotic stress on plants.  However, the role of melatonin in rhododendron plants is unknown.  In this study, the effect of melatonin on rhododendron plants exposed to heat stress and the potential underlying mechanism were investigated.  Analyses of morphological characteristics and chlorophyll a fluorescence indicated 200 µmol L^–1 was the optimal melatonin concentration for protecting rhododendron plants from heat stress.  To elucidate how melatonin limits the adverse effects of high temperatures, melatonin contents, photosynthetic indices, Rubisco activity, and adenosine triphosphate (ATP) contents were analyzed at 25, 35, and 40°C, respectively.  Compared with the control, exogenous application of melatonin improved the melatonin contents, electron transport rate, photosystem II and I activities, Rubisco activity, and ATP contents under heat stress.  The transcriptome analysis revealed many of the heat-induced differentially expressed genes were associated with the photosynthetic pathway; the expression of most of these genes was down-regulated by heat stress more in the melatonin-free plants than in the melatonin-treated plants.  We identified RhPGR5A, RhATPB, RhLHCB3, and RhRbsA as key genes.  Thus, we speculate that melatonin promotes photosynthetic electron transport, improves Calvin cycle enzyme activities, and increases ATP production.  These changes lead to increased photosynthetic efficiency and CO₂ assimilation under heat stress conditions via the regulated expression of specific genes, including RhRbsA.  Therefore, the application of exogenous melatonin may increase the tolerance of rhododendron to heat stress.

    A process-oriented methodology to conduct precise evaluation temporally and spatially on temperature suitability for potato growth was applied in China. Arable lands in China were gridded with 1 km×1 km geographic units, and potential potato phenology in each unit was automatically identified in terms of the potato planting initial temperature and effective accumulated temperature. A temperature thermal response coefficient model was used to compute a temperature suitability value for each day of potato phenology in each geographic unit. In addition, five temperature suitability ranking methods were applied to define suitable areas: (1) upper fourth quantile, (2) median, (3) expected value+1/4 standard deviation, (4) expected value+1/2 standard deviation, (5) expected value+1 standard deviation. A validation indicator was innovated to test the effectiveness of the five ranking methods. The results showed that from a strict degree point of view, the five methods sequence was as follows: 1=3>4>2>5, with a and c determined as the two best ranking methods. For methods 1 and 3, the suitable potato growing area was 1 of 57.76×10⁴ km². In addition, the suitable areas were spatially coincident with the main potato producing counties. The study output technically supports the proposal from China’s government that there is a large potential area to grow winter-ploughed potato in South China because the potential suitable area for growing potato is approximately 2×10⁷ ha. In southeast Heilongjiang and east Jilin, where it is hilly and mountainous, there are still some potentially suitable areas for potato growing accounting for nearly 2.32×10⁶ ha. The authors suggest to optimize the agricultural regionalization and layout in China and to adjust the cropping pattern structure.

  In this paper, authors established a farmer crop selection model (FCS) for the three provinces of Liaoning, Jilin and Heilongjiang of the Northeast China. With linking to the environmental policy integrated climate model (EPIC), the simulated results of FCS model for maize, rice and soybean were spatialized with 1 km×1 km grids to obtain cropping pattern. The reference map of spatial distribution for the three staple crops acquired by remote sensing imageries was applied to validate the simulated cropping pattern. The results showed that (1) the total simulation accuracy for the study area was 78.62%, which proved simulation method was applicable and feasible; (2) simulation accuracy for Jilin Province was the highest among the three provinces with a rate of 82.45% since its simple cropping system and not complex topography; (3) simulation accuracy for maize was the best among the three staple crops with a ratio of 81.14% because the study area is very suitable for maize growth. We hope this study could provide the reference for cropping pattern forecasting and decision-making.